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Simultaneous enhancement of build rate and microstructure in SS316L additive ma…

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Thu, 27/03/2025 - 12:00

Magnetic Field Regulates Blood Flow in Partially Blocked Arteries

pro — Tue, 18 Mar 2025 11:05:39 +0000

Magnetic Field Regulates Blood Flow in Partially Blocked Arteries pro Tue, 18/03/2025 - 16:35

Magnetic Field Regulates Blood Flow in Partially Blocked Arteries
A theoretical study demonstrates magnetic force lowers blood pressure fluctuations and stabilises flow, setting the stage for advanced cardiovascular therapies.

This image has been adapted to suit the story's needs under the Creative Commons Attribution-Share Alike 4.0 International license. Credits to the original image: http://www.scientificanimations.com, via Wikimedia Commons

An alarming report by WHO states that ischemic heart disease was the leading cause of death in the year 2021 among Indians, next to COVID-19. Restriction of blood flow in coronary arteries causes ischemic heart disease. Cholesterol, lipoprotein and calcium accumulate in the arteries forming plaque, narrowing the arteries and restricting blood flow. Blood pressure increases, leading to cardiovascular diseases such as hypertension and heart attacks. Regulating blood flow and pressure in the blocked arteries can help avoid lethal consequences.

A recent study by researchers from the Rummy Game (Online Rummy) showed that magnetic fields can effectively manipulate blood flow, making blood flow faster or slower depending on field direction. The finding opens up possibilities for using magnets in heart disease treatments and provides insights for creating advanced drug delivery systems.

The researchers used a computation framework to simulate and analyse the blood flow pattern. They consider factors such as flow speed (velocity), pressure, and frictional force within the artery walls (wall shear stress). “Wall shear stress (WSS) is the force per unit area exerted by the blood flow along the inner walls of blood vessels. It is a critical factor in vascular health, as abnormal WSS can contribute to the development of diseases like atherosclerosis. WSS is
influenced by the blood's velocity and viscosity along the vessel walls”, says Prof. Abhijeet Kumar, who led the study at the Department of Mechanical Engineering, Online Rummy.

The researchers devised a numerical model of a blocked artery and studied the influence of magnetic fields in the narrowed arteries using mathematical equations. The magnetic field interacts with iron-rich haemoglobin in the blood and impacts the blood flow depending on the direction of the magnetic field. The researchers calculated the motion of blood (using Navier-Stokes equations), analysed electromagnetic fields (using Maxwell’s equation) and monitored blood thickness or viscosity and flow (using the Carreau-Yasuda Model).

The researchers modelled different stages of narrowed arteries- mild-25 % blocked, moderate-35% blocked, and severe-50 % blocked with varied shapes. The arteries are either evenly narrowed (axisymmetric), off-centric (eccentric), asymmetric, or sharp-edged. Axisymmetric and sharp-edged blockages caused the most severe pressure fluctuation and obstructed smooth blood flow. When the researchers applied the magnetic field parallel to the blood flow, they observed an increased blood flow speed. When they used the magnetic field perpendicular to the blood flow, there was a decrease in the flow speed.

Computational simulations showed that the magnetic field increased the blood flow by about 17%, 30% and 60% in mild, moderate, and severely blocked arteries. Stronger magnetic fields facilitated smoother blood flow. Magnetic field orientation that aligns with the blood flow reduces the pressure near the blockage in the severely stenotic (abnormally constricted) artery. Pressure fluctuations create more shear stress on the plaques (accumulated mass that causes the block), increasing the risk of rupture. The study found that magnetic force stabilises flow and pressure fluctuations in all the stenosis shapes, reducing the risk of plaque rupture.

The findings of the study would help treat patients with hypertension. The results show that the magnetic field influences blood flow, pressure, and wall shear stress. This can further help control high blood pressure and prevent damage to arterial walls. The study underlines the importance of magnets in cardiovascular therapies and enhanced patient care. It also highlights possible developments in innovative drug delivery systems using magnets.

“High and ultrahigh magnetic fields have shown both positive and adverse effects in experimental models, suggesting that safety evaluations are crucial before clinical application… Given the complexities and challenges mentioned, including the need for extensive research, clinical trials, and regulatory approvals, it might take several years before such treatments become widely available,” reminds Prof. Kumar.

The researchers recommend further study, including more realistic models to understand the flexibility and shear stress of a real arterial wall. “The challenges in transforming this research into practical treatments include the complex interactions between magnetic fields and biological tissues, which can impact cellular structures, blood viscosity, and vessel walls. There is a need for careful evaluation to ensure safety and efficacy,” signs off Prof. Kumar.

