Reality, Artificial Reality and Illusions

Professor Santanu Chaudhury

We experience the world through our senses. Reality is the aggregate of all that exist around us, as opposed to those which are only imaginary. However, we have different interpretations of reality.

Philosophers talk about simulated reality. We can try to describe the concept with reference to digital gaming. We can imagine a character in the game, The algorithm that represents the character and the algorithm that represents the game environment in which the character operates are intertwined at many levels. The algorithms in the game take into account the environmental variables and some of the state variables of the character to depict the behaviour of the character and the environment of the game. The visual rendition on the screen is for our benefit – interface is only for the user who is controlling the digital simulation of the gaming world. It is a subjective projection of some of the variables within the program so that we can experience the sensation of being in the game. But it is, obviously, not for the characters in the game. The interface has no other reason to exist except to serve us. Just like we are experiencing simulation of the game, our physical reality can be the simulation game for someone else. This is akin to the classical concept of Maya. As per Advaita Vedantic Hindu philosophy – “the existence of, or our perception of, an independent, substantial world of real objects, persons, and processes must be grounded in some pervasive error. We take the unreal for the real and the real for the unreal. This is māyā.” Whenever the ‘I’, ‘me’, or ‘mine’ is present, according to Advaita, there also is māyā. (Maya—A Conceptual History, Dr Arpita Mitra, Prabuddha Bharat, January 2020)

But, there can be multiple ways of exposition of the simulated reality. Looking at it from the perspective of an individual perceiving the world – with I as the principle instrument of the epistemology, poetic expression of Rabindranath (in his poem Ami) puts human at the centre of the universe…reality emerges through his perceptions. Tagore says that the colour, which a human being can perceive, tinges the emerald as green and the ruby as red. It is not the sun alone, but it is the ability of man's visual perception, which illuminates the sky. The rose is beautiful only because man perceives it as beautiful. Human beings are not elements for some one’s experiments. Man is at the core of creating what the beauty of reality is. Rabindranath’s poetic assertion claims that man is at the centre of what is to be perceived of reality:

“Amari chetanar range panna holo sabuj, chuni uthlo ranga hoye. Ami chokh mellum akashe, jwale uthIo alo pube paschime. Golaper dike cheye ballum "sundar," sundar holo se.”

By virtue of creative imagination with digital tools at his(her) disposal, man can create world of his own defining new shades of reality.

Virtual reality (VR) is a simulated experience, which a human creates, with the help of technological interventions. A virtual reality environment is an immersive, interactive and digitally created environment. It can be similar to or completely different from the real world An immersive environment generates perceptual experiences from a perspective within it and not an observation from the outside (like a game or a movie). User gets the sense of “presence”: that is, the sense of really being present in the virtual world. There can be also variants of these systems, for example a computer terminal based interactive 3D world.

Computer generated virtual reality environments are virtual worlds, which we create, which we inhabit. Virtual objects are objects contained in the virtual worlds. In virtual worlds we interact with virtual objects. Virtual objects include avatars (virtual characters), virtual buildings, virtual weapons, and virtual treasures. Virtual objects are real or unreal. Virtual worlds are, in many cases fictional worlds – product of pure imagination and creativity. However, If a human in physical reality plays the role of a character in a game, the event in a game is fictional but the physicality of the underlying bodies and movements are real. This is more apparent if we examine non-game VR environments. Consider a conference happening in a virtual environment – realization is artificial but underlying physicality is real. Still non-real element comes in when in virtual world we are represented by bodies which we do not have and bodies are placed close together, when in real life we are thousands of kilometers apart. Therefore, we move into a space where real and unreal are enmeshed. Physical me and my avatar are both real and not a fiction. The immersive conferencing environment is also an actual operational context with real time response. As a creator, you are creating spaces which are not there in the natural world but are not fictional.

Virtual objects are nothing but digital entities – they are implemented through data structures and linked code which defines behavior of a digital object. Behavior of the virtual objects are typically causal in interaction with other digital objects. Spatial relations (tend to) serve as a measure of causal interactions. Space serve as a locus of continuous motion. Spatial constraints characterize dynamic evolution of and interaction between underlying objects. However, these digital objects are physically very distinct from the perceptual effects that they can induce. Going back to the red roses. Digital objects corresponding to the virtual red roses are not red (it may be a piece of code running on a hardware). Red roses are red, because of the colour that a human observer perceives when the code is executed. Digital red roses are red because human wants them to be red and implemented the technology to make them appear red to human eyes. These experiences delivered by a digital object in a virtual world are linked to the mental state and expectation – just like a piece of paper is perceived as money because we have a mental model of the money. Digital objects create that virtual world what we want to experience – man is at the centre of what is to be perceived as virtual in the digital world. Centrality of the human in whatever world we want to be in, is fundamental. Real and virtual are two sides of the same coin, the coin exists because we have the ability to perceive, imagine, create and experience. What is important is that, experiences in the virtual world are non-illusory perception when we are not in a world of fantasy.

Today we interact, exchange, buy, sell, work and play online in a digital world - all things which were part of our daily physical in-person interaction. Digital objects are creating a virtual world around us which is real but also virtual. You are communicating with a real person, but his or her existence in your physical world at that point of time is virtual. With virtual reality delivering stronger perceptual connect across distances - real and virtual are intermingled – augmenting your reality with virtual. Now, we are breaking the boundaries - we are moving into a new universe- metaphysical universe – metaverse – blurring the line between real and unreal and surreal, between creators and creations. Technology is enabling us to create a new reality – which would basically enable us to convert most of our activities of the real world to a digital space, integrating real world to the virtual, creating a world of our own. You can visit virtual space of others if you have the permission. You have the ability to create your own avatars – dual identity - which will go to work, interact with friends, may travel to exotic destinations enabling you to experience everything from the comfort of your home. Your imagination can also enable you to explore different worlds – like say, world of beautiful butterflies, if you have tools and creativity to explore. You can create new forms of creative compositions: experiential performances – dance, theatre, animated paintings, literary creations may become interactive experiences. You can share the excitement of new creations in a new medium.

Metaverse provides new opportunities for economic and professional activities, collaborations and markets. Markets can be new global opportunities for enterprises including MSME’s but also can be monopolistic and exploitative. You can even create multiple avatar of yours – creating multiple identities, living multiple lives in the virtual space. New questions regarding human sensitivity, values, ethics and morality cannot be avoided.

At a different level, metaverse also creates opportunity to promote a new world. You can, “Be the change you want to see in the world” (M.K. Gandhi) by creating a virtual connected world with the new values and sensibilities. If there is fear among us, if rights of free expressions are challenged, if rights of scientific thoughts are compromised, Metaverse provides an opportunity to create a courageous journey for a transformational social change in the true tradition and belief of free, open and democratic connected world. This journey can truly belong to all human beings in the connected world. This is the power to create a new world. You need not wait for the reality to change but technology has enabled us to build our preferred reality- a better reality to live with. This is not illusion.

Professor Santanu Chaudhury

Director

Professor
Department of Computer Science and Engineering

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Editorial

Prasenjeet A. Tribhuvan

By their very nature, rankings, of all kinds, seldom represent institutions in their entirety. However they can be pragmatic markers of what an institution is doing well and what it is not. As IIT Jodhpur completes one more year since its inception, we are met with the pleasant news of a surge in our NIRF ranking. Techscape, the journal that encapsulates the immense research capability and diversity of our vibrant institute and its bright inhabitants has emerged as a faithful resource which continues to inscribe the institute’s journey to imminent eminence.

Since modernity as we know it was ushered in with the socio-scientific revolution in Western Europe of 17th century, most of our sciences and social sciences have been influenced by an epistemic binary of ‘Nature/Culture’ which unfortunately later metamorphosed into the antagonism of Nature v/s Culture. This meant that Culture, which is a collection of all activities that humanity undertakes, including the activity of Science, was posited against Nature, thereby indicating that the main objective scientific endeavor was to exploit nature to meet humanity’s utilitarian needs. However an array of human-induced ecological disasters creating immense loss of human life and/or degradation of quality of life forced us to realize that humanity’s future is intricately wound with the future of our environment. Culture in general and Science in particular should work with Nature, and not against it and recent global forays into science and engineering echo this realization. The foundation day issue of Techscape this year to a great extent represents this organic progress of scientific and engineering research into technologies that will lead us to an eco-friendly, sustainable future.

