Interdisciplinary research and the integration of perspectives
Assistant professors Dr Sabyasachi Mukhopadhyay and Dr Imran Pancha from the Department of Physics and the Department of Biological Sciences, respectively, along with Ms Ashwini Nawade, a PhD student of the Department of Physics, have developed a method to integrate plant proteins in the solid-state electronic circuits and utilize the biological functionality to produce a thin film, cost-effective photodetector. Their paper entitled Electron Transport across Phycobiliproteins Films and its’ Optoelectronic Properties has been published in the ECS Journal of Solid State Science and Technology with an Impact Factor of 2.07. It is an interdisciplinary research project between the Department of Biotechnology and Physics.
Explanation of the research
Biomolecules such as proteins, peptides being the most crucial life-forms, have an intimate relationship with various life activities for biological functions. The contemporary work with biomolecules mainly focuses on its evolving potential associated with nanoscale electronics where proteins and peptides are integrated as sensing materials. The researchers explored the optoelectronics functionality of combined proteins known as phycobiliproteins. They investigated electron transport behavior across the phycobiliproteins films under dark and white light illumination. The research affirms that the photochemical activity of the protein is more stable in a solid-state/ thin-film with tightly bonded water molecules than its presence in a buffer solution. Furthermore, the studies demonstrate that phycobiliproteins films modulate their electrical conductivity within their different conformation states. Researchers speculate that the electrical conductance variation could originate from the chemical alteration of cysteine-conjugated bilin chromophores to protein and the electrostatic environment around the chromophores.
The research explores the photochemical properties and electrical transport efficiency of phycobiliproteins (PBPs) films. In addition, it investigates the optoelectronics functionality of PBPs films by studying electron transport behavior across the protein films under a dark state and white light illumination. The researchers proposed to develop a photodetector with the protein film in the future.
- Published in Biology News, Departmental News, News, Physics News, Research News
Metaheuristics attribute selection model for efficient diagnosis of chronic disorders
The technological advancements in the medical domain have aided in the effective collection of data such as personal information, clinical history, and disease symptoms of patients. However, the accumulation of massive quantity of data may cause errors in the diagnosis of the disease. A chronic disease dataset may be comprised of numerous symptoms and attributes where not all of them are of equal importance in disease diagnosis. A few of those attributes may be less relevant or redundant.
Through her research, Dr Priyanka from the Department of Computer Science and Engineering proposes metaheuristics driven attribute optimization techniques that can be implemented in optimizing chronic disease datasets to achieve optimal efficiency in disease risk prediction which can help in proper medical diagnosis. Her paper titled “A Decisive Metaheuristics Attribute Selector Enabled Combined Unsupervised-Supervised Model for Chronic Disease Risks Assessment” was published in the Q1 journal Computational Intelligence and Neuroscience.
This research can be used to develop a decision support system to assist medical experts in the effective analysis of chronic diseases in a cost-effective manner. The system model may be used to assist medical experts in the efficient diagnosis of chronic disease risks. In future, the research study can be further enhanced to validate the model on more complex heterogeneous datasets with varying sizes and structures. Also, deep learning methods can be employed using image-based real-time datasets.
Abstract of the Research
Advanced predictive analytics coupled with an effective attribute selection method plays a pivotal role in precise assessment of chronic disorders risks in patients. In this paper, a novel buffer enabled heuristic a Memory based Metaheuristics Attribute Selection (MMAS) model is proposed, which performs local neighbourhood search for optimizing chronic disorders data. Heart disease, breast cancer, diabetes and hepatitis are the datasets used in the research. Upon implementation of the model, a mean accuracy of 94.5% using MMAS was recorded and it dropped to 93.5% if clustering was not used. The average precision, recall and f-score metric computed were 96.05%, 94.07% and 95.06% respectively. The model also has a least latency of 0.8 sec. Thus it is demonstrated that chronic disease diagnosis can be significantly improved by heuristics based attribute selection coupled with clustering followed by classification.
