Results 181 to 190 of about 43,983 (273)

Innovation Pathways to Carbon Efficiency: Disentangling the Effects of AI, R&D, and Clean Energy Blessings on U.S. Environmental Sustainability

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT The United States (U.S.) faces challenges in achieving its ambitious net‐zero carbon emissions target by 2050, with current emissions having fallen by less than 1% in 2024. Despite an investment of $500 billion in low‐carbon resources while holding the second‐largest green technology patent portfolio globally, it is further imperative to ...
Md Zubair Ahmad   +5 more
wiley   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

open access: yesCarbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao   +6 more
wiley   +1 more source

Primary Psychoses Among Sentenced Prisoners in Finland

open access: yesCriminal Behaviour and Mental Health, EarlyView.
ABSTRACT Background Recent studies suggest an increased prevalence of primary psychotic disorders among sentenced prisoners in Finland. Exploring the extent and correlates of lifetime primary psychoses through high‐quality data is crucial for early identification and effective interventions within correctional settings.
Petra Laivonen   +2 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

open access: yesCarbon 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   +4 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

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