Results 31 to 40 of about 18,755 (251)

Bifurcation of *COOH Pathway Determines HCOOH Formation in CO2 Electroreduction on Bismuth

Angewandte Chemie, EarlyView.
Driven by the mechanistic debate of Bi‐catalyzed CO2‐to‐HCOOH conversion, ambiguity remains regarding true reaction pathways. To resolve this, we combined constant‐potential AIMD simulations with spectroscopic evidence to analyze the competitive pathways.
Hyun Dong Jung, Jiawei Deng, Yanbo Hua, Kun Jiang, Seoin Back   +4 more
wiley   +2 more sources

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Mechanistic Insight Into the Polymorph‐Dependent Photosalient Effect of a White Light or Two‐Photon Activated Photoreactive Molecular Salt

Angewandte Chemie, EarlyView.
Photocycloaddition in stilbene‐type salt polymorphs exhibit distinct light‐driven responses: OHT‐TI shows a violent photosalient effect under visible and NIR (two‐photon) irradiation, whereas OHT‐TII reacts statically. Packing and computational analysis reveals that shell‐like structures in OHT‐TI frustrate structural relaxation, accumulating explosive
Emanuela Santagata, Francesco Ambrosio, Amedeo Capobianco, Andrea Peluso, Giorgia Rizzi, Stijn Van Cleuvenbergen, Yovan de Coene, Koen Clays, Paolo Pio Mazzeo, Roberto Centore, Fabio Borbone   +10 more
wiley   +2 more sources

An accelerated first-order method for solving SOS relaxations of unconstrained polynomial optimization problems

, 2011
Our interest lies in solving sum of squares (SOS) relaxations of large-scale unconstrained polynomial optimization problems. Because interior-point methods for solving these problems are severely limited by the large-scale, we are motivated to explore ...
Sun, Xu Andy, Freund, Robert Michael, Bertsimas, Dimitris J.   +2 more
core   +1 more source

Nonlinear conjugate gradient methods for unconstrained optimization

, 2020
Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method.
Andrei, Neculai
core   +1 more source

Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors

Advanced Electronic Materials, EarlyView.
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko, Alon Ascoli, Fernando Corinto, Yuriy V. Pershin   +3 more
wiley   +1 more source

Degradation Mechanism of Phosphate‐Based Li‐NASICON Conductors in Alkaline Environment

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
The presence of water in the cathode of a Li‐air battery shifts reactions to produce LiOH, creating a corrosive, alkaline environment. This study investigates the alkaline stability of the common Li‐NASICON solid‐state conductor chemistries through a systematic experimental study combined with computational modeling to understand the degradation ...
Benjamin X. Lam, Zhuohan Li, Tara P. Mishra, Gerbrand Ceder   +3 more
wiley   +1 more source

Second-order mollified derivatives and optimization [PDF]

The class of strongly semicontinuous functions is considered. For these functions the notion of mollified derivatives, introduced by Ermoliev, Norkin and Wets, is extended to the second order.
Rocca Matteo, La Torre Davide, Crespi Giovanni   +2 more
core  

Application of optimization algorithms in the design of a superconducting A.C. generator rotor [PDF]

, 1990
The superconducting a.c. generator is expected to be the optimum choice among a.c. generation systems in future because of its reduced size, high efficiency, high terminal voltage and its contribution to the stability of the power system.
Safi, Sabah K.
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source