Dr. Manasi Mukherjee and Prof. Mitali Mukherjee’s review of ‘Bioblitz’ initiative underscores the importance of engaging with our immediate surroundings as they bring forth the ecological wealth and diversity of our campus. Dr. Srijan Sengupta et al write about how we can make electrical vehicles more efficient in the Scientific and Social Connect section. Dr. Lipika Dey delves into the novel and important domain of sustainability analytics and elucidates how organizations can employ Artificial Intelligence to assess their sustainability metrics. This issue has a rich collection of Research Snippets with Dr. Erande et al writing on ‘Green Chemistry’ an exciting branch of organic chemistry that looks to eradicate use and creation of hazardous compounds in chemical reactions. Prof. Rangra et al present their ongoing work on Multi-electrode Sensor system to increase efficiency in industrial processes. Dr. Pranay Ranjan writes about Borophene, a promising material that can have multiple uses in coming times. Prof. Ashutosh Alok and Neetu Chandra Chundawat delve into the exciting world of ‘beautiful’ and ‘charm’ physics for a more accurate understanding of fundamental reactions in nature. Dr. Nipun Arora et al describe the design and development of an insect inspired flapping wing Micro air vehicle, which is an accurate paradigm of how nature can inspire smart and efficient designs in complex MAV systems. Dr. Amitava Bannerjee presents his group’s work on designing 2D catalyst for the efficient production of the significant category of ‘Green Fuels’ and making Green Fuel more economically viable. Finally to round things up, we have Prof. Chakraborty and Narndra Kumar’s article on Cascaded Latent Heat Storage system, Dr. Arpit Khandelwal and Sanchit Kundal writing on Hemoglobin detection using ultra low power optical micro-disk resonators, Dr. Amit Bhardwaj et al writing on CatBoost and its use in modeling of deformable objects and Dr. Kunwar Aditya’s research snippet on dV/dt induced false-turn-on of a MOSFET.

We hope you enjoy reading this issue of Techscape as much as we have enjoyed putting it together. Finally, we are immensely grateful to all our contributors and readers as we look forward to a bright and engaging future for the journal and for all of us.

Prasenjeet A. Tribhuvan

Assistant Professor

IITJ-Bioblitz

Manasi Mukherjee and Mitali Mukerji

Scientists and Researchers at IITJ are trying to understand the adaptive nature of xerocoles, the well adapted flora and fauna of Thar through their, morphology, physiology, behaviours, genetics etc. Motivated by Albert Einstein’s famous saying, "Look deep into nature, and then you will understand everything better", this study shall provide researchers with knowledge of adaptive design principals that shall give rise to bioprospecting and bioinspired solutions as well as a prospect in large for conservation, rewilding or restoration of degraded ecosystems in this arid eco-region. The objective of the work calls for a large amount of ecological and environmental data. To reduce the time and cost of the work, a citizen Science initiative has been approached called IITJ-Bioblitz by the team members of the project Thar-DESIGNS from IIT-Jodhpur, under the guidance of Prof. Mitali Mukerji, Head, BSBE. The project aims to connect and aggregate local ecological information through a crowdsourced approach and at the same time inculcate a spirit of curiosity, appreciation, ownership and responsibility for health of the ecosystem.

The IITJ-Bioblitz program began with the exact words of Pythagoras, "Leave the roads; take the trails." Inaugural walks were organised on the 25th and 26th June 2022 for IITJ-Bioblitzers. Prof. Santanu Chaudhury, Director, IITJ and Prof. Sampat Vadera, Deputy Director, IITJ, inaugurated the program and participated in the walk, motivating all the participants. Around 43 citizens of IITJ, including students, faculties and their family members from varied age groups participated in the walk led by a few volunteers with an experienced ecologist Dr Manasi Mukherjee. Participants were guided to spot, identify and learn about the vivid local flora and fauna including the birds, reptiles, rodents, mammals, native vegetation and their interactions, ecology and behaviours. An app “Prakriti” developed by an IITJ team led by Dr. Suchetana Chakraborty, CSE, was introduced to the participants for acquiring the crowdsourced ecological data for scientific use. Participants were motivated with an Eco-BEGINNER badge that shall be upgraded based on their engagement and contributions to the BIOBLITZ program. To encourage participation and keep up the interest and excitement, Bioblitz is planning photography contests, various awards like Eco-Champ, Eco-Achiever and Eco-Literates and Prizes in future.

The participants of IITJ-Biolblitz were able to record around 15 species of native flora, 26 species of birds, and many other common fauna like garden lizards, monitor lizard, squirrels, Indian gerbil, Chinkara, etc. Participants had fun differentiating between the brown rock-chat and female Indian robin, locating a Plain prinia from its call, watching a synchronous flight of Indian silverbill flock, and understanding how galls are formed on Khejri trees. Some behavioural observations like inverted nest making of Baya weavers, mud pellet hanging nests of Dusky -crag martin, alarm calls and hovering behaviours in Indian bushlark, feeding from dump-yards by Common Mynah and martins, most birds being ground dwellers and insect feeders, grabbed their attention. "In every walk with nature one receives far more than he seeks" (John Muir), so did our participants who had joined the walk to spot few birds, but were extremely excited to observe and learn much more. They noticed the garden lizard change its colour from light to bright and dark colours when alarmed or under stress. They also observed how Bistanta mexicana, has an incredible camouflaging body structure and colour, mimicking a dry piece of grass. They were surprised to discover the number and depth of desert gerbil burrows which they had mistaken for burrows of snakes. Newer insights on how various plants are associated with the environment, respective fauna and resident population were discussed on the walks. A group of enthusiasts, who had joined the Bioblitz program for a leisure nature walk found themselves better connected, more educated, intrigued, and highly involved with the process, summing the ultimate goal of the program. All Eco-beginners have shown utmost interest in helping science grow through their observations and participation. As an outcome of the program, a large number of images and corresponding data have been uploaded in the Prakriti app. Discussions amongst participants indicated the presence of white-footed fox, Desert hare, Asciatic wild-cat, Nilgai and Caracal in the campus.

As IITJ-Bioblitz is a continuous program, periodic activities shall continue. Though the inaugural walk began with birding, future events shall include walks for native flora, insects, mammals, rocks, soil, microbes and various other aspects. Participants can choose their field of interest and participate willingly.

Team members of IITJ-Bioblitz inaugural program Prof. Mitali Mukerji Dr. Manasi Mukherjee Dr. Suchetana Chakraborty Dr. Ayan Sadhukhan Mr. Rishabh Jain Mr. Sachin M Rathod Ms. Shivangi Sharma

Special thanks to Mr. Meraj for covering the IITJ-bioblitz program and posting this wonderful vlog that has details of the program, interaction with participants and their feedback about the event. ITJ-Bioblitz program considers and welcomes such activities under citizen science initiative. This shall help us build a community that engages more participants and enthusiasts.

AI-driven Sustainability Assessment - what, why and how

Lipika Dey

Sustainability assessment can be defined as the process of identifying, measuring, and evaluating the potential impacts of alternatives in the context of enterprise decision making and policy planning to ensure sustainable development. Sustainability practices aim towards the benefits of society as a whole. In 2015, the United Nations proposed 17 sustainable goals (SDGs) to achieve this. These goals provide general directions for policy planning and responsible actions to address issues such as eradication of poverty, hunger and inequalities, ensure gender equality, provide facilities like health education, clean water and sanitization to all, focus on clean energy, encourage responsible consumption and production, reverse climate change, protect land and water resources, ensure justice for all and also towards building sustainable cities, communities, institutions and partnerships. While the goals broadly cover all aspects of environment, society and corporate governance, progress in each of these areas are made easier to track through the introduction of 169 targets that are measurable and are expected to be achieved by all organisations by 2030. Sustainable decision making focuses on actions that can help an organisation achieve these targets.

An organization is measured by assessing its performance along all the three dimensions of sustainability - environment (E), society (S) and governance (G), collectively referred to as ESG. Though standards are still emerging, each area has a set of key performance indicators which are tracked to evaluate sustainability progress and design policies for further improvement in future. Conscious investors today demand visibility into a company’s sustainability practices. Many companies are therefore publishing an annual sustainability report in which they provide a detailed assessment of risks perceived and sustainability measures undertaken. It has been found that ignoring sustainability can cause upto 6% decline in a company’s revenue, as negative perceptions can be amplified through social media influencers, even before a company can react to it.

Sustainability Metrics - Tracking to assess

Sustainability assessment is a complex task. Organizations like Global Reporting Initiative (GRI) and Sustainability Accounting Standard Board (SASB) suggest tracking various data points for the purpose. In this section we present some key sustainability metrics that are monitored for assessing the ESG impact of a company.

Environmental sustainability metrics can be put under five broad areas as mentioned below :

Climate risk - Under this metric, an organisation assesses their exposure to climate-related risks due to the changing environment and physical risks of climate change. Oft-reported perceived risks are regulatory transition risks and physical risks from climate change that could negatively impact productivity and success. Forward-looking scenario based analysis help companies develop effective risk mitigation strategies across corporate asset locations, supply chains, and product life cycles.

Carbon emissions - As per the Paris Agreement adopted in 2015, nearly all countries have agreed to reduce global greenhouse gas emissions in an effort to limit the global temperature increase to 2° Celsius above pre-industrial levels by 2050. Consequently, companies are actively migrating from using fossil fuels like coal to renewable and cleaner energy sources like natural gas, wind, water, solar energy.