Article written by:	Divyapriya Chandrasekaran
Image/ Graphic credit:	This image has been adapted to suit the story's needs under the Creative Commons Attribution-Share Alike 4.0 International license. Credits to the original image: http://www.scientificanimations.com, via Wikimedia Commons
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Modelling of coronary artery stenosis and study of hemodynamic under the influe…

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Tue, 18/03/2025 - 12:00

How Researchers Are Optimising Indian Railways—Without Touching Train or Track

pro — Mon, 17 Mar 2025 12:34:47 +0000

How Researchers Are Optimising Indian Railways—Without Touching Train or Track pro Mon, 17/03/2025 - 18:04

How Researchers Are Optimising Indian Railways—Without Touching Train or Track

Here’s how Online Rummy and Indian Railway researchers are making Indian railways more efficient by grouping non-daily trains together for the timetabling process.

Pixabay: Indian Railway

Despite the dizzying complexity of all its components, your body is still extraordinarily efficient at what it does. But what if it wasn’t? What if your brain had to manually and non-intuitively chart tedious plans to coordinate what blood flows through which arteries at what time?

Termed by some as the arteries of our economic system, India boasts the fourth largest railway network worldwide, a technological marvel whose function propels a flurry of crucial socioeconomic development across the country’s various corridors. But how do you upgrade anything without painstakingly replacing hardware that has stood firmly on the nation’s soil for over 160 years? According to a team of collaborators from Zonal Railways, the Centre for Railway Information Systems (CRIS), and the Rummy Game (Online Rummy), you don’t have to — you just need to look at things with fresh eyes.

To understand this new research involving Prof Madhu Belur from the Department of Electrical Engineering, Prof Narayan Rangaraj from the Department of Industrial Engineering and Operations Research at Online Rummy, and experts from Zonal Railways and CRIS, let’s first look at how trains are timetabled.

In this study, the team grouped Indian trains into two broad categories: daily trains — trains that run on all days of the week — and non-daily trains that run a few times per week. For example, most long-standing trains between popular destinations run daily. In contrast, some trains to very specific destinations run only on specific days of the week — this is quite common when new trains are introduced between pairs of cities where traffic is building up over time. While daily trains have it mostly sorted out, the non-daily ones are a tougher challenge within the Indian railway timetable.

The main issue is that these non-daily trains are scattered throughout the week, making it hard to plan efficient schedules. Another challenge is that different railway zones initially plan their local schedules considering their own sectional resources, and this may result in these non-daily trains having conflicts at other busy sections or sub-optimal use of bottleneck resources on the larger network. To address this, the team of collaborators explored a process called ‘dailyzing,’ which involves clustering non-daily trains to improve scheduling efficiency.

At its core, dailyzing is about grouping “similar” non-daily trains into a single, predictable pattern, almost as if they were a daily service. Similar trains that use almost the same resources and at almost the same times (within a window of 15 min) but on different days of the week are grouped in a cluster. Instead of treating these sporadic trains as independent, railway planners can now map them onto a 24-hour schedule, creating a structured timetable that fills gaps and reduces inefficiencies.

The team used Hierarchical Agglomerative Clustering (HAC) — a technique that identifies patterns in vast amounts of data — to sort trains that run on similar routes at similar times but on different days. These trains are then scheduled as a single "cluster", ensuring a more compact and efficient timetable. The team found that scheduling one representative train from the group as a ‘daily train’ can help to schedule non-daily trains in that group.

Right now, the Indian Railways operates over 13,150 passenger trains daily across the country, yet many of its non-daily services run inconsistently across the week. This scattered scheduling leads to underutilised tracks on some days and congested bottlenecks on others. By clustering trains, the researchers found they could speed up the timetabling process because once a cluster is scheduled, every train within it automatically follows suit.

Think of it like scheduling a bus for a busy city junction. If five different buses pass through the same junction at the same time of the day but on different days of the week, it would be rather tiresome and inefficient to schedule it as such. But when you cluster all the buses into one “daily” path, you just have to plan for one bus, which will automatically set the times for all the buses in that group.

Further, this method could even make space for new trains. If a cluster has fewer than seven trains (one train for each day of the week), additional services can be slotted in the free days, the research explained. Bottleneck sections could now be managed more effectively, reducing delays and maximising train flow.

To put their model to the test, the researchers focused on India's Golden Quadrilateral and Diagonals (GQD) network — a vast rail system connecting Delhi, Mumbai, Chennai, and Kolkata. They analysed real-world train data and applied popular clustering techniques such as Hierarchical Agglomerative Clustering (HAC), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means. The results were striking, showing that HAC produced the best clusters, ensuring that non-daily trains mostly “complemented” each other, rarely causing conflicts. In this context, a cluster satisfies the complementing conditions once all its trains run on the same stretches and at the same time of the day but on different days of the week.

HAC produced conflict-free clusters within seconds, while some other techniques often took several minutes. This speedy method using HAC also helped reveal hidden inefficiencies, pointing out where new trains could be introduced without disrupting the system.

