Results 71 to 80 of about 26,697 (199)

Computing control invariant sets is easy

, 2017
In this paper we consider the problem of computing control invariant sets for linear controlled systems with constraints on the input and on the states.
Alamir, Mazen, Fiacchini, Mirko
core  

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Self‐Powered Bearing Sensing and Real‐Time Fault Diagnosis Enabled by Non‐Invasive Triboelectric Sensors and Edge AI Acceleration

Advanced Science, EarlyView.
This study achieves the synergistic integration of self‐powered sensing and edge AI acceleration to establish a real‐time fault diagnosis system. The proposed TENG‐based self‐powered bearing sensor (NSE‐TBS) and FPGA‐accelerated edge AI framework fundamentally break through the inherent limitations of conventional monitoring systems, including complex ...
Kehui Zhu, Zhongheng Liu, Xinming Li, Jinrui Zhang, Meng Li, Yiming Guo, Lihua Han, Yanxue Wang   +7 more
wiley   +1 more source

A High‐Throughput Live Imaging Platform to Investigate Circuit‐Dependent Regulation of Circadian Rhythms in Brain Tissue

Advanced Science, EarlyView.
Biological rhythms coordinate physiology, from genes to behavior. Study of circadian rhythms in brain tissue is constrained by limited throughput and spatial and temporal information quality. A new platform for high‐throughput, long‐term multiplexed fluorescent live imaging of circadian rhythms in brain slices is introduced.
Marco Ferrari, Natalie Ness, Julieta Acosta, Marco Brancaccio   +3 more
wiley   +1 more source

Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair

Advanced Science, EarlyView.
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing, Yang Yang, Zichen Hong, Chunhui Tian, Huiyu Chu, Susanne Clara Prokop, Hongwei Cai, Mingxia Gu, Jason Tchieu, Ken Mackie, Feng Guo   +10 more
wiley   +1 more source

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

Advanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar, Yannaël Bossard, Rachel Sava, Tobias Gänswein, Lorenca Sadiraj, Jean‐Samuel Dupré, Manuel Schröter, J. Gray Camp, Fernando Cardes, Julian Bartram, Andreas Hierlemann   +10 more
wiley   +1 more source

Memristive Physical Reservoir Computing

Advanced Science, EarlyView.
Memristors’ nonlinear dynamics and input‐dependent memory effects make them ideal candidates for high‐performance physical reservoir computing (RC). Based on their conductance modulation, memristors can be classified as electronic or optoelectronic types.
Dian Jiao, Ziyuan Wang, Jingrui Wang, Li Zhang, Xianhua Wei, Lingxiang Hu, Zongxiao Li, Athanasios V. Vasilakos, Zhizhen Ye, Fei Zhuge   +9 more
wiley   +1 more source

Organic Thin‐Film Transistors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
Organic thin‐film transistors (OTFTs) are reviewed for neuromorphic computing applications, highlighting their power‐efficient, and biological time‐scale operation. This article surveys OFET and OECT devices, compares them with memristors and CMOS, analyzes how fabrication parameters shape spike‐based metrics, proposes standardized characterization ...
Luke McCarthy, Mohan V. Jacob, Mostafa Rahimi Azghadi   +2 more
wiley   +1 more source

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

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

Advanced 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, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source