Energy consumption - There is also an overall effort to reduce energy consumption altogether in order to reduce greenhouse gas emissions as well as emission of other compounds that are detrimental to the environment.

Water Usage - Water is a critical and primary metric, whose use and wastage need to be monitored and restricted within organisational premises. Reducing water wastage, leakage etc. are also part of this agenda. Industries also have to be particularly conscious about protecting water from being polluted due to their site activities like mining, construction, chemical usage etc. Water pollution is measured by the “total natural capital cost of the environmental impacts from heavy-metal and pesticide pollution or from excess fertilizer use causing algal blooms.”

Waste & pollution - Waste management is a broad category that includes monitoring food waste, agricultural and animal waste, medical waste, radioactive waste, hazardous waste, industrial non-hazardous waste, construction and demolition debris, extraction and mining waste, oil and gas production waste, fossil fuel combustion waste, and more. This

The above metrics provide broad guidelines to the companies about elements to focus on and also what to track and monitor. Data collection from different sources is an important activity. The data, measured against the company’s goals, is the space where ESG operates. Deployment of IoT (Internet of Things) powered sensor-based platforms help in measuring and tracking many of the above-mentioned parameters. Analytical frameworks sitting on top of these platforms provide the necessary tools to collate, analyze, report and also perform predictive analytics and what-if reasoning with the data to assess and select the right alternatives for a better future.

Tracking social sustainability is somewhat more complex since these goals can be a mixture of subjective and objective. Three key metrics tracked are gender pay equity, diversity and inclusion and wage levels. These are centred around ensuring a free and fair workplace which focuses on equality of all and follows labour laws.

The fourth metric measures risks resulting from incidents involving child and forced labour. This is an important source of risk for all companies who outsource work to third party vendors, as compliance to sustainability demands that all stakeholders that a company deals with are also sustainable.

The fifth metric attempts to ensure health and safety that covers health risks perceived for all stakeholders. Ensuring safe workplaces and monitoring occupational health hazards of employees has been an area of focus for quite a few years now. This metric also assesses safety risks and vulnerabilities of society at large, who may become a part of the company’s ecosystem by virtue of their geographical location. Thus all activities that may be polluting air or water or affecting biodiversity etc. have to be accounted for.

Another important social metric is the effort put towards training employees both in terms of training hours and money spent behind it. This measures the company’s commitment to prevention of on-the-job accidents while dealing with complex machinery, equipment maintenance, adherence to safety measures in construction or mining sites and so on.

An organisation’s commitment towards innovation is also assessed as a part of its social commitment. A culture of innovation provides employees the freedom to experiment. Some organisations measure it by the percentage of time employees are encouraged to spend on tasks that may fall outside their scope of work. This is tracked through the number of patents filed or publications generated as also the incentives provided for such activities.

Finally, since one of the key targets of the sustainability program is to ensure a better world for all, it is very important to track all activities that are directed towards “Giving back to the community”. Awareness programs, fitness initiatives, greening activities and many other programmes are conducted by organisations to ensure the society at large benefits from their work. An important aspect is to come up with methods to measure the success of these programmes.

The third pillar of sustainability is to ensure transparency, fairness, integrity and honesty in its governing structure. Ensuring diversity and inclusion of all communities in all boards and committees, holding stakeholder meetings regularly, having financial fraud-control mechanisms in place, implementing processes to ensure compliance to regulatory standards are some of the metrics that are tracked under this category.

Not all the metrics mentioned above are actually quantifiable for assessment purposes. Many of them are intangible in nature. It is also obvious that the metrics are not totally isolated from each other, and each action plan should be formulated to ideally contribute to as many metrics as it can.

Responding to the growing demands from investors and customers, organisations publish different kinds of reports in which their targets, actions, activities, achievements and plans around the key metrics are disclosed. These disclosures being free-format, it is difficult to come up with objective assessments. There is no specific format or unit for reporting different items under a metric. Regulators across the globe are waking up to this requirement. The UK is the first country to mandate climate-related disclosures by 2025. The EU has also proposed its Corporate Sustainability Directive (CSRD). The US is also planning to come up with a framework for disclosure of ESG information soon. However, given the nature of the items, it is unlikely that sustainability assessment can be totally objective. A lot of subjective issues are likely to remain along with some vagueness and uncertainties inherent to the domain. Meaningful sustainability assessment has to be predictive in nature, which can predict the collective impact of an array of actions undertaken. It is precisely here that AI-based methods step in.

AI and Sustainability Assessment

If sustainability assessment begins with data acquisition, it starts making an impact only when the data is made use of. Some AI applications that have already made their presence felt are in the areas of energy use and storage optimization, balancing electric supply and demands in real time, managing microgrids for renewable energy and so on. Predictive maintenance of equipment based on sensor data not only increases the life-spans, but also goes a long way towards ensuring safe workplaces. Early warning systems based on failure prediction models also play a crucial role in avoiding mishaps. As the vision-based technologies mature, video monitoring solutions complete with automated detection of anomalous events and event-based alarm generation systems are being deployed in factories and assembly lines to avoid accidents. Pollution monitoring solutions for air and water are also gaining markets.

Working with climate-risk data turns out to be trickier. While the data shared by individual organisations are important, impact assessment in this case requires aggregate analysis. Experts are of the opinion that the expected outcomes assessed from the collective data reported do not match the reality. None of the climate risks have shown any signs of reversal.

Analysts are working on complex causal models to disentangle the complex causal relationships between the known causal factors like industry emissions, greenhouse gases or vehicular pollutants etc. and the observed variables like rising temperatures and sea-water levels, occurrence of natural disasters and so on. Without these causal models it is difficult to assess the short and long term impacts of the mitigation steps. Counterfactual reasoning is another important tool in this repertoire that is used by analysts to simulate non-existing situations in order to assess impacts of interventions and preemptive steps.

Going beyond the measurables, sustainability assessment also requires churning a lot of unstructured data that includes textual descriptions of events, actions, plans and policies available in reports and disclosures. Social media interactions with the outside world, consumer reactions to an organization’s stand, internal and external communications all provide valuable inputs for assessment purposes. Traditionally, third party assessors collected data from companies in the form of a survey to come up with a single numerical score. The scoring process was highly non-transparent and rigid. With increasing availability of public disclosures, it is now possible to employ Natural Language Processing techniques to extract relevant information from the reports, and use it within customized analytics platforms to obtain sector-specific or application-specific scores. Given the complex format of the reports, this poses many challenges to the natural language processing community. Challenges include automated classification and location of relevant information within reports, extracting the right unit of data using information extraction principles and then using them for analytics. Not all data reside in text boxes. Multimodal analysis of content to process and combine information from text, tables, graphs and images is another complex task.

The transformer-based language models provide strong foundations for building such applications, as they can encode the context of information very well. Trained on large volumes of sustainability-related open data like News articles, these models are capable of analyzing and extracting all relevant information from large reports in minutes. Building sector-specific and customized analytical models is now easy. Stakeholders can specify their own preferences and obtain performance report for the preferred area only. This has helped in democratization of sustainability analytics and assessment and is particularly important for scope-3 assessments, in which every organization needs to assess all partners. While an automobile manufacturing organization may have to focus on workplace safety aspects for its parts manufacturers, this is not likely to be the crucial aspect while selecting its financial service providers. Ability to drill down a score and have access to the underlying data that has led to the score is also leading to an increasing demand for in-house analytical platforms powered by natural language processing.

Qualitative aspects like expert comments and opinions on organisation actions as well as policies and regulations influence sustainability assessment in a big way. Debates, arguments, opinions and stances abound in this area, leading to a virtual sea of information that need to be carefully assessed before taking a decision. Transformer based language models are proving to be extremely powerful in encoding contextual semantics. An array of language applications have been built using these models that can perform diverse tasks like detecting topics, alignments, contradictions, sentiments, opinions, moods and stance from large collections of text. These technologies are being explored to provide augmented intelligence platforms with exploratory analysis capabilities to decision-makers who can obtain multi-perspective views of the underlying content before taking decisions. TCS ESG integration solution ((https://www.tcs.com/sustainable-finance-esg-integration-solution) is one such application intended to provide a 360 degree ESG view based on public disclosures and open media content gathered about companies. Figure 1 presents a screenshot from the system.

The use of technology in sustainability analytics today is largely restricted to monitoring and optimization of energy usage data. There is a huge unexplored possibility of using AI based analytics and reasoning to build impactful decision-making systems. AI also has an important role in detecting and exposing “greenwashing”. Greenwashing refers to the unethical process of conveying false impressions or providing misleading information about how sustainable or environment friendly a product, process or service is, even as reality speaks otherwise. Exposing greenwashing requires multi-source, multimodal feasibility analysis of complex data taking into account the attributes of the product or service, the purpose, the technology underneath and the claims. This article is intended to show the tip of the iceberg, with the hope that researchers of the future would feel excited enough to plunge into the ocean out there to ensure a greener earth before it’s too late.

References

Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104.

