Results 71 to 80 of about 696 (152)

Al Nanoparticle‐Decorated Metal Oxide Synaptic Transistors for Ultralow‐Energy Neuromorphic Computing with Wide Dynamic Range

Advanced Science, EarlyView.
A nanoparticle‐engineered electrolyte‐gated memtransistor is introduced as a materials‐level strategy to overcome the intrinsic trade‐off between energy consumption and synaptic precision. By embedding aluminum nanoparticles at the oxide–electrolyte interface to modulate ion trapping dynamics, the device achieves stable multistate plasticity under ...
Jun‐Gyu Choi, Yoonseok Song, Seokhyeon Baek, Jingon Jang, Sungjun Park   +4 more
wiley   +1 more source

Data‐Driven Design and Fabrication of Heat‐Resistant, Ultrastrong, Lightweight Aluminum‐Based Entropy Alloy by Additive Manufacturing

Advanced Science, EarlyView.
A data‐driven strategy integrating quantum machine learning (QML) and high‐throughput computing overcomes hot‐cracking limitation to design a novel lightweight aluminum‐based entropy alloy for additive manufacturing. The fabrication transforms brittle intermetallics into deformable hierarchical nanostructures, yielding ultrastrong strength (>1 GPa) and
Enmao Wang, Chao Ding, Danyang Zhou, Chenjin Xu, Swee Leong Sing, Jianzhong Jiang, Huibin Wu   +6 more
wiley   +1 more source

ReRAM/CMOS Array Integration and Characterization via Design of Experiments

Advanced Electronic Materials, EarlyView.
This paper proposes the Design of Experiments to characterize arrays of oxide‐based ReRAM devices by exploring the large characterization space efficiently using only a few numbers of experiments. Using in‐house integration of 20 000 ReRAM devices on a CMOS chip, the unconventional optimization approach determines optimized measurement parameters and ...
Imtiaz Hossen, William A. Borders, Advait Madhavan, Shweta Joshi, Patrick M. Braganca, Jabez J. McClelland, Brian D. Hoskins, Gina C. Adam   +7 more
wiley   +1 more source

Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids. [PDF]

Biomimetics (Basel)
Turgut OE, Asker M, Yesiloz HB, Genceli H, Al-Rawi M.   +4 more
europepmc   +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 Kimh, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

A multifaceted hybrid ES-robotic device for gait training in individuals with neurological disorders. [PDF]

Nat Commun
Dell'Eva F, Guanziroli E, Camerini V, Gandolla M, Brignole L, Maludrottu S, Gruppioni E, Ferrigno G, Molteni F, Ambrosini E, Pedrocchi A.   +10 more
europepmc   +1 more source

Tandem Takeoff: Powering Tomorrow with Industrial‐Grade Perovskite/Silicon Solar Cells

Advanced Energy Materials, EarlyView.
Perovskite/silicon tandem solar cells have recently achieved certified power conversion efficiencies of 34.85%, far exceeding the Shockley‐Queisser limit for single‐junction silicon and standalone perovskite cells. This review highlights the latest advances in the design, integration, and optimization of perovskite top cells for monolithic tandem ...
Maria Vasilopoulou, Di Huang, Jue Gong, Faming Li, Hao Zhang, Yinqing Sun, Lin Mao, Ermioni Polydorou, Ioannis G. Aviziotis, Leonidas C. Palilis, Onurcan Kaya, Stephan Roche, Jordi Arbiol, Dimitrios Davazoglou, Emmanuel Kymakis, Lei Liu, Kuan Sun, Abd Rashid bin Mohd Yusoff, Mingzhen Liu, Mohammad Khaja Nazeeruddin   +19 more
wiley   +1 more source

Piezoelectric Hysteresis Modeling Under a Variable Frequency Based on a Committee Machine Approach. [PDF]

Sensors (Basel)
Aggogeri F, Pellegrini N.
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Digital twin-driven deep learning prediction and adaptive control for coal mine ventilation systems. [PDF]

Sci Rep
Yang X, Li H.
europepmc   +1 more source