Results 141 to 150 of about 2,248,852 (247)

Thermodynamics Optimizes the Physiology of Life

Философия и космология, 2014
Thermodynamics serves as a basis for optimal solutions of the tasks of physiology, which are solved by organisms in the characteristic process of life: evolution, development, homeostasis, and adaptation. It is stated that the quasiequilibrium thermodynamics of quasiclosed complex systems serves as an impetus of evolution, functions, and activities of ...
openaire   +1 more source

Ionic Cocrystal Programming of Spatial Ionic Organization in Carbon Nitrides Enables Highly Efficient H2O2 Photosynthesis

Advanced Materials, EarlyView.
Ionic cocrystal‐programmed ionic organization establishes a general strategy for electrostatic programming in polymeric photocatalysts. ABSTRACT Controlling the spatial organization of ions in polymeric photocatalysts remains a fundamental challenge for optimizing charge transport and catalytic selectivity in solar‐driven hydrogen peroxide (H2O2 ...
Anna Lo Presti, Zahra Hajiahmadi, Sam A. J. Hillman, Mu Xiao, James R. Durrant, Thomas D. Kühne, Christian Mark Pelicano   +6 more
wiley   +1 more source

Exploratory In Silico Evaluation of Microencapsulation Matrices for Indomethacin. [PDF]

Molecules
Vargas Rubio KI, Delgado E, Cabrales-Arellano P, Gamboa Gómez CI, Rojas-Contreras JA, Guerrero Rivera R, Martínez Gómez VJ, Cordero Soto IN, Contreras Hernández MG, Reyes Jáquez D.   +9 more
europepmc   +1 more source

1T‐to‐2H Phase Evolution During Epitaxial Growth of Transition Metal Dichalcogenides

Advanced Materials, EarlyView.
During MOCVD growth of MoS2 and WSe2, a transient metallic 1T phase emerges in early, edge‐rich, chalcogen‐deficient domains and declines as the films ultimately coalesce as 2H material. Together, experiments and ReaxFF simulations link domain size, edge stoichiometry, and vacancies to this evolution.
Andrew R. Graves, Yiru Zhu, Matin Salimi Irdmusa, Nadire Nayir, Thomas V. Mc Knight, Chen Chen, Ke Wang, Adri C. T. van Duin, Joan M. Redwing   +8 more
wiley   +1 more source

Efficient zinc ion biosorption on the biomass of <i>Ericaria selaginoides</i> algae following response surface methodology optimization: uptake behaviors and mechanisms. [PDF]

PeerJ
Fawzy MA, Alharbi M, Sonbol H, Fouad MR, Sheikh S, Hassan SHA.   +5 more
europepmc   +1 more source

Descriptor‐Informed Screening of Interface‐Active Molecules for Efficient Magnesium Metal Anodes

Advanced Materials, EarlyView.
A descriptor‐informed molecular screening strategy identifies 4‐bromo‐N, N‐dimethylaniline (BrNNA) as an interface‐active electrolyte component that enables fast Mg stripping/plating in Mg(TFSI)2‐based electrolytes. By simultaneously regulating Mg2+ solvation and interphase formation, the BrNNA‐containing electrolyte delivers activation‐free Mg ...
Hao Xu, Yue Li, Tian Xie, Arafat Hossain Khan, Fengzhan Sun, Zhao Li, Lingyue Liu, Zhaohui Yang, Xinlong Xie, Huayu Qiu, Quanquan Guo, Tian Sun, Xingyuan Chu, Jingwei Du, Jianxin Zou, Xinliang Feng, Minghao Yu   +16 more
wiley   +1 more source

In Situ Formation of a Highly Selective Nickel Single Atom Catalyst for Electrochemical CO2 Reduction to CO

Advanced Materials, EarlyView.
Development of a novel method for synthesizing Ni single atom catalysts for highly selective electrochemical CO2 reduction in situ. This catalyst achieves 100% selectivity for CO and is formed in an industrially relevant cell architecture. Using post‐mortem XRD, STEM, and EDS and operando XAS, the identity of the active site and the mechanism behind ...
Ian Street, Venkata Sai Sriram Mosali, Noah Sandberg, Fengyuan Shi, Deborah Myers, William E. Mustain   +5 more
wiley   +1 more source

Differentiable Thermodynamic Phase-Equilibria for Machine Learning. [PDF]

J Chem Inf Model
Ben Hicham KK, Ascani M, Rittig JG, Mitsos A.   +3 more
europepmc   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

POMs-GibbsNet: A Deep Neural Network for the Prediction of Thermodynamic Parameters of Polyoxometalates. [PDF]

J Comput Chem
Buils J, Bo C, Balcells D.
europepmc   +1 more source