Catalysis in the digital age: Unlocking the power of data with machine learning

BM Abraham, MV Jyothirmai, P Sinha… - Wiley …, 2024 - Wiley Online Library
The design and discovery of new and improved catalysts are driving forces for accelerating
scientific and technological innovations in the fields of energy conversion, environmental …

Recent advances in heteroatom-doped/hierarchically porous carbon materials: Synthesis, design and potential applications

A Hayat, M Sohail, AYA Alzahrani, H Ali… - Progress in Materials …, 2024 - Elsevier
Heteroatom-doped porous carbon or hierarchically porous carbon materials (HPCMs) have
been widely used in several fields such as adsorption and separation, organic catalytic …

From characterization to discovery: artificial intelligence, machine learning and high-throughput experiments for heterogeneous catalyst design

J Benavides-Hernández, F Dumeignil - ACS Catalysis, 2024 - ACS Publications
This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …

Identification of acetylcholinesterase inhibitors from traditional medicinal plants for Alzheimer's disease using in silico and machine learning approaches

MT Islam, M Aktaruzzaman, A Saif, MMH Sourov… - RSC …, 2024 - pubs.rsc.org
Acetylcholinesterase (AChE) holds significance in Alzheimer's disease (AD), where
cognitive impairment correlates with insufficient acetylcholine levels. AChE's role involves …

InVO4-Decorated Ti3C2 MXene for Efficient Photocatalytic Hydrogen Evolution

SJ Kalita, S Varangane, P Basyach… - … Applied Materials & …, 2024 - ACS Publications
The generation of hydrogen through photocatalysis is a fascinating technology for
addressing environmental concerns and the energy crisis. Nevertheless, the quest for cost …

Machine learning driven advancements in catalysis for predicting hydrogen evolution reaction activity

P Sinha, MV Jyothirmai, BM Abraham… - Materials Chemistry and …, 2024 - Elsevier
In the field of catalysis research, the emergence of machine learning (ML) has triggered a
significant transformation, revolutionizing our methodologies for exploring and …

Emerging ZnO Semiconductors for Photocatalytic CO2 Reduction to Methanol

SD Kshirsagar, SP Shelake, B Biswas, K Ramesh… - Small, 2024 - Wiley Online Library
Carbon recycling is poised to emerge as a prominent trend for mitigating severe climate
change and meeting the rising demand for energy. Converting carbon dioxide (CO2) into …

Integrating experimental and machine learning approaches for predictive analysis of photocatalytic hydrogen evolution using Cu/g-C3N4

B Arabacı, R Bakır, C Orak, A Yüksel - Renewable Energy, 2024 - Elsevier
This study addresses environmental issues like global warming and wastewater generation
by exploring waste-to-energy strategies that produce renewable hydrogen and treat …

[HTML][HTML] Elucidating the local structure and electronic properties of a highly active overall alkaline water splitting NixCo1-xO/hollow carbon sphere catalyst

V Mashindi, MW Terban, DM Meira, BD Moreno… - International Journal of …, 2024 - Elsevier
A Ni x Co 1-x O/HCS catalyst with superior water-splitting is presented. High water-splitting
reaction kinetics and enhanced durability were observed. The structure-function relationship …

The g-C3N4/CdO heterojunction as an efficient photo-electron catalyst for hydrogen production

Y Shen, P Yuan, Z Yuan, Z Cui, D Ma, F Cheng… - Physica B: Condensed …, 2024 - Elsevier
The electronic, optical, and photo-electro catalytic properties of the gC 3 N 4/CdO
(CGN/CdO) heterojunction are studied by Density Functional Theory (DFT) calculations. The …