Research News

The paper “A unique bridging facets assembly of gold nanorods for the detection of thiram through SERS” has been published by Prof Ranjit Thapa, Professor of Physics and his PhD student, Ms Anjana Tripathi, in ACS Sustainable Chemistry & Engineering having an Impact Factor of 8.198.

Abstract

The addition of Au NRs (Gold Nanorods) to TRM (Thiram) of higher and lower concentrations, yields side-by-side assembly (SSA) and bridging facets assembly (BFA), respectively, and exhibited excellent hotspots for the ultra-low detection of TRM. Bridging facets of Au NRs, such as (5 12 0) and (5 0 12) planes are mainly responsible for the BFA. This kind of interaction is observed for the first time and not reported elsewhere. The detailed facets of Au NRs, namely side facets, bridging facets, and pyramid facets, were discussed with the 3D model of Au NRs. The computational studies confirm the SSA and BFA for Au NRs with varying concentrations of TRM are well in agreement with the experimental results.

Research in brief

Au NRs were synthesized successfully using the seed-mediated method and characterized by UV-Vis analysis, SEM, TEM, FT-IR, Raman, and XPS analysis. Synthesized Au NRs were employed for the detection of TRM. Upon adding Au NRs to TRM of higher and lower concentrations yields side by side (SSA) and bridging facet assembly (BFA), validated by TEM analysis. This unique BFA was observed for the first time and not reported before to the best of our knowledge. Elemental mapping confirms the good adsorption of TRM over Au NRs, and FT-IR, Raman, SERS, and XPS analysis confirm the adsorption of TRM on Au NRs through Au-S bond. A uniformity study was performed for the TRM-Au NRs sample using 25 random places and obtained an RSD of ≤ 10% for each peak in SERS. This shows TRM is uniformly adsorbed on Au NRs. LOD and EF were achieved at 10 pM and 2.8 ×106, respectively. Hence, Au NRs are considered an excellent substrate for the detection of TRM. The unique assembly of BFA may play a significant role in the research community to further study the facet-dependent interactions of nanostructures. The computational study was performed to know the reason behind SSA and BFA. The density functional theory (DFT) was carried out using the Vienna Ab-initio Simulation Package (VASP). The Perdew-Burke-Ernzerhof (PBE) functional within Generalized Gradient Approximation (GGA) is adopted to treat the exchange-correlation interactions. These studies confirm the formation of a strong bond between Au and S, as well as the SSA and BFA for higher and lower TRM concentrations with Au NRs. The binding energy of TRM in SSA and BFA is -3.81 eV and 3.19 eV respectively. From the theory, it shows that TRM of lower concentration form BFA and higher concentration of TRM, due to high barrier energy for TRM diffusion, Au NRs form SSA. In this respect, we calculated the activation barrier for thiram migration from edge site (BFA) to in between site (SSA). Results indicate that TRM needs 2.40 eV energy to migrate from the edge site to in between site to form side-by-side assembly. Therefore, for diffusion from edge to in between (SSA) site high-energy barrier is required i.e. higher concentration is required for such configuration. Hence, at low concentration, TRM will form bridge facet assembly and due to high barrier energy for TRM diffusion, the side-by-side assembly is possible only at high concentration.

Practical implementation/social implications

Concerns have grown in recent years about the widespread use of the pesticide thiram (TRM), which has been linked to negative effects on local ecosystems. This highlights the critical need for quick and accurate point-of-need pesticide analysis tools for real-time applications. The detection of TRM using gold nanorods (Au NRs) with a limit of detection (LOD) of 10-11 M (10 pM) and an enhancement factor (EF) of 2.8 × 106 along with 6.2% of signal homogeneity (with respect to peak at 1378 cm-1) achieved through surface-enhanced Raman scattering (SERS). The interaction of Au NRs with TRM is sensitive, and ultra-low detection of hazardous TRM through SERS makes an ideal technique for environmental protection, real-time applications, and analysis of one-of-a-kind materials.

Collaborations

Bhavya M. B, Akshaya K. Samal
Institute: Centre for Nano and Material Sciences, Jain University, Jain Global Campus
Ramanagara, Bangalore 562112, India

Proteins are the most vital life forms which maintain close coordination with almost living activities through their biological functions. Nevertheless, in most cases, proteins suffer from low charge (electron) transfer efficiency as they are mainly made of insulating organic molecules. The interdisciplinary research publication, of Dr Sabyasachi Mukhopadhyay and Dr Sabyasachi Chakrabortty from the Department of Physics & Department of Chemistry respectively, along with their PhD scholars: Ms Ashwini Nawade, Mr Kumar Babu Busi and Ms Kunchanapalli Ramya, envisions the molecular-level understanding of the charge transport behaviour of various protein-metal nanocluster hybrid.