Prof Madhu Belur explained that the model was based on and built for the GQD network for two reasons: the GQD comprises a significant and major portion of the total freight and coaching traffic for the Indian Railways. Secondly, timetables for non-GQD and less frequented railway zones are carried out in a much more zonal fashion, which already simplifies things enough since the lighter volume of trains in these areas makes it easier to timetable their schedules.
Interestingly, Prof Belur noted that Indian Railways, with the team’s support in creating an automated tool based on clustering, has already been implementing a modified version of the dailyzing model to enhance timetabling on the GQD. Future refinements could further enhance train scheduling by fine-tuning clusters to include more trains and integrating real-time adjustments, making India's railway system even more seamless and adaptable.

The researchers acknowledge that as the model scales up, new challenges will emerge. Long-distance trains often pass through multiple congested sections, where a single clustering approach may not be enough. A train that fits neatly into a cluster in one section of its journey may face bottlenecks elsewhere, requiring a different clustering strategy for different segments of the route. Moreover, since railway zones currently handle their timetables independently, future timetabling refinements will need better coordination across zones to fully realise the benefits of dailyzing. Addressing these complexities will be crucial in making Indian Railways even more efficient and adaptable in the years to come.

Article written by:	Ankush Banerjee
Image/ Graphic Credit:	Pixabay: Indian Railway
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Clustering techniques to optimize railway daily path utilization for non-daily …

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Mon, 17/03/2025 - 12:00

A novel Online Rummy “paddle-wheels” sensor to detect heavy metals in water

pro — Fri, 07 Mar 2025 10:45:07 +0000

A novel Online Rummy “paddle-wheels” sensor to detect heavy metals in water pro Fri, 07/03/2025 - 16:15

A novel Online Rummy “paddle-wheels” sensor to detect heavy metals in water

The low-cost sensor made of a copper-based metal-organic framework performs as well as DNA based sensor, the gold standard for water quality sensors.

Graphical representation of Cu-TCPP sensor detection of Cd, Pb and Hg atoms.
Credit: Prashanth Kannan

Heavy metals are elements with high atomic weights and densities. They play significant roles in various sectors, from manufacturing to agriculture. However, despite their utility, heavy metals also pose significant environmental and health concerns due to their potential toxicity, persistence, and bioaccumulative (ability to accumulate within living organisms) nature.

According to a report by The Energy and Resources Institute (TERI), nearly 718 Indian districts have groundwater contaminated with heavy metals, such as arsenic, cadmium, chromium, and lead. The Ministry of Environment, Forest and Climate Change (MoEF&CC) has also identified 320 locations as having a high probability of contamination with heavy metals. Ingesting these metals can cause serious health problems, including damage to the skin, bones, brain and other organs, especially in children. Efficient detection of these metals in water is crucial for ensuring environmental safety and public health.

In a bid to address heavy metal pollution, researchers from the Indian Institute of Technology, Bombay, and Monash University, Australia, with funding support from the Department of Biotechnology (DBT), Govt. of India, have developed a sensor using a copper-based metal-organic framework (MOF) to detect toxic metals in water more cost-effectively and efficiently.

Metal-organic frameworks (MOFs) are a class of materials characterised by their highly porous structures. At a microscopic level, these frameworks are composed of nodes of metal ions connected by organic compounds, forming a porous network with tunable properties and immense surface area to volume ratio. Due to their unique structure and versatility, MOFs have garnered significant interest in various scientific and industrial applications.

For their study, the team of researchers fabricated an MOF with copper (Cu) forming the metal nodes connected by the organic compound Tetrakis (4-carboxyphenyl) porphyrin, forming copper-tetracarboxyphenylporphyrin, or Cu-TCPP for short. The Cu-TCPP is a two-dimensional (2D) MOF with a paddle-wheel structure. The unique structure also means Cu-TCPP can have more surface area contacting the water and is much more efficient at picking up heavy metal ions than conventional 3D materials. The sensor is able to detect heavy metal ions like lead (Pb), cadmium (Cd) and mercury (Hg) in water samples, even when there are only a few atoms per millilitre present.

“This MOF involves two Cu atoms binding to each carboxyphenyl arm of the TCPP molecule, hence forming the characteristic paddle-wheel structure. This means that other metal ions with similar configurations would be able to replace Cu in the structure and maintain the overall order without causing structural collapse. Other metal ions, especially heavy metal ions, can also accumulate on the MOF lattice,” explains Prashanth Kannan, the first author of the paper and a student at the Online Rummy-Monash Research Academy, talking about the structure of the Cu-TCPP MOF.

Paddle-wheel structure of the Cu-TCPP MOF, with red copper atoms binding to the white TCPP molecule.
Credit: Authors

The Cu-TCPP detects heavy metal ions in water in two ways - by substitution, where a metal ion knocks the copper out and replaces it, or by accumulation, where the metal ions just accumulate on the surface. Lead has incomplete p-orbitals, meaning it needs more electrons to be stable. This incompleteness allows the lead to replace the Cu ions in the MOF seamlessly while still allowing the MOF to maintain its structure. Once the lead replaces the copper, MOF’s electronic properties also change, which allows researchers to measure the amount of lead in the water.