Figure 1: The proposed Metaheuristics attribute selector based classification model for chronic disorders detection
Figure 2: Accuracy analysis of MMAS method on different disease datasets
- Published in Computer Science News, Departmental News, News, Research News
Ultra-stable perovskite nanocrystals for light-emitting applications
Cesium lead halide perovskite nanocrystals (PNCs) belong to the flourishing research area in the field of photovoltaic and optoelectronic applications because of their excellent optical and electronic properties. Mainly, Cesium lead bromide (CsPbBr3) NCs with bright green photoluminescence (PL) and narrow full-width at half-maximum (FWHM) of <25 nm are the most desirable for television displays and green-emitting LEDs. However, challenges with respect to CsPbBr3 PNCs‘ stability, limit their usage in practical applications. The recent findings of Dr Nimai Mishra and his research team assert that surface passivation with an additional ligand could be an excellent, easy, and facile approach to enhancing the photoluminescence and stability of PNCs.
Dr Nimai Mishra, Assistant Professor, Department of Chemistry, along with his research group comprising of students pursuing PhD under him, Dr V G Vasavi Dutt, Mr Syed Akhil, Mr Rahul Singh, and Mr Manoj Palabathuni have published their research article titled “Year-Long Stability and Near-Unity Photoluminescence Quantum Yield of CsPbBr3 Perovskite Nanocrystals by Benzoic Acid Post-treatment“ in The Journal of Physical Chemistry C (A Q1 journal published by ‘The American Chemical Society’) having an impact factor of ~4.2.
In this article, the research group addresses the stability issues of green-emitting CsPbBr3 PNCs with simple post-treatment using benzoic acid (BA). A remarkable improvement in PLQY from 69.8% to 97% (near unity) was observed in benzoic acid-treated CsPbBr3 PNCs. The effective surface passivation by benzoic acid is also apparent from PL decay profiles of BA-CsPbBr3 PNCs. The long-term ambient stability and stability against ethanol of BA-CsPbBr3 PNCs are also well presented in the research. The PL intensity of untreated CsPbBr3 PNCs is completely lost within five months since the synthesis date, while ̴ 65% of initial PL intensity is preserved for BA-CsPbBr3 PNCs even after one year.
Furthermore, BA-CsPbBr3 PNCs exhibits excellent photo-stability where 36% of PL is retained while PL is completely quenched when the PNCs are exposed to 24 hours of continuous UV irradiation. Importantly, BA-CsPbBr3 PNCs show excellent stability against ethanol treatment as well. Finally, green, emitting diodes using BA-CsPbBr3 PNCs are fabricated by drop-casting NCs onto blue-emitting LED lights. Thus a simple benzoic acid posttreatment further presents the scope of use of these materials display technologies.
- Published in Chemistry-news, Departmental News, News, Research News
Hatchlab incubates student venture Amruthik Private Ltd
Empowering and Enabling startup entrepreneurs
A personal incident motivated Jithin Peram, final year Computer Science Engineering student, to start Amruthik Pvt. Ltd, a company which supplies customised food to various hospitals based on the specific needs of the patients. Various doctors and hospitals have appreciated this customisation of food as per the need. Patients are satisfied as they do not have to take the generic food given by the hospital canteen now. Instead, they have the option to have a very specific diet prescribed by certified dieticians.
The motivation behind the launch of Amruthik is quite inspirational. Jithin’s grandfather passed away due to corona. While his grandfather was suffering with Covid-19 and was admitted in hospital, Jithin was preparing for viva practicals. On hearing the news, he was shattered and it struck him how quickly everything can change around us. Since Jithin was not able to do small things such as taking lunch to his grandfather or standing next to him for moral support; With Amruthik, Jithin dreams of being there for people who need moral support and care in their hospital beds “This makes me happy, and I believe this kind of support is something everyone deserves”, says Jithin on a happy note.
Five years from now, Jithin envisions himself supporting, helping and standing by millions of people who need such services. He believes in putting smiles on faces and wants to see the impressive growth of his company.
Let’s see what Jithin says
As an engineering student, I would have never known the opportunities I have, even with the idea to build my company I would have been lost without proper guidance The Hatchlab Research Centre has given me guidance and a foundation that I can rely upon building my company.
I am thankful for the immense support I got from the faculty and the guidance provided by SRM AP, I especially thank Mr Udayan Bakshi for mentoring me and sharing his experiences with me.
- Published in Blog, IDEA NEWS, Innovation, News, Student Startups, Students Achievements