Results 71 to 80 of about 31,740 (265)

Computational Thermodynamics

, 2021
Diese Arbeit befasst sich mit theoretischen Konzepten der phänomenologischen und statistischen Thermodynamik und deren numerischer Umsetzung. Das Hauptziel dieser Arbeit ist es, Arbeitsabläufe für die akurate Beschreibung von thermodynamischen Eigenschaften von Molekülen und Festkörpern zur Verfügung zu stellen. Der während dieser Arbeit entwickelte Cp
openaire   +1 more source

Quantum computers, quantum computing, and quantum thermodynamics

Frontiers in Quantum Science and Technology
Quantum thermodynamics aims to extend standard thermodynamics and non-equilibrium statistical physics to systems with sizes well below the thermodynamic limit. It is a rapidly evolving research field that promises to change our understanding of the foundations of physics, while enabling the discovery of novel thermodynamic techniques and applications ...
Fabrizio Cleri, Fabrizio Cleri
openaire   +4 more sources

Monolithic Oxidation Enables Ultrathin Vertically Graded Tantalum Oxide for Low‐Voltage, Low‐Variability Memristive Switching

Advanced Functional Materials, EarlyView.
Monolithic UV‐ozone oxidation of Ta forms an ultrathin Ta2O5/TaOx bilayer enabling resistive switching with a vertical defect gradient. A stoichiometric surface layer over an oxygen‐deficient sublayer promotes localized filament nucleation near the top interface, enabling low‐voltage operation, and reduced cycle‐to‐cycle variability.
Seunghoon Yang, Dong Hyun Lee, Conan Weiland, Won‐Il Lee, Kim Kisslinger, Mingzhao Liu, Aswin kumar Anbalagan, Xiao Tong, Soumyajit Mandal, Nikhil Tiwale, Houk Jang, Chang‐Yong Nam   +11 more
wiley   +1 more source

Computational thermodynamics and microstructure simulations to understand the role of grain boundary phase in Nd-Fe-B hard magnets. [PDF]

Sci Technol Adv Mater, 2021
Koyama T, Tsukada Y, Abe T.
europepmc   +1 more source

Thermodynamic computing system for AI applications

Nature Communications
Recent breakthroughs in artificial intelligence (AI) algorithms have highlighted the need for novel computing hardware in order to truly unlock the potential for AI. Physics-based hardware, such as thermodynamic computing, has the potential to provide a fast, low-power means to accelerate AI primitives, especially generative AI and probabilistic AI. In
Denis Melanson, Mohammad Abu Khater, Maxwell Aifer, Kaelan Donatella, Max Hunter Gordon, Thomas Ahle, Gavin Crooks, Antonio J. Martinez, Faris Sbahi, Patrick J. Coles   +9 more
openaire   +4 more sources

Functionalizing Micro‐to‐Mesoscopic Electrode Architectures for Regulating Electron Transfer Behaviors in Electrocatalysis

Advanced Functional Materials, EarlyView.
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao, Jiaojiao Zhang, Shideng Yuan, Xinmeng Yu, Keming Wan, Xiaoguang Duan, Zhining Wang   +6 more
wiley   +1 more source

A Lattice Monte-Carlo Approach to Two Flavors PNJL Model

Jurnal Ilmu Dasar
We extend the Monte Carlo PNJL framework by introducing nearest-neighbor interactions between fluctuating sub-volumes, resulting in a spatially structured lattice model.
M. S. Z. Raihan P. H., Bintoro A. Subagyo, Agus Purwanto   +2 more
doaj   +1 more source

Electrostatic Superlattices Beyond 1:1 Stoichiometry

Advanced Functional Materials, EarlyView.
Polymer‐mediated charge regulation drives two hierarchical routes to higher‐stoichiometry nanoparticle superlattices. Tuning the polymer's molecular weight promotes progressive interstitial filling, transforming ZnS into the fully occupied CaF2${\rm CaF}_2$ lattice. Exchanging polymer assignment between large and small nanoparticles instead breaks CsCl
Binay P. Nayak, Prapti Kakkar, Wesley P. Korba, Honghu Zhang, Wenjie Wang, Surya K. Mallapragada, Alex Travesset, David Vaknin   +7 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source

Designing Vanadium‐Based Oxide Electrocatalysts for Water Splitting: Experimental and Mechanistic Insights with Machine Learning

Advanced Functional Materials, EarlyView.
This review establishes structure‐property‐mechanism relationships across six modification strategies for V‐based oxide water‐splitting electrocatalysts: lattice engineering, heteroatom doping, interface engineering, carbon‐based hybridization, morphology engineering, and surface reconstruction and pre‐catalyst design, where dissolution is reframed as ...
Youness El Issmaeli, Amina Lahrichi, Hoje Chun, Rafael Gómez‐Bombarelli, Bruno G. Pollet   +4 more
wiley   +1 more source