Smeuninx, N., De Clerck, B., & Aerts, W. (2020). Measuring the readability of sustainability reports: A corpus-based analysis through standard formulae and NLP. International Journal of Business Communication, 57(1), 52-85.

Ballestar, María Teresa, Miguel Cuerdo-Mir, and María Teresa Freire-Rubio. "The concept of sustainability on social media: A social listening approach." Sustainability 12, no. 5 (2020): 2122.

dV/dt induced false-turn-on of a MOSFET: What it is and how to avoid it?

Kunwar Aditya

In Figure 1, if the FET M1 turn-on suddenly, then rate of change of voltage at node U will cause displacement current through Miller capacitor CGD of the FET M2. This current causes voltage drop VGS,off across the turn-off resistor of M2. If VGS,off is greater than the threshold voltage VGS(th) of M2, it will turn-on. This phenomenon is known as false-turn-on or self-turn-on or parasitic-turn-on of a FET. This in turn will cause a direct short circuit across the DC supply.

It should be noted that, for medium to high voltage power devices (mostly IGBTs and SiC MOSFETs), it is a common practice to provide a negative Vdrv to prevent erroneous turn-on due to dv/dt phenomenon. However, for low-voltage power devices (<= 40V), both MOSFET and gate-driver are usually supplied from the same power rail (e.g., 12V battery in case of automotive application). Therefore, gate driver output also varies with input supply with maximum output clamped to maximum rail voltage and minimum to 0V for safety reasons. Nevertheless, for simplifying the derivation, Vdrv in this paper will be assumed to be zero when FET is turning-off. Therefore, using (1) and (2), and setting Vdr equal to 0, one can derive the VGS,off as in equation (3).

From (3), VGS,off is a rising exponential function with time-constant τ equal to (RG,off+Rgd,off)(CGS+CGD) and peak value equal to (R_(G,off)+R_(gd,off))C_GD (dV_DC)/dt. To avoid false turn-on one can either reduce the peak value of VGS,off below the threshold voltage VGS(th) of the FET or can increase the time constant τ.

To reduce the peak value, one option is to reduce RG,off. This can be achieved by using separate gate-resistors for turn-on and turn-off interval with resistor for turn-off interval lower than turn-on interval. Usually, it is a common practice to bypass the turn-on resistor RG,ON using a Schottky diode to limit the voltage generated on the gate pin of FET due to dv/dt. However, bypassing the external gate resistor will increase the dv/dt rate resulting in relatively higher voltage drop across Rgd,off which is still present in the current IG,off path. Therefore, this method works only if the value of Rgd,off is significantly lower compared to RG,OFF. Another solution is to add a transistor to the driver circuit that can bypass the dv/dt induced gate current during turn-off [2]. Such a solution is called an active Miller clamp. These solutions to reduce the induced voltage on the gate of MOSFET have been summarised in Figure 2.

One more effective way to avoid false turn-on is to increase the time constant τ of VGS,off so that it doesn’t reach its peak value during dv/dt interval, t. This can be achieved effectively by adding an external capacitor CGS,Ext between gate-source pin of FET. If τ>>t then, using Maclaurin expansion ex=1+x, equation (3) can be re-written as:

This essentially means that CGD and CGS behave like a capacitive divider. Therefore, to have a low sensitivity to parasitic turn-on, FETs with a large CGS/CGD ratio should be selected. Adding external CGS,Ext further increases the CGS/CGD ratio. However, it should be noted that the gate-source capacitor affects the switching speed of the FET, therefore, an optimum value must be selected for a given circuit.

To verify equation (3), an approximate small signal model of an STL64DN4F7AG dual channel automotive grade 40V MOSFET from STMicroelectronics[1] was simulated in LTspice as shown in Figure 3. In the Figure 3(a), RG,OFF is 10Ω, CGS is 611pF and CGD is 26pF, therefore time constant τ is 6.37ns. Supply of 16V is being turned-on and off in 50ns to have dv/dt of 0.32V/ns.

Same circuit was simulated in Figure 3(b) with CGS,Ext equal to 10nF to have a τ of 106ns which is almost two times the dv/dt interval of 50ns. For τ>dv/dt, VGS,off is given by equation (4) and is calculated to be 0.039V. Figure 4 and Figure 5 shows the simulation result for both cases, i.e., for τdv/dt period respectively. IGD can also be calculated as:

In Figure 4, one can see that the VGS,off reaches its peak value of 83mV during dv/dt interval. However, in Figure 5, since τ>>dv/dt, VGS,off manages to reach a peak of 33mV only. VGs,off start dropping once dv/dt period is over. IGD in each case is independent of RG,off and is equal to 8.32mA. This essentially verifies the concept of dv/dt induced gate voltage on MOSFET discussed above.

Author hopes that the concept presented in this paper might be useful to young researchers working in the field of power electronics. Interested researchers may read the full optimisation of half-bridge circuit in the paper ‘Optimizing switching performance of MOSFETs in half-bridge topology’ at enerxiv.org.

References:
[1] Automotive-grade dual N-channel, 40 V, 7.0 mΩ typ., 40 A, STripFET™ F7 Power MOSFET in a PowerFLAT™ 5x6 double island package. [online]. Available: https://www.st.com/resource/en/datasheet/stl64dn4f7ag.pdf
[2] STMicroelectronics, AN5355: Mitigation technique of the SiC MOSFET gate voltage glitches with Miller clamp, Rev 1, 2019.

Green Chemistry – A Potent Approach towards Organic Synthesis

Kailas Arjun Chavan, Supriya, Ghanshyam Mali, Amar Nath Singh Chauhan, and Rohan D. Erande

Green chemistry is an astonishing branch of chemistry which avoids the inception of hazardous byproducts. "Design of chemical products and processes to eradicate the usage and creation of hazardous compounds" is how Green Chemistry is described. This description and the concept of Green Chemistry were initially proposed over 30 years ago, in the early 1990s. The notion of design is the most significant part of Green Chemistry. Design is an expression of human intention that how can they design something which is completely eco-friendly, and not serendipitous that entails originality, forethought, and methodical approach. Green chemistry is fundamentally based on its twelve principles and there are "design guidelines" that chemists may use to assist themselves to attain the deliberate objective of sustainability. Green Chemistry is distinguished by meticulous planning of organic synthesis and molecular design in order to minimise negative repercussions which aims to maximizing the productivity with minimal wastage. Hence, the Green Chemistry method seeks to promote molecular sustainability which is hardly unexpected that this aim has been applied to almost all industry areas. There are uncountable instances of successful implementations of award-winning, economically competitive technologies in industries ranging from aerospace to automobiles, cosmetics to electronics, energy sector to regular household items, pharmaceuticals, and agriculture. Green Chemistry has shown how scientists may build next-generation goods and processes that are lucrative while also being beneficial to human health and the environment. The twelve principles of Green Chemistry “PRODUCTIVELY” serve as a foundation for the development of safer compounds and chemical transformations which was recently coined as a simpler and more memorable term for them

Green chemistry is an astonishing branch of chemistry which avoids the inception of hazardous byproducts. "Design of chemical products and processes to eradicate the usage and creation of hazardous compounds" is how Green Chemistry is described. This description and the concept of Green Chemistry were initially proposed over 30 years ago, in the early 1990s. The notion of design is the most significant part of Green Chemistry. Design is an expression of human intention that how can they design something which is completely eco-friendly, and not serendipitous that entails originality, forethought, and methodical approach. Green chemistry is fundamentally based on its twelve principles and there are "design guidelines" that chemists may use to assist themselves to attain the deliberate objective of sustainability. Green Chemistry is distinguished by meticulous planning of organic synthesis and molecular design in order to minimise negative repercussions which aims to maximizing the productivity with minimal wastage. Hence, the Green Chemistry method seeks to promote molecular sustainability which is hardly unexpected that this aim has been applied to almost all industry areas. There are uncountable instances of successful implementations of award-winning, economically competitive technologies in industries ranging from aerospace to automobiles, cosmetics to electronics, energy sector to regular household items, pharmaceuticals, and agriculture. Green Chemistry has shown how scientists may build next-generation goods and processes that are lucrative while also being beneficial to human health and the environment. The twelve principles of Green Chemistry “PRODUCTIVELY” serve as a foundation for the development of safer compounds and chemical transformations which was recently coined as a simpler and more memorable term for them.