Metals like cadmium and mercury, on the other hand, don’t easily substitute with copper ions. Instead of replacing the copper, these metals accumulate at the surface, forming what are known as molecular islands on the surfaces of metals. “When faced with a highly regular periodic lattice arrangement such as the Cu-TCPP MOF, they initially accumulate on the surface of the MOF, then at high concentrations can cause the failure of the MOF structure. By identifying the differences in electrochemical waveform and intensity (during the failure), we are able to accurately estimate nanomolar levels of heavy metals in water,” explains Prashanth.

The researchers tested the sensor on water samples from taps and lakes. It accurately detected the three metals, lead, cadmium and mercury, even when present in trace amounts. The sensor performed well despite being tested with substances that could interfere with the MOF, like alkali metals, debris and other large particles, in the water, indicating its reliability in different conditions. The researchers then also compared their device with the state-of-the-art sensors available in the market and found that it performed comparably, if not better, in most cases. “Our device has the least complexity and comparable sensing limits to the best of the current DNA-based sensors (the gold standard for sensing devices),” remarks Prashanth.

Despite its performance, the sensor does have limitations. After a single use, the MOF structure tends to break down upon prolonged exposure to heavy metals. This means the sensor can only be used once. However, in the particular case of water quality sensors, since the industry standard for low-cost devices is one-time use, reusability is not needed and is not really a limitation of the sensor, according to Prashanth. “The major bottleneck with this type of device lies in material fabrication costs. MOFs are difficult to coat over large areas, but there are ongoing efforts by various research groups worldwide to make manufacturing possible on a large scale,” he adds.

The technology not only holds promise for improving public health but also highlights the potential of science to develop solutions to pressing environmental challenges. Prashanth is already looking ahead to the next challenges. “Currently, there are several topics of major interest worldwide that need materials like MOFs to address them, like detecting Perfluorooctane sulfonic acid (PFOS), perfluoroalkyl substances (PFAS), arsenic and chromium in drinking water and tap water,” he signs off indicating future applications.

Article written by:	Dennis C Joy
Image/ Graphic Credit:	Authors
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Tripartite Detection and Sensing of Toxic Heavy Metals Using a Copper-Based Por…

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Fri, 07/03/2025 - 12:00

Study suggests strategies to extract truth from unwilling senders

pro — Thu, 06 Mar 2025 10:57:27 +0000

Study suggests strategies to extract truth from unwilling senders pro Thu, 06/03/2025 - 16:27

Study suggests strategies to extract truth from unwilling senders
Offering limited options to choose from for a multiple choice setting recovers more accurate and truthful information than presenting the complete range of options, reveals Online Rummy study.

One would recall, with pain and much irritation, the times when one had to travel internationally during the COVID-19 times. If you happened to be the one inside the city receiving passengers, you would be afraid; what if the incoming passengers travelled through places with higher infection? If you were the traveller, you would like to believe that you are not infected and would want to avoid reporting your travel through COVID-19-affected cities. Health officers, on the other hand, had a tough situation to deal with. They had to extract as much truth from people unwilling to disclose the whole truth. All they could do was ask questions and believe the answers were true.

If you are wondering if there is any chance of recovering the truth, you can stop worrying! In a first of its kind study, Dr Anuj Vora and Prof Ankur Kulkarni from the Rummy Game (Online Rummy) tackle the challenge of how the receiver can design the right questions to learn as much truth as possible when the sender is not entirely cooperative, and there could be errors in communication due to noise.

Problems related to extracting information from people who are unwilling to disclose information or non-cooperative senders occur frequently, say, during negotiations. Negotiating parties may not give truthful information because they think that disclosing some facts may lead to an unfavourable deal. Extraction of information from non-cooperative senders is studied extensively in mechanism design theory. Roger Myerson laid the foundations of mechanism design theory and was awarded the 2007 Nobel Memorial Prize in Economic Sciences, along with Leonid Hurwicz and Eric Maskin.

“Mechanism design has not attempted to quantify the amount of information obtainable in settings where all information may not be obtainable,” explains Prof Ankur Kulkarni. In situations like the one faced by the health officer in COVID-19 times, it may not be possible to retrieve the complete travel history of all the travellers. However, it is important to know how much information can be obtained. “Quantification of information is the subject of information theory. We are the first to perform an information theoretic analysis of a problem that is broadly within the domain of mechanism design,” says Prof Kulkarni.

The current study shows that despite the sender being non-cooperative and the communication being noisy, the receiver can still recover a huge number of possible correct answers. At the same time, there are a huge number of correct answers that cannot be recovered, however cleverly the questionnaire is designed.

“Our results show on the one hand how a receiver may strategise to obtain information from such agents, and on the other that there will usually be blind spots in the knowledge of the receiver, regardless of how it strategises,” say the researchers.

Vora and Kulkarni quantify the amount of information that can be extracted by defining a quantity called the ‘information extraction capacity’. They established a method to calculate the range of values (the upper and lower limits) for this quantity and show that in several cases, the information extraction capacity can be exactly calculated. Their study provides strategies that the receiver can use to design the questionnaire and also a structural understanding of the kind of information that can be recovered.

