Results 191 to 200 of about 30,083 (262)

Discreteness, Computation, and Rules of Life for Self-Organization Dynamics Beyond Equilibrium. [PDF]

Newton
Youk H.
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Dynamic Etching‐Induced Cl‐Terminated Ti3C2Clx/Ti3ZnC2 Heterostructure for Ammonia Electrosynthesis and Zinc‐Nitrogen Batteries

Advanced Science, EarlyView.
A stable Ti3C2Clx/Ti3ZnC2 heterostructure, fabricated by dynamic etching, exhibits outstanding electrocatalytic NRR activity (NH3 yield: 20.1 µg h−1 mg−1, FE: 38.1%) in alkaline media. The corresponding Zn‐N2 battery achieves a peak power density of 36.5 µW cm−2 and an NH3 yield of 13.1 µg h−1 mg−1, providing an advanced strategy for NH3 and ...
Yu Wang, Ying Sun, Liqun Ye, Jichi Liu, Hui Li, Yang Fu, Fengzhan Sun, Jieshan Qiu, Chang Yu, Tianyi Ma   +9 more
wiley   +1 more source

Design of a Cylindrical Thermal Rotary Concentrator Based on Transformation Thermodynamics. [PDF]

Materials (Basel)
Xia G, He X, Jia Y, Zhu Y, Tian Z.
europepmc   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Thermodynamic Principles Behind Mechanisms and Reactivities: Hydrogen Atom Abstraction and Related Radical Reactions. [PDF]

Acc Chem Res
Srnec M, Bím D, Maldonado-Domínguez M, Wojdyla Z, Fučík R.   +4 more
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Proton, Electron, and Hydrogen-Atom Transfer Thermodynamics of the Metal-Organic Framework, Ti-MIL-125, Are Intrinsically Correlated to the Structural Disorder. [PDF]

J Am Chem Soc
Altınçekiç NG, Lander CW, Yu J, Roslend A, Shao Y, Noh H.   +5 more
europepmc   +1 more source

Engineering of Crystal and Domain Structures in Epitaxial Y:HfO2 Thin Films by YSZ Substrate Miscut

Advanced Science, EarlyView.
We investigate how YSZ substrate miscut influences crystal structure and domain formation in epitaxial Y‐doped HfO2 thin films. Using magnetron sputtering, high‐resolution X‐ray diffraction, atomic‐resolution scanning transmission electron microscopy, and first‐principles calculations, we systematically examine the characteristics of thickness‐ and ...
Jun Young Lee, Hyung‐Jin Choi, Kun Hee Ye, Haneul Choi, Byeong‐hyeon Lee, Min‐Seok Kim, Dong‐Hun Han, June Hyuk Lee, Sung Ok Won, Tae Heon Kim, Hye Jung Chang, Jung‐Hae Choi, Seung‐Hyub Baek   +12 more
wiley   +1 more source

Machine learning for RNA secondary structure prediction: a review of current methods and challenges. [PDF]

RNA
Sacco G, Bussi G, Sanguinetti G.
europepmc   +1 more source