Results 41 to 50 of about 8,218,575 (213)

Group Contribution Revisited: The Enthalpy of Formation of Organic Compounds with “Chemical Accuracy” Part V

Applied Sciences
Group Contribution (GC) methods to predict thermochemical properties are eminently important in chemical process design. Following our earlier work in which a Group Contribution (GC) model was presented to account for the gas-phase heat of formation of ...
Robert J. Meier, Paul R. Rablen
doaj   +1 more source

Physico-chemical characteristics of PfGCS1-SAPN.

, 2022
Physico-chemical characteristics of PfGCS1-SAPN.
Akram Abouie Mehrizi (12316882), Farhad Zahedi (4063123), Soroush Sardari (4048096), Iran Alemzadeh (2416912)   +3 more
core   +1 more source

Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement

Advanced Science, EarlyView.
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang, Xinyuan Ke, Andrew Heath, Richard J. Ball, Jiawei Xie, Jinchen Fan, Guisheng Li, Kevin Paine   +7 more
wiley   +1 more source

Soil Inorganic Electron Acceptors and Carbon Substrates Hierarchically Govern Wetland Methanogenesis Temperature Response

Advanced Science, EarlyView.
ABSTRACT Wetlands constitute Earth's largest natural methane (CH4) source, yet projections of their climate feedback remain uncertain due to poorly constrained temperature sensitivity (Q10‐CH4) of microbial methanogenesis. While water table dynamics have been demonstrated to regulate wetland methanogenesis by altering key soil conditions such as ...
Shuying Qiu, Qingfang Jing, Xuhui Zhou, Xiaoxin Sun, Zhenyu Wei, Baizhi Jiang, Hongyang Chen   +6 more
wiley   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Revolutionising Agricultural Sustainability: New ‘Furrow Tillage’ can Mitigate Short‐Term Soil‐to‐Atmosphere CO2 Flux and Promote Soil‐Plant‐Microbe Health

Advanced Science, EarlyView.
Furrow tillage resolves the conventional‐vs.‐no‐tillage trade‐off by simultaneously cutting CO2 efflux to 2.0–3.0 g C m−2 d−1 and unlocking high nutrient availability for the rice rhizosphere. This scalable agronomic solution strengthens soil health, enhances plant physiology, reshapes microbial metabolism, and shifts paddy systems toward a net ...
Arnab Majumdar, Munish Kumar Upadhyay, Argha Ghosh, Rakesh Biswas, Ioly Kotta Loizou, Martin Buck, Mark Tibbett, Biswajit Giri, Debojyoti Moulick, Manoj Kumar Jaiswal, Tarit Roychowdhury   +10 more
wiley   +1 more source

The Plant‐to‐Plant Circular Strategy: Coupling Photodegradation and Phytoremediation With Plant‐Based Nanomaterials for Plastic Degradation

Advanced Science, EarlyView.
Plant‐based nanomaterials derived from alfalfa serve as dual‐function catalysts, coupling photodegradation and phytoremediation to degrade polyethylene under UV‐A light and in soil. The nanomaterials work synergistically with alfalfa and soil microbes, achieving efficient plastic breakdown without trophic transfer.
Haoran Liu, Lena Ciric, Yuheng Wang, Ziru Pei, Manpreet Bhatti   +4 more
wiley   +1 more source

Universal Battery Capacity Degradation Forecasting Driven by Foundation Models Across Diverse Chemistries and Conditions

Advanced Science, EarlyView.
A unified time‐series forecasting framework learns transferable battery capacity‐degradation patterns from 20 heterogeneous datasets spanning chemistries, formats, temperatures, and cycling conditions. A single model delivers competitive predictions on both known and previously unseen datasets, while physics‐guided representation learning improves ...
Joey Chan, Huan Wang, Zhen Chen, Haoyu Pan, Wei Wu, Zirong Wang, Ershun Pan, Min Xie, Lifeng Xi   +8 more
wiley   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

A critical re‐analysis of biochar properties prediction from production parameters and elemental analysis

GCB Bioenergy
Biochar is the product of intentional pyrolysis of organic feedstocks. It is made under controlled conditions in order to achieve desired physico‐chemical characteristics.
Johanne Lebrun Thauront, G. Soja, Hans‐Peter Schmidt, Samuel Abiven   +3 more
semanticscholar   +1 more source