The study assumes that the receiver will ask just one question and present a list of possible answers as options from which the sender chooses one correct answer. For example, a health officer may present sequences of cities visited before arriving at the current port. In a naive approach, the officer would list all possible sequences as the choices. However, it turns out that this approach gives travellers more opportunities to lie if they have information to hide. If the options are limited, travellers who wish to disclose some travel sectors but hide others will tend
to report more truthfully. The officers can recover the most truth by keeping the number of options within the optimal range, as suggested by the study.

The health officer may wish to know only a few cities visited previously. Thus, the length of the ‘sequence’ of cities may be limited to just a handful. However, in another situation, say when tax officers are trying to trace a chain of financial transactions, the sequence they wish to recover will be longer. More choices will need to be offered for the multiple-choice questions the officers ask. The number of optimal choices to be offered will grow with the increasing length of the sequence to be recovered. The researchers define the rate of growth of the number of optimal choices as the information extraction capacity. The quantity of communication resources required when communicating with a non-cooperative sender depends on the information extraction capacity.

Vora and Kulkarni bring in an aspect from information theory and model the communication when the communication itself may be noisy or not very accurate. For example, if one is trying to send a message over a communication line and say the line changes the letter B to D each time, then if the receiver gets D, they will assume it is D even when B is sent, making communication ambiguous for two letters (B and D). What it means in this case is that only 24 letters out of 26 can be sent without error. The amount of information that can be sent without errors is termed the zero-error capacity of the channel. In the current study, Vora and Kulkarni established that to utilise the information extraction capacity of the sender, the zero-error capacity of the channel needs to be more than the information extraction capacity and the receiver can extract a huge number of sequences in this case.

The study offers an insight into the basis of why certain questionnaires, such as in immigration or options offered by customer care bots, are not exhaustive. As users, we may frequently need to select an option that closely matches our case when we do not find an exact match. “Our study demonstrates that providing limited options in multiple choice questions may not be due to bad design, but it may be a strategy crafted to obtain as much truthful information as possible from a large number of users,” comments Prof Kulkarni.

This research was supported by the grant from the Science and Engineering Research Board, Department of Science and Technology, India.

The finding has applications in different fields, including finance, control systems, intelligence gathering and national security, market research and diplomatic negotiations. “Our results in this paper provide not only strategies for the receiver, but also a structural understanding of the type information that can potentially be recovered,” concludes Prof Kulkarni.

Article written by:	Arati Halbe
Image/ Graphic Credit:	-
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Shannon meets Myerson: Information extraction from a strategic sender

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Thu, 06/03/2025 - 12:00

Cobalt-based catalysts and more: reducing carbon emissions in steel industry

pro — Fri, 21 Feb 2025 04:21:45 +0000

Cobalt-based catalysts and more: reducing carbon emissions in steel industry pro Fri, 21/02/2025 - 09:51

Cobalt-based catalysts and more: reducing carbon emissions in steel industry

Combining hydrogen-based processes with advanced catalysts and renewable energy paves the way for developing economically and industrially viable solutions to decarbonise the steel industry

Image Credits: Wikimedia Commons

Globally, steel is a vital component of modern infrastructure and economic progress. India is among the top producers of steel. However, steel production is closely linked to environmental concerns as it relies heavily on coal as a fuel. In the steel production process, carbon (primarily sourced from coal and natural gas) reacts with iron ore to produce molten iron, which is then refined to create steel. However, this process also generates vast amounts of carbon dioxide (CO₂) but it also generates vast amounts of carbon dioxide (CO2). As a result, the steel industry globally emits over 3.7 billion metric tons of CO2 every year, contributing to 7–9% of carbon emissions. Steel production can be made sustainable by adopting a method called hydrogen-based direct reduction of iron (H-DRI).

In a recent review published in the Journal of Energy and Climate Change, researchers from the Chemistry Department at the Rummy Game (Online Rummy), led by Prof. Arnab Dutta, have collated the advances made in the field of hydrogen generation for the steel industry and put forward the best way to decarbonise the steel industry using ‘green’ hydrogen.

The H-DRI process uses hydrogen to convert iron ore into steel instead of coal, releasing water vapour rather than carbon dioxide as a byproduct during the manufacturing process. This makes hydrogen a great option for "decarbonising" the steel industry. Currently, most of the hydrogen comes from processes like steam methane reforming or coal gasification. Both rely on fossil fuels, which still generate CO2, defeating the primary purpose.

So, to produce hydrogen sustainably, researchers are shifting towards water electrolysis — a process of splitting water into hydrogen and oxygen using electricity in an electrolyser device. If renewable energy sources like wind or solar can power the electricity, the process becomes emission-free, hence the term ‘green hydrogen’. However, producing green hydrogen at an industrial scale is expensive as it needs considerable infrastructure modifications and effective catalysts.