The article titled ‘“Improved Charge Transport across Bovine Serum Albumin – Au Nanoclusters’ Hybrid Molecular Junction” was featured in the prestigious Q1 journal ACS Omega (IF: 3.512), published by the ‘American Chemical Society’. They successfully incorporated Gold Nanoclusters inside the protein backbone leading to an increase in their conductivity. This will provide new avenues for the rational design of bioelectronic devices with optimized features. The BSA-Au cluster has been a promising model for bioelectronic functionalities. With an increase in their current carrying capacity, they can be used for many more applications, especially as the interface between tissue and organ in biocompatible devices. The research team is also planning to work with various protein dopants to understand their charge transport mechanism. These studies will help in using the protein for various applications mainly in bioimplants or biosensors for drug testing and diagnostics purposes.

Abstract of the Research

Proteins, a highly complex substance, have been the essential element in the living organism where various applications are envisioned due to their biocompatible nature. Apart from protein’s biological functions, contemporary research mainly focuses on their evolving potential associated with nanoscale electronics. Here, we report one type of chemical doping process in model protein molecules (BSA) to modulate its electrical conductivity by incorporating metal (Gold) nanoclusters on the surface or within it. The as-synthesized Au NCs incorporated inside the BSA (Au 1 to Au 6) were optically well characterized with UV-Vis, time-resolved photoluminescence (TRPL), X-ray photon spectroscopy, and high-resolution transmission electron microscopy techniques. The PL quantum yield for Au 1 is 6.8% whereas Au 6 is 0.03%. In addition, the electrical measurements showed ~10-fold enhancement of conductivity in Au 6 where maximum loading of Au NCs was predicted inside the protein matrix. We observed a dynamic behaviour in the electrical conduction of such protein-nanocluster films, which could have real-time applications in preparing biocompatible electronic devices.

Water pollution continues to be one of the serious concerns facing the country. The ensuing scenario of eutrophication and harmful algal blooms has exacerbated the menace. This demands wholescale water management techniques to segregate the pollutants, retrieve useful nutrients, and treat the water effectively for sustainable use. Dr Karthik Rajendran and his PhD scholar, Mr Sarath Chandra, from the Department of Environment Science have published a paper discussing various nutrient recovery methods and their consequential outcomes. The research was done in collaboration with Dr Deepak Kumar from SUNY College of Environmental Science and Forestry, Syracuse, NY and Dr Richen Lin from Southeast University, Nanjing, China.

The article titled, “Nutrient recovery from wastewater in India: A perspective from mass and energy balance for a sustainable circular economy” was published in Bioresource Technology Reports (Q1 Journal), having an Impact Factor of 4.41. Their research investigates the possibilities of recovering Nitrogen (N) and Phosphorous (P) from wastewater in terms of technology, energy, and economic point of view. Excessive presence of Nitrogen and Phosphorous can result in eutrophication and algal blooming. These nutrients also pose a harmful threat to infrastructure. Nutrient recovery can mitigate these challenges and improve the quality of water.

Phosphorus is one of the limited resources available on earth and a key ingredient in fertilizer production. The recovery process also helps in transforming wastewater into resource pools that can efficiently churn out valuables that hold the key to a sustainable future. This will help reduce the imports of fertilizers and bring down the emissions to half in producing fertilizers. Their findings will also pave the way for making necessary policies to reduce water pollution and recover nutrients. As two-thirds of wastewater remains uncollected, they claim that effective treatment and water management practices can save around 800 crores per annum. Their future research plan also includes the experimental analysis of the nutrient recovery system.

Abstract of the Research

Wastewater (WW) is a potential source to recover N, and P, whereas, in India, it is scarcely explored. In this work, four different nutrient recovery methods were compared from a mass- and energy-balance perspective to understand the overall process flow. From 1000-m3 WW, chemical precipitation yielded 33.8 kg struvite, while micro-algae resulted in 299.1 kg (dry powder). Energy consumption was lowest for the fuel cells at 216.2 kWh/1000 m3, while microalgae used the highest energy at 943.3 kWh/1000 m3. Nonetheless, the cost-saving analysis showed that microalgae (78.6$/1000 m3) as a nutrient recovery choice, had higher savings than any other methods compared. For a country like India, where two-thirds of urban wastewater is untreated, wastewater-biorefinery options such as nutrient recovery hold the key to a sustainable circular economy.

