Results 51 to 60 of about 10,196 (151)
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This work presents a bio‐inspired computing framework for Parkinson's disease analog recognition using electroencephalogram signals. Temporally encoded EEG features stimulate a mycelium‐inspired memristive reservoir, where disease‐related patterns emerge through physical spatiotemporal dynamics.
Ioannis K. Chatzipaschalis +5 more
wiley +1 more source
Topological Learning for the Classification of Disorder: An Application to the Design of Metasurfaces. [PDF]
ACS Nano, 2023 Madeleine T +8 more
europepmc +1 more source
Thermal Conductivity and Tunable Thermal Anisotropy of Magnetic CrSBr Monolayer
Advanced Physics Research, EarlyView.Top (left) and side view of single‐layer CrSBr (right). Phonon transport is strongly anisotropic, with a lattice thermal conductivity along the a‐lattice vector which is almost twice the one along the b‐vector (κxx$\kappa _{xx}$ = 1.8 κyy$\kappa _{yy}$). ABSTRACT We present first‐principles calculations of the thermal conductivity, κ${\bm \kappa }$, of
Marta Loletti +4 more
wiley +1 more source
Carbon Energy, EarlyView.ABSTRACT Biochar has emerged as a useful and adaptable source of carbon for supercapacitor electrodes. Its value comes from the way biomass chemistry, thermal conversion, and activation conditions shape the resulting pore network, surface groups, and degree of carbon ordering.
Soumen Mandal +6 more
wiley +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
Carbon Energy, EarlyView.Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su +4 more
wiley +1 more source
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
Communications on Pure and Applied Mathematics, EarlyView.ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.Nitrogen/sulfur co‐doping optimizes the electron and spatial structure of biomass‐derived hard carbon, and the anode demonstrates superior long‐term cycling stability over 2000 cycles, validating an improved “adsorption‐intercalation‐pore filling” mechanism.
Qian Long +8 more
wiley +1 more source
Perovskite Topological Lasers: A Brand New Combination. [PDF]
Nanomaterials (Basel), 2023 Wang L, Wu L, Pan Y.
europepmc +1 more source