Results 161 to 170 of about 1,416 (264)

Integrating Recycling and Emission Reduction: A Business Strategy Analysis With Multi‐Objective Mixed‐Integer Linear Programming Framework for Optimising Sustainable Closed‐Loop Supply Chain Network Design

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT This research develops an integrated mixed‐integer linear programming (MILP) model for closed‐loop supply chain network design that optimises competing economic and environmental objectives including profit maximisation, supplier quality improvement and CO2 emission reduction.
Reza Eslamipoor
wiley   +1 more source

Whose Sustainability Counts? Board Governance, ESG Ratings, and Sustainable Development Goals: Evidence on the ESG–SDG Wedge

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Institutional investors increasingly rely on ESG ratings to evaluate financially material sustainability risks, while governments promote corporate alignment with the United Nations Sustainable Development Goals (SDGs). Because these frameworks differ substantially in capital market salience and monitoring intensity, board oversight may not ...
Mohamed Hegazy   +2 more
wiley   +1 more source

Connectivity concepts in neuronal network modeling. [PDF]

open access: yesPLoS Comput Biol, 2022
Senk J   +9 more
europepmc   +1 more source

Engineering Biochar‐Derived Functional Materials for High‐Performance Supercapacitors: Design Principles, Mechanisms, and Scalable Strategies

open access: yesCarbon Energy, EarlyView.
ABSTRACT Biochar has emerged as a useful and adaptable source of carbon for supercapacitor electrodes. Its value comes from the way biomass chemistry, thermal conversion, and activation conditions shape the resulting pore network, surface groups, and degree of carbon ordering.
Soumen Mandal   +6 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

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