Results 121 to 130 of about 462 (258)

An Indicator‐Based Decision Framework for Circular Bioeconomy Transition in the Steel Industry: Integrating Multiphase Learning and Cooperative Game Modelling

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari, Mohammadreza Sadeghi‐Moghadam, Hannan Amoozad Mahdiraji   +2 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Molecular Dynamics Simulations of γ‐Belite(010)–Water Interfaces With High‐Dimensional Neural Network Potentials

Chemistry – A European Journal, EarlyView.
Several γ$\gamma$‐belite(010)–water interfaces have been studied by molecular dynamics simulations using a high‐dimensional neural network potential. The structure and reactivity of interfacial water have been analyzed and two types of surface defects could be identified, which indicate the possible existence of a wide range of surface structures ...
Bernadeta Prus, Jörg Behler
wiley   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source

A Meta‐Analytic Review of Board Characteristics and Carbon Emission Disclosure: The Moderating Effect of Contextual Factors

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT The relationship between board governance and corporate carbon emission disclosure remains persistently inconsistent across the empirical literature, despite decades of accumulated evidence. Drawing on agency, stakeholder, legitimacy, institutional, and upper echelons perspectives within a single analytical framework, we conduct a three‐level ...
Mohamed Hegazy, Diego Prior, Mahmoud Zarea   +2 more
wiley   +1 more source

Toward a Paradigm Shift in Low‐Temperature SCR Catalyst Design: Defect Engineering and Data‐Driven Integration

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This work systematically reviews the key factors influencing the performance of low‐temperature NH3‐SCR. The mechanism and challenges of defect engineering strategies, such as oxygen vacancies, heteroatom doping, crystal facet exposure, and surface reconstruction, in controlling both activity and selectivity were analyzed.
Rongrong Kan, Pinjing He, Fan Lü, Hua Zhang   +3 more
wiley   +1 more source

EStore: A User-Friendly Encrypted Storage Scheme for Distributed File Systems. [PDF]

Sensors (Basel), 2023
Chen Y, Dong G, Xu C, Hao Y, Zhao Y.
europepmc   +1 more source

Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration

FlexMat, EarlyView.
Abstract Soft robots, engineered from highly compliant materials, offer superior adaptability and safety in unstructured environments compared to their rigid counterparts. Recent advancements, fueled by bio‐inspiration and material programmability, have led to the rapid co‐evolution of their core modules: actuation, sensing, protection, energy, and ...
Qiulei Liu, Zicao Peng, Chong Sun, Haitao Yang   +3 more
wiley   +1 more source

Polymer informatics: Integrating data‐driven strategies, advanced machine learning, and automated synthesis for next‐generation polymer design

InfoScience, EarlyView.
Designing new polymers for applications such as sustainable plastics, biomaterials, and 3D printing has traditionally been slow and expensive, relying heavily on trial‐and‐error experiments. This review shows how polymer informatics—the integration of large polymer databases, machine‐learning models, and automated robotic synthesis—enables fast ...
Md. Saiful Islam, Tamanna Hoque, Junied Islam Shuvo, Sheta Roy Tori, Sadit Bihongo Malitha, Md. Zahangir Alam, A. M. Sarwaruddin Chowdhury   +6 more
wiley   +1 more source