Indian Institute of Technology Ropar

About: Indian Institute of Technology Ropar is a education organization based out in Ropar, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 1014 authors who have published 2878 publications receiving 35715 citations.

Critical-point behavior of a measurement-based quantum heat engine

Abstract: We study how a quantum heat engine performs across the critical value of an external parameter, pertaining to the quantum phase transition. Considering a two-ion system subjected to a magnetic field, we show that the system performs in a quantum Otto cycle above a critical value of the magnetic field, while below such critical point, it does not operate in a heat cycle at all. Moreover, at the critical point, its interaction with an ancillary ion deteriorates the performance of the system as a heat engine. We further show that a strong interaction between the constituent ions of an ion-based system is crucial for it to work in a heat-work cycle, while the coupling to the ancillary system must be minimized.

Multifunctionality Exploration of Ca2FeRuO6: An Efficient Trifunctional Electrocatalyst toward OER/ORR/HER and Photocatalyst for Water Splitting

Abstract: Durable multifunctional electrocatalysts with zero emission and high catalytic activity are desirable for environmentally benign clean energy technologies such as water-splitting devices, fuel cell...

Unsupervised gene selection using biological knowledge : application in sample clustering

Abstract: Classification of biological samples of gene expression data is a basic building block in solving several problems in the field of bioinformatics like cancer and other disease diagnosis and making a proper treatment plan. One big challenge in sample classification is handling large dimensional and redundant gene expression data. To reduce the complexity of handling this high dimensional data, gene/feature selection plays a major role. The current paper explores the use of biological knowledge acquired from Gene Ontology database in selecting the proper subset of genes which can further participate in clustering of samples. The proposed feature selection technique is unsupervised in nature as it does not utilize any class label information in the process of gene selection. At the end, a multi-objective clustering approach is deployed to cluster the available set of samples in the reduced gene space. Reported results show that consideration of biological knowledge in gene selection technique not only reduces the feature space dimensionality in great extent but also improves the accuracy of sample classification. The obtained reduced gene space is validated using strong biological significance tests. In order to prove the supremacy of our proposed gene selection based sample clustering technique, a thorough comparative analysis has also been performed with state-of-the-art techniques.

Stabilization of Cobalt-Polyoxometalate over Poly(ionic liquid) Composites for Efficient Electrocatalytic Water Oxidation

Abstract: The key to unlock a renewable, clean, and energy-dense hydrogen fuel lies in designing an efficient oxygen evolving catalyst exhibiting high activity, stability, and cost-effectiveness. This report addresses an improved activity toward oxygen evolution by a composite of cobalt-polyoxometalate [Co4(H2O)2(PW9O34)2]10– (CoPOM) and an ionic polymer, poly(vinyl butyl imidazolium) (PVIM), in highly alkaline media. PVIM provides a stable platform for CoPOM and acts as a conductive linker between CoPOM and the electrode surface, forming a concrete solid composite, which balances the multinegative charge of CoPOM synergistically. This improved stability and conductivity of CoPOM by PVIM in the PVIM–CoPOM composite performs remarkable electrocatalytic water oxidation with a very low overpotential of 0.20 V and a very high current density of 250 mA/cm2 (at 1.75 V vs RHE) with a turnover frequency (TOF) of 52.8 s–1 in 1 M NaOH.