A5079049057- Electrocatalysts for Energy Conversion
- Advanced Photocatalysis Techniques
- Supercapacitor Materials and Fabrication
- Advanced battery technologies research
- MXene and MAX Phase Materials
- Gas Sensing Nanomaterials and Sensors
- Fuel Cells and Related Materials
- Advancements in Battery Materials
- ZnO doping and properties
- Analytical Chemistry and Sensors
- Luminescence Properties of Advanced Materials
- Catalytic Processes in Materials Science
- Copper-based nanomaterials and applications
- Advanced Chemical Sensor Technologies
- Perovskite Materials and Applications
- TiO2 Photocatalysis and Solar Cells
- Quantum Dots Synthesis And Properties
- Ferroelectric and Piezoelectric Materials
- Nanomaterials for catalytic reactions
- Machine Learning in Materials Science
- Electrochemical Analysis and Applications
- Ga2O3 and related materials
- Electronic and Structural Properties of Oxides
- Semiconductor materials and devices
- Multiferroics and related materials
Indian Institute of Technology Madras
2016-2025
Cancer Institute (WIA)
2024
National Institute of Solar Energy
2019-2021
Ningbo Institute of Industrial Technology
2020
Chinese Academy of Sciences
2020
Sri Ramakrishna Institute of Paramedical Sciences
2019
Indian Institute of Science Bangalore
2013-2015
Bangalore University
2014-2015
Liaoning Shihua University
2015
University of Pennsylvania
2013
New multicomponent equiatomic rare earth oxides (ME-REOs) containing 3-7 elements (Ce, Gd, La, Nd, Pr, Sm and Y) in proportions are synthesized using nebulized spray pyrolysis. All the systems crystallized as a phase pure fluorite type (Fm3[combining macron]m) structure spite of high chemical complexity. A nominal increase lattice parameter compared to CeO2 is observed all ME-REOs. X-ray photoelectron spectroscopy performed on ME-REOs confirmed that constituent present 3+ oxidation state,...
Atomically dispersed catalysts, with maximized atom utilization of expensive metal components and relatively stable ligand structures, offer high reactivity selectivity. However, the formation atomic-scale metals without aggregation remains a formidable challenge due to thermodynamic stabilization driving forces. Here, top-down process is presented that starts from iron nanoparticles, using dual-metal interbonds (RhFe bonding) as chemical facilitator spontaneously convert Fe nanoparticles...
Abstract Photocatalysis is a promising and convenient strategy to convert solar energy into chemical for various fields. However, photocatalysis still suffers from low conversion efficiency. Developing state of the art photocatalysts with high efficiency cost huge challenge. Transition metal nitrides (TMNs) as class metallic interstitial compounds have attracted significant attention in photocatalytic applications. In fact, TMNs exhibit multifunctional properties systems. This review first...
An efficient and robust metal nitride electrocatalyst with the best performance to date for high throughput hydrogen production from seawater.
Abstract Compared to traditional modulation by metal cations doping, oxyanions offer a higher possibility of mediating the performance electrocatalysts toward oxygen evolution reaction (OER) due their special polyanion configurations and large electronegativity. However, mechanism rules mediation remain poorly understood. Herein, an in situ electrochemical oxyanion (NO 3 − , PO 4 3− SO 2− or SeO ) steering strategy study variation OER for transition‐metal (TM = Ni, Fe, Co) hydroxide is...
There has been a recent paradigm shift in the computer animation industry with an increasing use of pre-recorded motion for animating virtual characters. A fundamental requirement to using capture data is efficient method indexing and retrieving motions. In this paper, we propose flexible, searching arbitrarily complex motions large databases. Motions are encoded keys which represent wide array structural, geometric and, dynamic features human motion. Keys provide representative search space...
Abstract Nitrogen-doped carbon materials with a large specific surface area, high conductivity, and adjustable microstructures have many prospects for energy-related applications. This is especially true N-doped nanocarbons used in the electrocatalytic oxygen reduction reaction (ORR) supercapacitors. Here, we report low-cost, environmentally friendly, large-scale mechanochemical method of preparing porous carbons (NPCs) hierarchical micro-mesopores area via ball-milling polymerization...
The oxygen evolution reaction (OER) is key to renewable energy technologies such as water electrolysis and metal-air batteries. However, the multiple steps associated with proton-coupled electron transfer result in sluggish OER kinetics catalysts are required. Here we demonstrate that a novel nitride, Ni2 Mo3 N, highly active catalyst outperforms benchmark material RuO2 . N exhibits current density of 10 mA cm-2 at nominal overpotential 270 mV 0.1 m KOH outstanding catalytic cyclability...
Abstract Semiconducting metal oxides (SMOXs) are used widely for gas sensors. However, the effect of ambient humidity on baseline and sensitivity chemiresistors is still a largely unsolved problem, reducing sensor accuracy causing complications calibrations. Presented here general strategy to overcome water‐sensitivity issues by coating SMOXs with hydrophobic polymer separated metal–organic framework (MOF) layer that preserves SMOX surface serves gas‐selective function. Sensor devices using...
•Porous Co3Mo3N can act as a multifunctional electrocatalyst for OER, ORR, and HER•Co3Mo3N performs better than precious metal catalysts•Cobalt oxide-rich activation surface layer is shown to aid OER activity•Better ORR HER performance of due Co Mo d-states Efficient catalysts are required both oxidative reductive reactions hydrogen oxygen in sustainable energy conversion devices. However, current metal-based electrocatalysts do not perform well across the full range reported all complex...
A material's electronic properties and technological utility depend on its band gap value the nature of (i.e. direct or indirect). This gaps is notoriously difficult to compute from first principles. In fact it computationally intense approximate also rather time consuming. Hence prediction represents a challenging problem. Machine learning based approach offers promising efficient means address this Here we predict for perovskite oxides (ABO3) with elemental composition, ionic radius,...