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A paper titled “Study on ferroelectric polarization induced resistive switching characteristics of neodymium-doped bismuth ferrite thin films for random access memory applications” has been published by Dr Pranab Mandal, Assistant Professor of Physics and his PhD student, Ms K N Malleswari in the journal ‘Current Applied Physics’ having an Impact Factor of 2.480.

Doi: https://doi.org/10.1016/j.cap.2022.04.013

Abstract

Resistive random-access memory (ReRAM) devices are based on the resistance switching (RS) effect. Such RS devices have recently attracted significant attention due to their potential application in realizing the next-generation non-volatile memory (NVM) devices. The present work reports on resistive switching (RS) characteristics of Neodymium (Nd)-doped bismuth ferrite (BFO) layers. The Nd (2–10 at%) doped BFO thin film layers were deposited using a spray pyrolysis method. The structural analysis reveals that a higher Nd doping concentration in BFO leads to significant distortion of the prepared Nd: BFO thin films from rhombohedral to tetragonal characteristics. The morphological analysis shows that all the deposited Nd: BFO thin films have regularly arranged grains. The X-ray photoelectron spectroscopy (XPS) analysis reveals that the prepared Nd: BFO thin films have a higher Fe3+/Fe2+ ratio and fewer oxygen vacancy (VO) defects which enrich the ferroelectric characteristics in Nd: BFO layers. The polarization-electric field (P-E) and RS characteristics of the fabricated Nd: BFO-based RS device were examined. It was observed that the Nd (7 at%) doped BFO RS device shows large remnant polarization (P r) of 0.21 μC/cm2 and stable RS characteristics.

Research in brief

Non-volatile resistive random access memory (RRAM) are future generation random access memory device with potential benefits such as high operational speed (nanoseconds read and write time), non-volatility, high endurance scalability and low power consumption [Namnoscale Research Lett., 15, 90, 2020]. Here in this work, we presented the resistive switching characteristics of a multiferroic material namely Nd-doped BiFeO3 material. The device shows stable resistive switching characteristics.

Practical implementation/social implications

Researchers in this field are focusing to overcome challenges of high operation current, lower resistance ratios, and reliability issues [Namnoscale Research Lett., 15, 90, 2020]. While several prototype RRAMs have been developed by other groups, future memory applications would require overcoming the challenges mentioned above.

Collaboration

The work has been conceptualized by Dr Amiruddin at  Crescent Institute of Science and Technology, Chennai; and Dr Pranab Mandal and Ms Malleswari provided inputs on ferroelectric polarization – electric field (P – E) measurement and drafting.

A paper titled “Organic food preferences: A comparison of American and Indian consumers” has been published by Prof Bharadhwaj Sivakumaran, Dean- SEAMS, SRM University-AP, Kirubaharan Boobalan (SSN College of Engineering), and Margaret Susairaj (Great Lakes Institute of Management, Chennai) in the journal Food Quality and Preference having an Impact Factor of 5.6.

This research tests a nomological model predicting organic food attitudes and purchase intentions in USA and India. Data were collected from India (n = 687) and the USA (n = 632) using Amazon M Turk and were analyzed using structural equation modelling and multi-group moderation technique. Results revealed that over and above attitude, subjective norm and perceived behavioural control, response efficacy and self-expressive benefits significantly affect consumers’ attitudes and purchase intentions toward organic food among American and Indian consumers. Findings reveal that response efficacy and attitude matter more in the USA while subjective norms and self-expressive benefits exert a greater influence in India. Therefore, marketers may reinforce belief-related elements while selling organic food products in the USA and societal-related elements while selling in India. Theoretically, this work adds to the Theory of Planned Behavior by adding self-expressive benefits and develops a common model for organic food across samples in USA and India.

Surface-enhanced Raman Spectroscopy (SERS) is a nuanced chemical technique that amplifies the Raman scattering of molecules by utilising plasmonic nanostructured materials. SERS operates as a powerful detection tool that allows for the structural fingerprinting of a molecule. The ultra-high sensitivity and selectivity of the process offer it a vast array of applications in surface and interface chemistry, nanotechnology, biology, biomedicine, food science, environmental analysis and other areas.

Dr J P Raja Pandiyan and his PhD scholar, Ms Arunima Jinachandran from the Department of Chemistry have been keenly involved in exploring the possibilities of SERS technology in food science and other fields. The safety and quality concerns related to food were the primary reasons that impelled them to step into this domain. Their article “Surface-enhanced Raman spectroscopy for food quality and safety monitoring” was published in the book Nanotechnology Applications for Food Safety and Quality Monitoring, published by Elsevier. The article was published in collaboration with Dr Selvaraju Kanagarajan from the Swedish University of Agricultural Sciences.

