Results 71 to 80 of about 551 (192)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Spontaneous emergence of computation in network cascades. [PDF]

open access: yesSci Rep, 2022
Wilkerson G, Moschoyiannis S, Jensen HJ.
europepmc   +1 more source

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

open access: yesAdvanced 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   +19 more
wiley   +1 more source

RALF: an adaptive reinforcement learning framework for teaching dyslexic students. [PDF]

open access: yesMultimed Tools Appl, 2022
Minoofam SAH   +2 more
europepmc   +1 more source

A Large Scale Multi‐Modal Workflow for Battery Characterization: From Concept to Implementation

open access: yesAdvanced Energy Materials, EarlyView.
Isolated characterization techniques produce independent datasets and single‐property insights. However, progressively more holistic interpretations of battery‐material behavior is needed in the future. Here we demonstrate a coordinated multimodal workflow enabling the correlation of heterogeneous datasets and the construction of multidimensional ...
François Cadiou   +34 more
wiley   +1 more source

Quantum circuits from non-unitary sparse binary matrices. [PDF]

open access: yesSci Rep
Karuppasamy K   +3 more
europepmc   +1 more source

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