Catalysts are essential to make the water electrolysis used for hydrogen production effective. Generally, noble metals such as platinum and palladium are used as catalysts. “These (noble metals) are expensive and limit large-scale applications, and are not suitable for harsh or remote conditions,” says Dr. Suhana Karim, a postdoctoral research fellow in Prof. Dutta’s lab. “So, the focus is on finding alternatives that are economically viable and sustainable,” she adds.

Researchers worldwide, including Prof. Dutta’s group, are developing cobalt-based catalysts (cobaloximes) that are water soluble and air-stable to aid electrolysis without requiring specialised equipment. Cobaloximes are cheaper than noble metals and can be synthesised easily.

Several researchers have improved the stability and reaction rates of cobaloximes by modifying their molecular structure. For example, Prof. Dutta and his team have added natural amino acids, vitamins, and other functional groups into the catalyst’s structure to increase hydrogen production rates while maintaining energy efficiency. “We have also modified cobaloximes to work effectively in the presence of various minerals and salts, such as in seawater,” adds Dr. Suhana.

Cobaloximes work well in labs, but it is complex to use them for industrial hydrogen production. Hence, researchers are modifying their structure to make it compatible with the electrodes of the electrolyser and attaching them to solid supports to enhance stability, efficiency, and durability.

The researchers also analysed different types of electrolysers and furnaces to improve hydrogen production using renewable energy for industry. They found that cobaloxime catalysts perform well in both alkaline electrolysers, using solutions like potassium hydroxide, and proton exchange membrane electrolysers, which use a solid polymer membrane in acidic conditions.

"Each type has strengths and weaknesses in cost, durability, and efficiency," explains Prof. Dutta.

In an electrolyser, when an electric current is passed through water, it splits, and hydrogen gets collected at the negative electrode (cathode) and oxygen at the positive electrode (anode). A complete set of electrodes, including a membrane, called a “stack”, separates the hydrogen and oxygen generation during electrocatalysis. Using multiple stacks, the electrolysers work more efficiently to produce copious amounts of hydrogen and can cut CO2 emissions by 30–50%, making the hydrogen-based energy economy more sustainable. “A single stack might produce one litre of hydrogen per day, but an appropriately designed multi-stack system can produce ten times as much using the same control setup,” explains Prof. Dutta.

Prototype of a multi-stack electrolyzer developed by Prof. Arnab Dutta's research group. (Photos by: Arnab Dutta and Suhana Karim)

Researchers from Online Rummy also point out that the traditional blast furnace-basic oxygen furnace method uses a lot of coal to produce steel, releasing a significant amount of CO₂. In contrast, the electric arc furnace uses electricity, and when powered by renewable energy, it produces less carbon emissions. Researchers believe that by combining hydrogen-based direct reduction of iron with electric arc furnace technology, steelmaking can become nearly carbon-neutral.

The use of green hydrogen can further be combined with carbon capture, utilisation, and storage (CCUS) strategies to further reduce emissions. CCUS systems capture any leftover CO₂ from steelmaking or other processes, allowing its use to produce synthetic fuels or chemicals or stored deep underground for the long term. This approach also promotes a circular economy by reusing CO₂ in productive ways.

The Online Rummy study highlights how water electrolysis using cobalt-based catalysts, and
choosing suitable electrolysers and furnace types, can produce green hydrogen-based steel. This approach helps significantly reduce carbon emissions, paving the way for a cleaner and more
sustainable future for steel production.

Article written by:	Manjeera Gowravaram
Image/ Graphics Credit:	Lead image: Wikimedia Commons Inline image: Prof Arnab Dutta and Dr Suhana Karim
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Cobalt-based molecular electrocatalyst-mediated green hydrogen generation: A po…

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Fri, 21/02/2025 - 12:00

Online Rummy researchers use new technique to measure rate of degradation of coatings on iron

sagar_sinnarkar — Tue, 04 Feb 2025 12:25:36 +0000

Online Rummy researchers use new technique to measure rate of degradation of coatings on iron sagar_sinnarkar Tue, 04/02/2025 - 17:55

Online Rummy researchers use new technique to measure rate of degradation of coatings on iron

Combining two electrochemical techniques, hydrogen permeation-based potentiometry (HPP) and electrochemical impedance spectroscopy (EIS), the researchers efficiently measured the coating degradation rates on the industrially relevant metal.

Representative image: Credits peter731 from Pixabay

Metals corrode with time, and some metals corrode more than others, e.g., iron rusts in days, while gold and silver take decades or centuries to deteriorate. Metals often have a layer of protective coating, like the paint on our cars, to prevent corrosion. A more efficient way of protecting metals is by coating them with organic coatings. Organic coatings are layers of carbon-based polymeric substances, natural or synthetic, applied in the form of paints and varnishes. According to a recent market analysis report by Grand View Research, the market for such corrosion inhibitors is a USD 8.93 billion market projected to grow at 3.6% annually from 2025 to 2030.