As an analytical technique, SERS possesses several advantages such as non-destructive, sensitive, and selective. In the chapter, the necessity, and applications of SERS in food science are elaborately discussed. They have also discussed all the possible food contaminants and how to identify them using SERS to ensure food quality. This book will serve as an enlightening read to research groups who are working on Raman, surface-enhanced Raman spectroscopy, analytical chemistry, and food quality analysis.

In recent years, human activity recognition has gained significant attention inside the scientific community. The enhanced spotlight is on the ground of its direct application in multiple domains. The latest research at the Department of Computer Science validates this assumption. Assistant Professor Dr V M Manikandan, and the 4th year B Tech Student Chaitanya Krishna Pasula have published a chapter titled An analysis of human activity recognition systems and their importance in the current era in the book Computational Intelligence Based Solutions for Vision Systems. The book is published by IOP Publishing Ltd.

Explanation of the chapter

Human activity recognition is one of the most interesting and active research areas in computer vision. More research efforts are being put towards automatically identifying and analysing human activities due to their emerging importance in everyday applications. It serves applications in various areas like security video surveillance, smart homes, healthcare, human-computer interaction, virtual reality, robotics, and digital entertainment. Numerous papers have been published in the domain of human activity recognition. This book chapter discusses the various applications of human activity recognition, different methods available for automatic activity detection from videos, and the advantages of the human activity recognition system. It also describes the challenges in designing and implementing human activity detection schemes. Researchers further explain the publicly available datasets used for training and evaluating the systems for human activity recognition. The efficiency parameters used to evaluate the human activity recognition systems are also briefed in this chapter. The chapter is concluded by comparing the methodologies and speculating the possibilities of future research in this field.

In the future, the researchers are planning to design and implement an activity recognition system to identify abnormal activities in public places for safety purposes. This book chapter will be a helpful reference for UG/PG/Ph.D students who aspire to research in the domain of activity detection from video.

High-entropy alloys (HEAs) are gaining research significance in recent times as they propose novel alloy designs and concepts demonstrating better performance. HEAs constitute multiple principal elements in varying concentrations and combinations to produce new materials with excellent physical properties and superior performance at extreme temperature conditions. Recent studies have brought out a few high-entropy alloys possessing exceptional properties, even capable of challenging the existing theories and models for conventional alloys. However only very little has been explored within this multidimensional space leaving limitless possibilities to be explored and materialized.

Dr Sheela Singh, from the Department of Mechanical Engineering, has been conducting rigorous research in this domain and she has published research articles proposing novel ideas to tweak the properties of HEAs. In one of the articles co-authored by Dr Sheela, “Effect of minute element addition on the oxidation resistance of FeCoCrNiAl and FeCoCrNi2Al high entropy alloy”, published in the journal Advanced Powder Technology, she investigates the effect of Ti0.1 and Ti0.1Si0.1 addition on the high-temperature isothermal oxidation behaviour of dense FeCoCrNiAl and FeCoCrNi2Al high entropy alloys.

Mechanical properties such as hardness & young’s modulus, thermal properties such as melting temperature, specific heat capacity and coefficient of thermal expansion (CTE) were investigated by Nano hardness tester (NHT), differential scanning calorimetry (DSC) and dilatometer, respectively. The phases present in the HEAs produced by hot vacuum pressing and after isothermal oxidation were characterized by X-ray diffraction, Scanning Electron Microscopy and Raman Spectroscopy.

The weight gain recorded after isothermal oxidation for 5,25,50 and 100 hours at 1050°C was found to be parabolic in nature. X-ray diffraction analysis (XRD), as well as Raman spectroscopy analysis of HEA’s oxidized at 1050°C for 100 hours, shows the formation of the Al2O3 phase. A homogeneous thin oxide scale without any discontinuity was observed throughout the cross-section. It has been confirmed that Ti & Si addition in minute amount (0.1 at. % each) improves the mechanical properties and oxidation resistance as well as reduces the waviness of the oxide scale.

Another article co-published by her, “Enhanced Magnetization with Increased Chromium Concentration in FeCoCrxNi2Al High-Entropy Alloy”, in Materials and Science Technology, reports the effect of increasing the concentration of antiferromagnetic element Cr in FeCoCrxNi2Al (x = 0.5, 1.5) High Entropy Alloy (HEA) on their magnetic properties. It was found that the structure and composition of different phases, and the likely degree of spinodal decomposition in the Cr-Fe rich BCC phase significantly affects the magnetic properties.

