Results 161 to 170 of about 13,990 (264)

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Enhancing Gypsum Plaster with Encapsulated Fischer-Tropsch Paraffin Wax as a Phase-Change Additive for Broad-Range Thermal Energy Storage. [PDF]

Polymers (Basel)
Voronin D, Smirnova E, Demikhova N, Sayfutdinova A, Kopitsyn D, Fakhrullin R, Vinokurov V, Stavitskaya A.   +7 more
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Heat Storage/Release in Direct-Contact Heat Exchanger for Latent Heat Storage

Proceedings of National Heat Transfer Symposium, 2011
Nomura, Takahiro, Tsubota, Masakatsu, Oya, Teppei, Okinaka, Noriyuki, Akiyama, Tomohiro   +4 more
openaire   +1 more source

Magnetic Microcapsules with Carbon Nanotubes-Fe₃O₄ for Enhanced Solar Thermal Energy Storage. [PDF]

ACS Omega
Huang M, Yin L, Ren H, Zhang Y, Liang Y, Liao S, Huang Y.   +6 more
europepmc   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Graphene-silver hybrid nanoparticle embedded phase change materials for enhanced thermal management of lithium-ion batteries. [PDF]

RSC Adv
Akshay B, Seyas Mumthas FS, Mohan M, Bhuvanachandran Rajeswari V, Ravikumar C.   +4 more
europepmc   +1 more source

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

A Wood Plasticine With Controlled Phase-Change Behavior and Malleability for Energy-Closed-Loop and Conformally Adaptive Thermal Management. [PDF]

Adv Sci (Weinh)
Zhou J, Liu Y, Qiao L, Gu Y, Yao T, Zhang W, Wang F, Li Y, Ji X, Kong L, Yang H, Xiao Y, Wang C.   +12 more
europepmc   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source