By the end of 20th century, the world has faced many natural calamities which are a counter reaction of nature’s exploitation. In order to avoid that, nowadays scientists are focusing on greener pathways to find alternatives for toxic chemicals and efficient substitutes for time consuming substrate-based reactions. The optimization and implementation of green chemistry may be heckling but their results can be fascinating. Every researcher from the scientific community can contribute to the green chemistry protocol by taking responsibilities on an individual level. Proper disposal of chemicals using bifurcated containers, believing in the thought of “less is more”, utilization of safer cum pocket friendly chemicals and aiming at higher atom economy rates are the foundation stones of this revolution in the scientific world. Solvent less reactions like solid state synthesis are in trend these days because such reactions don’t require addition of toxic solvents, and are free from workup processes and yield the targeted product with good conversion rate. On the other hand, another green chemistry method is sonochemistry, in that ultrasonic radiation is used to complete the chemical reaction. The important advantages of sono-chemistry are the initiation of high temp and high pressure in very petite period due to cavitation phenomenon. Also, one can go with microwave assisted organic synthesis (MAOS) as an alternative green method where collision or induction of chemical and electromagnetic radiation stands principally. Moving towards another application of green chemistry i.e., photochemistry, where all type of pericyclic reactions are included because of transfer of orbital energy under UV or IR radiation [2].

In line, we have developed several green methods towards synthesis of medicinally active natural products and drugs like molecule in terms of finding better drug candidate. In our present work, For the first time, synthesis of substituted dihydropyrano [2,3-c]pyrazoles utilizing water as solvent, and using multicomponent reaction (MCR) catalysed by taurine has been achieved. We have developed new organic scaffolds connected with iso-nicotinamide, spiro-indole, and indole moieties.[3] Another green chemistry work from our lab on effective synthesis and biological evaluation of natural and designed bis(indolyl)methanes via taurine-catalyzed green approach has been published lately. So far, we have been able to synthesize eco-friendly, cost effective and efficient BIMs and its derivatives in aqueous medium and that derivative binds directly with antineoplastic drug.[4] Indeed, the future of organic synthesis relies heavily on green chemistry because it ensures specification oriented quick synthesis of complex organic frameworks using non-noxious substrates without any solvents in abundant yields. It ensures purity and reduces human effort for scrutinizing side products. The amalgamation of being environment friendly, cost effective and result oriented makes green chemistry a wonderful boon for scientists to look forward to in near future the.

References:
K. Nicolaou, “The emergence of the structure of the molecule and the art of its synthesis,” Angew. Chem. Int. Ed., vol. 52, no. 1, pp. 131–146, 2013.
[2] S. Zhi, X. Ma, and W. Zhang, “Consecutive multicomponent reactions for the synthesis of complex molecules,” Org. Biomol. Chem., vol. 17, no. 33, pp. 7632–7650, 2019.
[3] C. G. Neochoritis, T. Zarganes-Tzitzikas, K. Katsampoxaki-Hodgetts, and A. Dömling, “Multicomponent Reactions:‘Kinderleicht,’” J. Chem. Educ., vol. 97, no. 10, pp. 3739–3745, 2020.
[4] C. Cimarelli, “Multicomponent reactions,” Molecules, vol. 24, no. 13, p. 2372, 2019.
[5] K. Harada, “Asymmetric Synthesis of α-Amino-acids by the Strecker Synthesis,” Nature, vol. 200, no. 4912, pp. 1201–1201, 1963.
[6] C. Liu, W. Huang, J. Zhang, Z. Rao, Y. Gu, and F. Jérôme, “Formaldehyde in multicomponent reactions,” Green Chem., vol. 23, no. 4, pp. 1447–1465, 2021.
[7] R. O. Rocha, M. O. Rodrigues, and B. A. Neto, “Review on the Ugi multicomponent reaction mechanism and the use of fluorescent derivatives as functional chromophores,” ACS Omega, vol. 5, no. 2, pp. 972–979, 2020.
[8] G. Mali et al., “Design, Synthesis, and Biological Evaluation of Densely Substituted Dihydropyrano[2,3- c ]pyrazoles via a Taurine-Catalyzed Green Multicomponent Approach,” ACS Omega, vol. 6, no. 45, pp. 30734–30742, Nov. 2021, doi: 10.1021/acsomega.1c04773.
[9] A. C. Boukis, K. Reiter, M. Frölich, D. Hofheinz, and M. A. Meier, “Multicomponent reactions provide key molecules for secret communication,” Nat. Commun., vol. 9, no. 1, pp. 1–10, 2018.
[10] R. Afshari and A. Shaabani, “Materials functionalization with multicomponent reactions: state of the art,” ACS Comb. Sci., vol. 20, no. 9, pp. 499–528, 2018.

Multi-Electrode Sensor system for Tomography of salinity and Air-Water Flow in Industrial Conduits

Mani Rani, Tushar Kankhedia, Hardik Kothadia, Saakshi Dhanekar and Kamaljit Rangra

Two-phase flow e.g., air-water plays a vital role in industrial engineering applications such as generation of power, nuclear engineering - where the efficiency is determined by steam-water flow, chemical engineering - with multiphase flow regimes in reactors, extraction of crude oil, and transportation. The development of reliable hydrodynamic models for two immiscible fluids which are physically distinct and flow at the same time depends on the data accuracy available for the allocation of phases throughout the pipeline cross-section. Gas-liquid systems must be used to determine the volumetric gas fraction. Obtaining phase distributions in real-time with the high spatial and temporal resolution is extremely desirable. The most challenging objective is to find out the resolution which helps in recognizing the individual gas bubbles and also helps in determining the parameters such as diameter, volume, shape, etc. For this reason, the spatial resolution dimensions are in the proximity of the smallest bubble fraction present in the fluid [1]. The photographic method, which is a fairly frequent means of keeping track of the flow state by taking images through the conduit wall, is one type of such flow imaging technology, where resolution depends on the transparency of the liquid and walls of the conduit. Despite this, the algorithms for picture reformation are theoretically complex; because of the tomographic dependence on the limited data set. MRI scanners, X-ray or -ray tomographs are widely used non-invasive technologies [1]. However, for systems with fast changes in flow conditions the techniques lack appropriate time resolution and radiation power, and the cost of high-speed X-Ray tomography is likewise significant. Electrical tomography is a less expensive technology that has a high time resolution but due to soft fields, the spatial resolution is low. Wire mesh sensor has certain distinct advantages over the above-mentioned techniques e.g. higher time and spatial resolution, ease of implementation over a wide range of applications, and less expensive [2]. The spatial resolution can be further improved by optimizing the transmitter/receiver array and data acquisition hardware. Considering the multiphase flow, a multi-electrode tomograph sensor depends on the conductivity measurements that provide higher spatial and temporal resolution [2]. Wire mesh sensor is a hybrid mode solution that combines tomographic imaging with intrusive local flow parameter measurements. Wire mesh tomographs with several electrodes can be divided into two groups; depending on how electrical properties are measured. In conductivity type, WMT the current or voltage is measured at each sensitive point uniformly dispersed across the WMT's cross-section and the current or voltage is proportional to the local conductivity of the liquid. Permittivity type WMT — also known as capacitive WMT, measures the capacitance of the space seen between electrodes, which is proportionate to a fluid's permittivity, or ability to transfer electric fields.

In view of the above merits of wire mesh sensor, we are developing a high-resolution multi-electrode wire sensor system to accomplish the analyses of water salinity and comparable viewing of transient gas fraction patterns in conduits for industrial applications. As a precursor to a high-resolution sensor (16x16 nodes), a simple multi-electrode sensor formed by two primary grids with four electrodes in each has been designed as shown in Figure 1 (a). The two-grid sensor with 4x4 nodes is sufficient for water salinity measurements in a conduit with a homogeneous flow of diameter 6.4 cm and larger. A simplified schematic of the test setup is shown in Figure 1(b). The WMS electrodes consist of a copper wire mesh, with 4x4 nodes, installed on a Teflon ring with external and internal diameters of 64mm and 48mm respectively. Electrodes on the first grid act as transmitter electrodes which are provided short voltage pulses in a time sequence by a programmed Arduino UNO and an external amplifier used as a voltage follower. Local conductivity of the conduit cross-section is obtained as a 4x4 matrix, after a complete cycle of transmitter activation. The second grid electrodes function as receiver electrodes; recording the current that arrives at the electrodes. The local conductivity in the immediate vicinity of the respective crossing point between the transmitter and receiver electrodes determines each value of the salinity matrix. The result characterizes the instantaneous share of saline water at a given location inside the flow field. In order to demonstrate the effectiveness and sensitivity, a series of measurements have been performed with tap water, and RO water by taking DI water as a reference having a known amount of salinity, to establish the correlation between voltage drop and fluid conductivity at each crossing point as shown in Figure 2(a). The fitted curves of the average voltage drop with different concentrations of the salt at several points are plotted. The voltage drop across different points over the cross-section of the grid represents the salinity map across the conduit at a given location as shown in Figure 2(b). The results show that the structure provides a good map of the water salinity of liquid in a conduit over a cross-sectional area of 48mm determined by the 16 equally spaced points. A higher resolution is important for two-phase liquid flow in the operation of critical applications e.g. nuclear reactors. In order to improve the resolution for two-phase liquid flow in larger conduits, the 16x16 WMS design is at an advanced stage of testing.