Interestingly, the sample with Cr concentration x=1.5 showed two times larger saturation magnetization as compared to x=0.5. Furthermore, the magnetization versus temperature response shows a multi-phase character and exhibits distinct behaviour in low temperature and high-temperature regimes in both samples. The obtained soft ferromagnetic behaviour of these HEAs is crucial for the development of a new class of HEA for various applications.

The considerable structural and functional potential, as well as the richness of design, make HEAs promising candidates for new applications prompting further studies in the field. There remains a vast compositional space that is yet to be discovered. New studies have to be initiated finding out effective ways to recognise regions within this space where high-entropy alloys with potentially interesting properties may be lurking. Dr Sheela’s research is a right step in this direction to pave the way for fruitful developments in the future.

Q1 journal publications of our faculty members always bring honour to SRM University-AP. Dr Priyanka Singh, Assistant Professor from the Department of Computer Science and Engineering has published a paper titled “Ameliorated Follow the Leader: Algorithm and Application to Truss Design Problem” in the journal Structures (Q1 journal) having an impact factor of 2.983.

Abstract

In the real world, resources, time, and money are always limited, necessitating the need for well-balanced algorithms. According to the “No-free-lunch” theorem, no single algorithm exists that works well in all applications. Hence, an optimisation algorithm with improved performance is always needed. The paper presents an improved follow the leader (iFTL) algorithm that imitates the behavioural movement of a sheep within the flock. The algorithm has been utilised to solve eight complex 10, 37, 52, 72, 120, 200, 224, and 942 bar truss design problems.

Practical implications

The algorithm can be utilised to solve several structural and mechanical design problems such as bride design, antenna design, welded beam design, speed reducer, and many more. The algorithm is well suited for all types of real-life engineering problems where optimisation is required, from travel cost optimisation to optimisation of resources in the organisation under the given constraints and objective function.

Collaborators

1. Rahul Kottath (Computer Vision Engineer, Digital Tower, Bentley Systems India Private Limited, Pune, India)
2. Ghanshyam G. Tejani (Assistant Professor, Department of Mechanical Engineering, School of Technology, GSFC University, Vadodara, Gujarat, India)

Future Research Plan

Currently, Dr Priyanka is exploring new engineering applications where optimisation techniques can be used. She is working on optimisation methods that can be utilised to classify microarray data, energy optimisation, and mechanical and structural design problems. In future, she plans to propose her work to the industrial level for the greater good and better solutions.

With its vast applications in the industry, computing influential nodes is becoming a popular research field in recent days. The Department of Computer Science and Engineering is delighted to inform you that the paper, Computing Influential Nodes Using Nearest Neighborhood Trust Value and Pagerank in Complex Networks have been published by Dr Murali Krishna Enduri, Assistant Professor, Dr Satish Anamalamudi, Associate Professor, and the PhD students; Koduru Hazarathaiah, Ms Srilatha Tokala in the Entropy Journal (Q2 Journal), with an impact factor 2.587.

Abstract

Computing influential nodes attract many researchers’ attention for spreading information in complex networks. It has vast applications such as viral marketing, social leaders, rumour control, and opinion monitoring. The information spreading ability of influential nodes is more compared with other nodes in the network. Several researchers proposed centrality measures to compute the influential nodes in the complex network, such as degree, betweenness, closeness, semi-local centralities, PageRank, etc. These centrality methods are defined based on the local and/or global information of nodes in the network. However, due to the high time complexity, centrality measures based on the global information of nodes have become unsuitable for large-scale networks. Very few centrality measures exist that are based on the attributes between nodes and the structure of the network. We propose the Nearest Neighbourhood Trust PageRank (NTPR) based on the structural attributes of neighbours and nearest neighbours of nodes. We define the measure based on the degree ratio, the similarity between nodes, the trust value of neighbours, and the nearest neighbours.

Explanation of the research

The research computes the influential nodes on the various real-world networks by using the proposed centrality method NTPR. The researchers find the maximum influence by using influential nodes with SIR and independent cascade methods. They also compare the maximum influence of our centrality measure with the existing basic centrality measures.

Social implications

Viral Marketing is a business strategy that uses existing social networks to promote products. The influential nodes in complex networks can be found using the centrality measure and can be used as the seed nodes for promoting products in the social networks. A rumour is a statement being said without knowing if it is true or not. The rumours can be easily controlled by discovering influential nodes. The researchers look forward to finding a centrality measure to detect the influential nodes efficiently.