The efficiency of organic coatings deteriorates with time, eventually damaging the metal. That is because the coatings have pores and defects that allow water and oxygen to reach the underlying metal surface over time and corrode it. The coating wears with time because of a fundamental electrochemical process called oxygen reduction reaction (ORR), where molecular oxygen gets reduced to water, hydrogen peroxide or hydroxyl ions. This process occurs in various electrochemical devices, including fuel cells and metal-air batteries. Understanding the rate at which ORR occurs is important to know how quickly the coating may give way for the metal to corrode. This knowledge is critical in several industrial applications.

Traditional techniques, such as linear sweep voltammetry and potentiodynamic polarization, used to measure ORR rate are based on electrochemistry, i.e., chemical reactions that produce or consume electrical energy. In linear sweep voltammetry, a continuously changing voltage is applied to the metal and the current generated in response to it is measured. The resulting current-voltage curve provides insights into the rate at which ORR can occur on the metal. However, in coated metals, because organic coatings block the passage of ions required to generate current, the rate at which the coating degrades is often representative of current generated only at pre-existing tiny holes in the coating. This may not reflect the actual degradation rate at the interface.

A couple of years ago, researchers led by Prof Vijayshankar Dandapani at the Department of Metallurgical Engineering and Materials Science at the Rummy Game (Online Rummy) established an improved quantitative method to characterise the performance of organic coatings used for corrosion protection.

In their innovative approach, the Online Rummy researchers combined hydrogen permeation-based potentiometry (HPP) with electrochemical impedance spectroscopy (EIS). In the HPP setup, researchers apply an electrical current on one side of the metal to generate hydrogen. The hydrogen atoms then permeate through the metal and cause changes in electrochemical potential measured on the other side containing oxygen. In this way, the amount of hydrogen that has passed through the metal is used as a sensor to measure the ORR rate.

EIS is a technique used to analyse how materials respond to electrical signals. An alternating current (AC) voltage is applied to the material, and the resulting current response is measured, from which the material’s impedance (or resistance) can be calculated. The impedance value associated with different processes occurring on the metal surface, including hydrogen-induced ORR progress, can be monitored at a certain frequency of the AC signal.

Combining HPP and EIS techniques allowed the researchers to quantify the degradation rates at the interface between the organic coating and the metal. While HPP gives a direct measure of hydrogen permeation, EIS provides insights into how hydrogen permeation corrodes the coated metal.

“The idea itself came from an attempt to find if a complementary technique such as EIS can be used to strengthen the interpretations from the hydrogen permeation-based potentiometry (HPP) approach,” says Prof Vijayshankar.

In their earlier study, the researchers provided a proof-of-concept by measuring ORR at the interface between a model polymer coating and palladium metal using HPP and EIS. In this new study, the Online Rummy group, along with researchers from the University in Brest, France, have extended this application to an important industrial metal, namely, iron.

This study received funding from the Indo-French Centre for Promotion of Advanced Research -CEFIPRA and the Science and Engineering Research Board (SERB), India.

The researchers coated a thin layer of iron on palladium membranes and coated the iron with a polymer called poly-methyl methacrylate (PMMA). They measured the rate at which oxygen reduction reaction occurred at the interface between PMMA and iron using HPP-EIS. They captured the current-potential (I(U)) curves and corresponding impedance values, which they found to be higher than that for a bare iron surface. High impedance values correspond to low corrosion rates and vice versa. This validated the use of the HPP-EIS technique to evaluate ORR occurring at interfaces that one cannot easily study using the traditional methods because the interface between organic coatings and metals is buried and inaccessible.

(Left) ORR-assisted polymer coating degradation eventually forming rust on the iron layer deposited on the palladium membrane. (Right) Mechanism of HPP-EIS for determining ORR rate before rust formation.

HPP-EIS is cost-effective because it requires only two potentiostats, simple electronic devices that control and measure the voltage between two electrodes.

So, HPP-EIS can be used to monitor how quickly the organic coating will give way for the iron to rust in this particular instance. According to Prof Vijayshankar, this method would be of interest not only to the steel industry but will also be useful in the field of fuel cells and sensors.

With hydrogen blending becoming increasingly popular to reduce emissions from natural gas, one can also apply HPP-EIS technique “to determine how quickly the coat of paint on a natural gas pipeline where hydrogen is blended with natural gas degrades,” says Prof Vijayshankar, highlighting a potential application.

Article written by	Joel P Joseph
Image/Graphics credit	Image by peter731 from Pixabay
link to gubbi labs	-

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Cathodic oxygen reduction kinetics at an organic coating/iron interface using a…

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Tue, 04/02/2025 - 12:00

Natural Disasters and Climate Change Have a Long-Term Impact on State Finances

pro — Thu, 30 Jan 2025 04:11:14 +0000

Natural Disasters and Climate Change Have a Long-Term Impact on State Finances pro Thu, 30/01/2025 - 09:41

Natural Disasters and Climate Change Have a Long-Term Impact on State Finances

Researchers use a Disaster Intensity Index (DII) to assess disaster impacts on state budgets, offering a roadmap for better disaster preparedness and economic protection.