References:
1. Prasser, H.M., Böttger, A. and Zschau, J., 1998. A new electrode-mesh tomograph for gas–liquid flows. Flow measurement and instrumentation, 9(2), pp.111-119.
2. Liu, W., Tan, C. and Dong, F., 2015, May. A wire-mesh sensor for air-water two-phase flow imaging. In 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings (pp. 364-369). IEEE.
3. De Salve, M., Monni, G. and Panella, B., 2012, November. Horizontal air-water flow analysis with wire mesh sensor. In Journal of Physics: Conference Series (Vol. 395, No. 1, p. 012179). IOP Publishing.
4. Pietruske, H. and Prasser, H.M., 2007. Wire-mesh sensors for high-resolving two-phase flow studies at high pressures and temperatures. Flow measurement and instrumentation, 18(2), pp.87-94.
5. Da Silva, M.J., Schleicher, E. and Hampel, U., 2007. Capacitance wire-mesh sensor for fast measurement of phase fraction distributions. Measurement Science and Technology, 18(7), p.2245.
6. Peña, H.V. and Rodriguez, O.M.H., 2015. Applications of wire-mesh sensors in multiphase flows. Flow measurement and instrumentation, 45, pp.255-273.
7. Prasser, H.M., Scholz, D. and Zippe, C., 2001. Bubble size measurement using wire-mesh sensors. Flow measurement and Instrumentation, 12(4), pp.299-312.
8. Prasser, H.M., Misawa, M. and Tiseanu, I., 2005. Comparison between wire-mesh sensor and ultrafast X- ray tomograph for an air–water flow in a vertical pipe. Flow Measurement and Instrumentation, 16(2-3), pp.73-83

The Emergence of Borophene: “Lightest Elemental Dirac Material”

Pranay Ranjan

Unraveling non-van der Waal material always leads to unique layered materials having unprecedented properties. Among the family of the non-van der Waal materials, borophene (the single atomic thick layer of boron) emerges as the only lightest elemental Dirac material and thus, has fueled the research on layered materials [1-6]. Boron, the only material in the periodic table with a complex yet unique structure called icosahedral, canent two-center-two-electron bonds as well as stable electron-deficient three-center-two-electron bonds [1-3]. Due to the presence of such peculiar bonding in the bulk, theoretical calculation predicts two planar polymorphs phases namely anisotropic β12 having parallel ridges and isotropic hexagonally bonded X3 phases respectively. β12 having parallel ridges has been conjectured to have protrusions while X3 phase is deemed to have holes for structural stability [4-5].

Contrary to X3 phase, a recent, theoretical investigation of borophene (β12 phase) reveals enhanced thermal stability compared to graphene and its cousins. In addition, the β12 phase is found to be metallic in comparison to its bulk counterpart, while X3 is semiconducting and thus is considered to be the rare phase in 2D family. Unlike graphene, silicene, and boron nitride which are isotropic in nature, β12 phase of borophene is considered to be anisotropic and with ridges is expected to have higher carrier density in one direction and enhanced mechanical stiffness [6-7]. The first experimental realization of borophene was demonstrated via atomic layer deposition by Mannix et al. and later was followed by the deposition through molecular beam epitaxy on Ag [111] substrate respectively [1,3]. It was hypothesized that lattice matching of the silver and boron atoms is the primary reason behind the formation of borophene films [3]. However, it was observed through computational results that boron is not a naturally layered material but its polymorphs such as β12 and X3 are layered and are also metastable (higher energy than its bulk) [3,5]. In this context, therefore, synthesis of free-standing borophene and exploration of its physical and chemical properties has not even been thought of until we demonstrated the synthesis through blended sonochemical and micromechanical exfoliation for the first time and overcame the hypothesis of substrate-mediated growth (see Fig. 1) [8-9]. In addition, a few of the properties and application of the free-standing borophene is explored by us. However, the material is destined to open new opportunities for the next generation of devices (see Fig. 2).

Figure 1. a) Schematic diagram depicting typical sonochemical exfoliation, b) Transmission Electron Microscopy, and c) High Resolution TEM images (inset contains electron diffraction pattern), d,e) Atomic Force Microscopy images and height profiles of the borophene seheets, f) Raman spectrum, g) XPS spectrum (survey) for borophene, and h) short scan XPS B 1s. Scotch tape exfoliation of free standing borophene i) Image of the borophene crystal, j) Optical image of the crystal, k) Raman spectrum, l) Camera images of the exfoliation process, m,n) Optical image of the transferred B onto SiO2/Si substrate, o,p) XPS/Long range scan of the B 1s spectra, q-t) FESEM images of exfoliated borophene.[8-9]

Figure 2. Pictorial representation of the upcoming applications of Borophene in different spectroscopic ranges.[10]

References:
A. J. Mannix et al., Synthesis of Borophenes: Anisotropic, Two-Dimensional Boron Polymorphs, Science, 350, 1513, 2015.
A. J. Mannix et al., Synthesis of Borophenes: Anisotropic, Two-Dimensional Boron Polymorphs, Science, 350, 1513, 2015.
B. Feng et al., Experimental realization of two-dimensional boron sheets. Nat. Chem. 8, 563–568, 2016.
B. Feng et al., Discovery of 2D Anisotropic Dirac Cones. Adv. Mater. 30, 2–7, 2018.
X. Sun et al., Two-Dimensional Boron Crystals: Structural Stability, Tunable Properties, Fabrications and Applications. Adv. Funct. Mater. 27, 2017.
C. Lee et al. Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene, Science, 321, 385–388, 2008.
V. Nicolosi et al., Liquid exfoliation of layered materials, Science, 340, 72–75, 2013.
P. Ranjan et al., Freestanding Borophene and its hybrid. Advanced Materials, 31 (27), 1970196, 2019.
S. Chahal et al., Borophene via Micromechanical Exfoliation, Advanced Materials, 33 (34), 2102039, 2021.
P. Ranjan et al., Borophene: New sensation in flatland, Advanced Materials, 32 (34), 2000531, 2020.

Measuring Magnetism with Transmission Electron Microscopy

Devendra Singh Negi

The functional nature of the electronic property of a material is a prerequisite of the modern electronic devices. However, the electronic functionality of a material is governed by its electronic structure at atomic scale. Therefore, the capability of understanding and engineering materials at atomic dimension offers potential possibilities to design the desirable functional electronic properties in materials. In order to tailor the material at atomic dimensions, we inevitably require the capability to visualize and quantify the electronic properties at nano and atomic scale. In this context, the transmission electron microscopy (TEM) is an indispensable instrument for studying and analyzing the materials at atomic scale. The TEM has upsurged the advancement in diverse scientific domains, e.g., material science, chemical science, biological science, geological science etc. The TEM offers multiple characterization techniques on a single platform. These techniques qualitatively and quantitatively characterize materials from micro-meter to the length scale of atomic-dimensions, which further accelerate the material design and synthesis strategy for newer material discovery. Traditionally the TEM is considered an instrument, which is used for visualizing the high magnified images of the materials. However, after the development of the aberration correction in the TEM optics, there has been multifold developments in the TEM related techniques. This advancement has enabled the TEM to surpass the sub-atomic scale and the spectroscopic techniques in TEM are capable of detecting the signal of a single atom. These newly developed aberration corrector has enabled the TEM as an instrument which can perform a structural, chemical, magnetic, electric, biological, spectroscopic characterization with atomic scale sensitivity on a single platform. These technical advancements have certainly pushed the capability of TEM beyond imaging. In the latest advancement the TEM is finding its path to quantitatively measure the electric and magnetic field with atomic resolution. The rapid development in the electronic miniaturization is certainly demanding such techniques for designing and developing the futuristic materials. The nano and atomic scale sensitive magnetic measurement accompanied with imaging and spectroscopic capabilities in TEM offers unique capabilities for material investigation

Electron magnetic circular dichroism (EMCD) is a newly developed technique in TEM, which allows to quantitatively measure the magnetic properties of a magnetic material at atomic dimensions. The EMCD technique in TEM was developed by taking the inspiration from the X-ray magnetic circular dichroism (XMCD). The XMCD technique uses the X-ray beam in the larg e synchrotron facility to measure the magnetic dichroism in the magnetic materials. However, the EMCD can also similarly measure magnetic properties in the TEM facility. Furthermore, the TEM offers additional high spatial resolution imaging, spectroscopy, diffraction and other measurements simultaneously. Therefore, the EMCD is strongly considered as a substitution of XMCD techniques. The EMCD technique uses the inelastic electron diffraction pattern in the electron energy-loss spectroscopy mode. In a common method of EMCD, the magnetic crystal is rotated in the 2-beam [1], 3-beam geometry to acquire the energy-loss electron which contains the magnetic information of the material (Figure1). The EMCD method utilizes the sum rule for calculating the spin and orbital magnetic moment of the magnetic atom [2]. The EMCD has demonstrated the capability to measure the magnetic signal at atomic length scale [3]. Moreover, recently with the EMCD method a single atom magnetic moment detection is also shown to be feasible [4]. The three-dimensional reconstruction of magnetic structure is also envisioned with the EMCD method [5]. In the direction of the technique development, various methods are being developed which can impart the magnetic information from the EMCD much more easily (Figure 2-4). With the successful implementation of newer methods and instrumentation the EMCD method holds promising potential for the futuristic material characterization.

Figure 1. The experimental 2-beam geometry of EMCD. The EMCD signal is acquired by subtraction the energy-loss signal acquired on the detector positioned at 1 and 2 circle n, as shown in the figure 1.

Figure (2,3,4) The atomic resolution capability of EMCD. (2) Aperture method for enhancing the EMCD signal. (3) The vortex sectioning method in EMCD. (4) The capability of EMCD to detect single magnetic Co atom doped in GaAs crystal.

References:
P. Schattschneider et.al, Nature 441, 486 (2006).
2- J. Rusz et.al, Nat. Commun. 7, 12672 (2016).
3- D. Negi, et.al, Physical Review Lett ers, 122, 037201 (2019).
4- D. Negi, et.al, Physical Review B, 100, 104434 (2019).
5- D. Negi et.al, Physical Review B, 98, 174409 (2018).

Structural Battery

A. Andrews Cyril, Ankit Dev Singh and Srijan Sengupta

In the era of energy crisis and global warming, the automobile industry faces the challenge of decarbonization to mitigate the climate change problem. Electric vehicles have potential to change almost all aspects of transformation including carbon emission, fuels, driving habit and cost. Many countries including Norway, Germany, Netherland, France and Great Britain is planning to replace the gasoline or diesel cars with electric vehicles. EVs are the main focus for automobile industry currently and designing new lightweight vehicles for the commercial use is the need of hour as per the demand of EV market. Nowadays, the main problem faced by the EVs are their range of distance covered per charge and charging time. To improve the overall performance of EVs, development in the battery and power performance of an EV is a must.

EVs mostly have a heavy battery pack (almost 30 % of the entire vehicle) which also incurs 40 % of the cost. The behind this weight is because of the reason that the state-of-the-art Li-ion batteries are almost 17 time less efficient than the gasoline energy. Therefore 17 time more battery weight is necessary to achieve the same performance that of a petrol run car. For example, for cars such as alto, the tank carries 35 Lt. or almost 27.3 Kgs of petrol. Therefore, the amount of battery needed is around 464 Kg which is almost 60 % of the rest of the car weight and 37 % of the total weight (car + battery). This huge weight not only reduces milage but also plays a made the mechanical design complex.

Now, for a gasoline run car, if we break up the weight of different components it is found that the body has 36 % of the total weight and the interior carries roughly 12 % of the total weight remaining shared by the chassis and power transmission. Now, in a car, the chassis carry most of the loads and not the body nor the interior. Therefore, if by some means this (36 + 12) = 48 % of the body + interior weight can be built by a solid-state battery, it would serve the purpose (sufficient to run the car). The solid-state battery material must also be able to withstand the load experienced by the car body and that is how the name structural battery has come to the picture.

These solid-state Li-ion batteries can pack more energy owing to their solid electrolytes and use of Li metal as anode. The solid electrolyte is non-flammable unlike the liquid electrolyte used in commercial Li-ion batteries, and therefore, a lot safer to deal with. Further, rise in temperature (sworn enemy of liquid electrolyte Li-ion batteries) assist diffusion and the solid-state battery functions better without degradation.

The only catch is this solid-state Li-ion batteries are not suitable to carry load as Li is malleable metal. Therefore, batteries based on Li may not be suitable for structural batteries. This is where aluminium (Al) comes into picture. Al is the most abundant metal on Earth (including India) and are used in constructions in large volume. Al is also used as a negative electrode in Al-ion batteries which is the upcoming dominating chemistry threatening to replace Li chemistry.

Our group is already working on an Al-Fe/Ni based intermetallic battery based on molten salt chemistry for grid storage. We aim to extent our research to build the same Al-Fe/Ni battery with a solid electrolyte such that an Al-Fe based solid state battery can be built. Since both Al and Fe are structural materials, the solid-state battery made of Al & Fe must also be able to carry load sufficient for that of a car body and interior. EVs made of these batteries will be safer and shall match the performance (power, range, charging time) of a modern gasoline car.

Bibliography

1. M. Satyendra Kumara and Shripad T. Revankar. (2017), ‘Development scheme and key technology of an electric vehicle: an overview’, Renewable and Sustainable Energy Reviews Vol. 70, pp. 1266-1285
2. Huiyuan Xiong et al. (2019) ‘Numerical calculation model performance analysis for aluminum alloy mortise-and-tenon structural joints used in electric vehicles’, Composites Part B: Engineering Vol. 161, pp. 77-86
3. Cheng Lin et al. (2016) ‘Multi-objective optimization design for a battery pack of electric vehicle with surrogate models’, Journal of Vibro engineering, Vol. 18, Issue 4, pp. 2343-2358.
4. Yong Tang et al. (2011) ‘Experimental investigation on the dynamic performance of a hybrid PEM fuel cell/battery system for lightweight electric vehicle application’, Applied Energy Vol. 88, Issue 1, pp. 68-76.
5. Xin Chen et al. (2022) ‘Electric vehicles body frame structure design method: An approach to design electric vehicle body structure based on battery arrangement’, J Automobile Engineering Vol. 236(9), pp. 2025–2042.
6. Dainis Berjoza, Inara Jurgena (2017) ‘Influence of batteries weight on electric automobile performance’, 16th International Scientific Conference Engineering for Rural Development, LATVIA Jelgava, 24.-26.05.2017.
7. B. Clement et al., (2022) ‘Recent Advances in Printed Thin-Film Batteries’, Engineering, ISSN 2095-8099.
8. Shijian Wang et al., (2020) ‘Recent progress on flexible lithium metal batteries: Composite lithium metal anodes and solid-state electrolytes’, Energy Storage Materials 29, pp. 310–331.

AI-driven Sustainability Assessment - what, why and how

Lipika Dey

Sustainability assessment can be defined as the process of identifying, measuring, and evaluating the potential impacts of alternatives in the context of enterprise decision making and policy planning to ensure sustainable development. Sustainability practices aim towards the benefits of society as a whole. In 2015, the United Nations proposed 17 sustainable goals (SDGs) to achieve this. These goals provide general directions for policy planning and responsible actions to address issues such as eradication of poverty, hunger and inequalities, ensure gender equality, provide facilities like health education, clean water and sanitization to all, focus on clean energy, encourage responsible consumption and production, reverse climate change, protect land and water resources, ensure justice for all and also towards building sustainable cities, communities, institutions and partnerships. While the goals broadly cover all aspects of environment, society and corporate governance, progress in each of these areas are made easier to track through the introduction of 169 targets that are measurable and are expected to be achieved by all organisations by 2030. Sustainable decision making focuses on actions that can help an organisation achieve these targets.

An organization is measured by assessing its performance along all the three dimensions of sustainability - environment (E), society (S) and governance (G), collectively referred to as ESG. Though standards are still emerging, each area has a set of key performance indicators which are tracked to evaluate sustainability progress and design policies for further improvement in future. Conscious investors today demand visibility into a company’s sustainability practices. Many companies are therefore publishing an annual sustainability report in which they provide a detailed assessment of risks perceived and sustainability measures undertaken. It has been found that ignoring sustainability can cause upto 6% decline in a company’s revenue, as negative perceptions can be amplified through social media influencers, even before a company can react to it.

Sustainability Metrics - Tracking to assess

Sustainability assessment is a complex task. Organizations like Global Reporting Initiative (GRI) and Sustainability Accounting Standard Board (SASB) suggest tracking various data points for the purpose. In this section we present some key sustainability metrics that are monitored for assessing the ESG impact of a company.

Environmental sustainability metrics can be put under five broad areas as mentioned below :

Climate risk - Under this metric, an organisation assesses their exposure to climate-related risks due to the changing environment and physical risks of climate change. Oft-reported perceived risks are regulatory transition risks and physical risks from climate change that could negatively impact productivity and success. Forward-looking scenario based analysis help companies develop effective risk mitigation strategies across corporate asset locations, supply chains, and product life cycles.

Carbon emissions - As per the Paris Agreement adopted in 2015, nearly all countries have agreed to reduce global greenhouse gas emissions in an effort to limit the global temperature increase to 2° Celsius above pre-industrial levels by 2050. Consequently, companies are actively migrating from using fossil fuels like coal to renewable and cleaner energy sources like natural gas, wind, water, solar energy.

Energy consumption - There is also an overall effort to reduce energy consumption altogether in order to reduce greenhouse gas emissions as well as emission of other compounds that are detrimental to the environment.

Water Usage - Water is a critical and primary metric, whose use and wastage need to be monitored and restricted within organisational premises. Reducing water wastage, leakage etc. are also part of this agenda. Industries also have to be particularly conscious about protecting water from being polluted due to their site activities like mining, construction, chemical usage etc. Water pollution is measured by the “total natural capital cost of the environmental impacts from heavy-metal and pesticide pollution or from excess fertilizer use causing algal blooms.”