Representative image: Courtesy PixaHive

India’s location and tropical monsoon climate make the region highly vulnerable to natural disasters such as floods and cyclones, especially in coastal and river areas. Each year, the country experiences five to six tropical cyclones, with two or three being severe. These disasters cause not only immediate loss of life and property but also put a significant financial strain on the government.

The state government bears much of the disaster response cost after natural disasters such as floods and cyclones, impacting its budget. A recent study by Ms. Nandini Suresh, Prof Trupti Mishra, and Prof D. Parthasarathy of the Rummy Game (Online Rummy) analysed the financial impact of floods and cyclones on 25 states over 24 years (1995–2018). The research is published in the International Journal of Disaster Risk Reduction.

Traditionally, disaster response funding relies on estimating the cost of damages based on evaluating economic losses, the number of deaths, and the number of people affected. These evaluations are often inconsistent and biased. Instead, “We relied on data from weather and geographic sources (IBTrACS and the India Meteorological Department) to accurately measure cyclone strength (using wind speeds) and flood severity (based on unusual rainfall),” says Ms
Nandini Suresh. By combining this information, the researchers created a Disaster Intensity Index (DII), ensuring all types of disasters are treated fairly. The method avoids inconsistencies and biases and gives a clearer picture of disaster impacts, especially for floods and cyclones, which caused 80% of disaster-related losses in India during the study period.

The study uses a statistical model called panel Vector Auto Regression (VAR) to examine how revenue and expenditure affect each other from one year to the next few years. The model allows accounting for differences between states and ensures that past economic conditions don’t unfairly influence disaster severity measurements, giving a reliable way to study the financial impacts of disasters.

The findings from the study show that disasters put a heavy financial burden on affected states. First, disasters increase the state’s expenditure. The government must allocate substantial funds for immediate relief efforts such as evacuation, medical aid, food, and shelter. After the disaster, it must invest in rebuilding essential infrastructure such as roads, bridges, and homes. Secondly, these disasters reduce the government's revenues. As agriculture, trade, and business operations are often disrupted, tax collection and income from these services are reduced. The study highlights a cycle in which increased expenditures and falling revenues lead to more significant budget deficits.

However, based on the created DII, the study shows that disasters impact states differently. Less disaster-prone states like Madhya Pradesh and Chhattisgarh, which experience droughts and occasional floods, can handle relief with their own resources and suffer less financial damage. The disaster intensity is not high enough to affect people’s income or production; hence, there is no decrease in tax or non-tax revenues. On the other hand, disaster-prone coastal states like Odisha, Andhra Pradesh, and West Bengal, which frequently experience cyclones and floods, have higher recovery expenses and higher revenue losses. As a result, they often need to rely on external funding like loans, increasing state debt and making it difficult to fund other development projects.

The assistance offered by the National and State Disaster Response Funds (NDRF and SDRF) could be optimised for improved efficiency and faster disbursal. Certain regulations, such as the 25% cap on SDRF allocations for relief operations and some procedural requirements, may create hurdles in utilising these funds in a timely manner. By simplifying these processes, there may be an opportunity to enhance the overall impact of disaster relief initiatives.

The study emphasises the need for proactive disaster risk financing mechanisms such as resilience bonds, disaster insurance, and catastrophe bonds. Resilience bonds encourage investments in disaster prevention projects and offer incentives for reducing the effects of disasters. Disaster insurance supports individuals, companies, or governments in recovering from losses brought on by natural disasters. Catastrophe bonds allow governments or organisations to shift disaster risk to investors who receive interest unless a disaster occurs. “These provide quick funds during emergencies and reduce the need to take external loans after disasters,” says Ms Nandini.

However, implementing such measures in India is challenging due to a lack of awareness and understanding among stakeholders, including governments and the public, about the benefits of such instruments. The other key challenges include the high cost of disaster insurance premiums and a lack of a clear financial and legal framework for issuing resilience bonds or incorporating them into state budgets.

Public-private partnerships are also essential for building a climate-resilient economy. Governments can offer tax incentives for businesses to invest in climate resilience infrastructure and enforce sustainability regulations.

Diverting funds from other projects is a usual way for governments to handle disasters while staying within budget. However, it’s difficult to move money from fixed expenses like debt payments, salaries, or pensions as these take up most of the budget and are already set by law. Governments need flexible budgets, backup plans, and quick ways to adjust spending based on what is required so that they can quickly reallocate funds during emergencies.

The study also suggests states invest in early warning systems, cyclone shelters, and resilient infrastructure and promote sustainable land use that can minimise the economic impact of climate change and lower the long-term costs of dealing with disasters. Many states have already made progress: Tamil Nadu has installed advanced cyclone monitoring systems, Kerala has adopted climate-adaptive urban planning, and Odisha and many others have introduced budget tracking for climate-related spending.

With climate change increasing the frequency and intensity of disasters, Indian states will face greater financial challenges. “By adopting these measures, India can mitigate long-term financial risks while protecting lives and infrastructure and build a stronger, more sustainable future,” concludes Ms Nandini.

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