Waste & pollution - Waste management is a broad category that includes monitoring food waste, agricultural and animal waste, medical waste, radioactive waste, hazardous waste, industrial non-hazardous waste, construction and demolition debris, extraction and mining waste, oil and gas production waste, fossil fuel combustion waste, and more. This

The above metrics provide broad guidelines to the companies about elements to focus on and also what to track and monitor. Data collection from different sources is an important activity. The data, measured against the company’s goals, is the space where ESG operates. Deployment of IoT (Internet of Things) powered sensor-based platforms help in measuring and tracking many of the above-mentioned parameters. Analytical frameworks sitting on top of these platforms provide the necessary tools to collate, analyze, report and also perform predictive analytics and what-if reasoning with the data to assess and select the right alternatives for a better future.

Tracking social sustainability is somewhat more complex since these goals can be a mixture of subjective and objective. Three key metrics tracked are gender pay equity, diversity and inclusion and wage levels. These are centred around ensuring a free and fair workplace which focuses on equality of all and follows labour laws.

The fourth metric measures risks resulting from incidents involving child and forced labour. This is an important source of risk for all companies who outsource work to third party vendors, as compliance to sustainability demands that all stakeholders that a company deals with are also sustainable.

The fifth metric attempts to ensure health and safety that covers health risks perceived for all stakeholders. Ensuring safe workplaces and monitoring occupational health hazards of employees has been an area of focus for quite a few years now. This metric also assesses safety risks and vulnerabilities of society at large, who may become a part of the company’s ecosystem by virtue of their geographical location. Thus all activities that may be polluting air or water or affecting biodiversity etc. have to be accounted for.

Another important social metric is the effort put towards training employees both in terms of training hours and money spent behind it. This measures the company’s commitment to prevention of on-the-job accidents while dealing with complex machinery, equipment maintenance, adherence to safety measures in construction or mining sites and so on.

An organisation’s commitment towards innovation is also assessed as a part of its social commitment. A culture of innovation provides employees the freedom to experiment. Some organisations measure it by the percentage of time employees are encouraged to spend on tasks that may fall outside their scope of work. This is tracked through the number of patents filed or publications generated as also the incentives provided for such activities.

Finally, since one of the key targets of the sustainability program is to ensure a better world for all, it is very important to track all activities that are directed towards “Giving back to the community”. Awareness programs, fitness initiatives, greening activities and many other programmes are conducted by organisations to ensure the society at large benefits from their work. An important aspect is to come up with methods to measure the success of these programmes.

The third pillar of sustainability is to ensure transparency, fairness, integrity and honesty in its governing structure. Ensuring diversity and inclusion of all communities in all boards and committees, holding stakeholder meetings regularly, having financial fraud-control mechanisms in place, implementing processes to ensure compliance to regulatory standards are some of the metrics that are tracked under this category.

Not all the metrics mentioned above are actually quantifiable for assessment purposes. Many of them are intangible in nature. It is also obvious that the metrics are not totally isolated from each other, and each action plan should be formulated to ideally contribute to as many metrics as it can.

Responding to the growing demands from investors and customers, organisations publish different kinds of reports in which their targets, actions, activities, achievements and plans around the key metrics are disclosed. These disclosures being free-format, it is difficult to come up with objective assessments. There is no specific format or unit for reporting different items under a metric. Regulators across the globe are waking up to this requirement. The UK is the first country to mandate climate-related disclosures by 2025. The EU has also proposed its Corporate Sustainability Directive (CSRD). The US is also planning to come up with a framework for disclosure of ESG information soon. However, given the nature of the items, it is unlikely that sustainability assessment can be totally objective. A lot of subjective issues are likely to remain along with some vagueness and uncertainties inherent to the domain. Meaningful sustainability assessment has to be predictive in nature, which can predict the collective impact of an array of actions undertaken. It is precisely here that AI-based methods step in.

AI and Sustainability Assessment

If sustainability assessment begins with data acquisition, it starts making an impact only when the data is made use of. Some AI applications that have already made their presence felt are in the areas of energy use and storage optimization, balancing electric supply and demands in real time, managing microgrids for renewable energy and so on. Predictive maintenance of equipment based on sensor data not only increases the life-spans, but also goes a long way towards ensuring safe workplaces. Early warning systems based on failure prediction models also play a crucial role in avoiding mishaps. As the vision-based technologies mature, video monitoring solutions complete with automated detection of anomalous events and event-based alarm generation systems are being deployed in factories and assembly lines to avoid accidents. Pollution monitoring solutions for air and water are also gaining markets.

Working with climate-risk data turns out to be trickier. While the data shared by individual organisations are important, impact assessment in this case requires aggregate analysis. Experts are of the opinion that the expected outcomes assessed from the collective data reported do not match the reality. None of the climate risks have shown any signs of reversal.

Analysts are working on complex causal models to disentangle the complex causal relationships between the known causal factors like industry emissions, greenhouse gases or vehicular pollutants etc. and the observed variables like rising temperatures and sea-water levels, occurrence of natural disasters and so on. Without these causal models it is difficult to assess the short and long term impacts of the mitigation steps. Counterfactual reasoning is another important tool in this repertoire that is used by analysts to simulate non-existing situations in order to assess impacts of interventions and preemptive steps.

Going beyond the measurables, sustainability assessment also requires churning a lot of unstructured data that includes textual descriptions of events, actions, plans and policies available in reports and disclosures. Social media interactions with the outside world, consumer reactions to an organization’s stand, internal and external communications all provide valuable inputs for assessment purposes. Traditionally, third party assessors collected data from companies in the form of a survey to come up with a single numerical score. The scoring process was highly non-transparent and rigid. With increasing availability of public disclosures, it is now possible to employ Natural Language Processing techniques to extract relevant information from the reports, and use it within customized analytics platforms to obtain sector-specific or application-specific scores. Given the complex format of the reports, this poses many challenges to the natural language processing community. Challenges include automated classification and location of relevant information within reports, extracting the right unit of data using information extraction principles and then using them for analytics. Not all data reside in text boxes. Multimodal analysis of content to process and combine information from text, tables, graphs and images is another complex task.

The transformer-based language models provide strong foundations for building such applications, as they can encode the context of information very well. Trained on large volumes of sustainability-related open data like News articles, these models are capable of analyzing and extracting all relevant information from large reports in minutes. Building sector-specific and customized analytical models is now easy. Stakeholders can specify their own preferences and obtain performance report for the preferred area only. This has helped in democratization of sustainability analytics and assessment and is particularly important for scope-3 assessments, in which every organization needs to assess all partners. While an automobile manufacturing organization may have to focus on workplace safety aspects for its parts manufacturers, this is not likely to be the crucial aspect while selecting its financial service providers. Ability to drill down a score and have access to the underlying data that has led to the score is also leading to an increasing demand for in-house analytical platforms powered by natural language processing.

Qualitative aspects like expert comments and opinions on organisation actions as well as policies and regulations influence sustainability assessment in a big way. Debates, arguments, opinions and stances abound in this area, leading to a virtual sea of information that need to be carefully assessed before taking a decision. Transformer based language models are proving to be extremely powerful in encoding contextual semantics. An array of language applications have been built using these models that can perform diverse tasks like detecting topics, alignments, contradictions, sentiments, opinions, moods and stance from large collections of text. These technologies are being explored to provide augmented intelligence platforms with exploratory analysis capabilities to decision-makers who can obtain multi-perspective views of the underlying content before taking decisions. TCS ESG integration solution ((https://www.tcs.com/sustainable-finance-esg-integration-solution) is one such application intended to provide a 360 degree ESG view based on public disclosures and open media content gathered about companies. Figure 1 presents a screenshot from the system.

The use of technology in sustainability analytics today is largely restricted to monitoring and optimization of energy usage data. There is a huge unexplored possibility of using AI based analytics and reasoning to build impactful decision-making systems. AI also has an important role in detecting and exposing “greenwashing”. Greenwashing refers to the unethical process of conveying false impressions or providing misleading information about how sustainable or environment friendly a product, process or service is, even as reality speaks otherwise. Exposing greenwashing requires multi-source, multimodal feasibility analysis of complex data taking into account the attributes of the product or service, the purpose, the technology underneath and the claims. This article is intended to show the tip of the iceberg, with the hope that researchers of the future would feel excited enough to plunge into the ocean out there to ensure a greener earth before it’s too late.

References

Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104.

Smeuninx, N., De Clerck, B., & Aerts, W. (2020). Measuring the readability of sustainability reports: A corpus-based analysis through standard formulae and NLP. International Journal of Business Communication, 57(1), 52-85.

Ballestar, María Teresa, Miguel Cuerdo-Mir, and María Teresa Freire-Rubio. "The concept of sustainability on social media: A social listening approach." Sustainability 12, no. 5 (2020): 2122.