Results 211 to 220 of about 823,925 (294)

Highly‐Uniform Passive Crossbar Arrays of Resistive Switching Random Access Memory (RRAM) for In‐Memory Computing Applications

Advanced Electronic Materials, EarlyView.
Passive resistive memory arrays promise efficient in‐memory computing but suffer from sneak paths and programming variability. Here, highly uniform 32 × 32 passive RRAM crossbars are programmed with multilevel precision below 3% error and 99.5% yield.
S. Ricci, P. Mannocci, M. Porzani, D. Bridarolli, F. Carletti, M. Farronato, D. Ielmini   +6 more
wiley   +1 more source

Sustainable closed-loop supply chain management for a two-warehouse system with trade-credit and emissions constraints under dynamic demand. [PDF]

Sci Rep
Vishnoi M, Deepi D, Singh SR, Sarkar B.
europepmc   +1 more source

A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration

Advanced Electronic Materials, EarlyView.
Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti, K. Nikiruy, A.S. Demirkol, Alon Ascoli, M. Ziegler, R. Tetzlaff, Fernando Corinto   +6 more
wiley   +1 more source

Reconfigurable Ternary Logic‐In‐Memory With Organic Antiambipolar Transistor

Advanced Electronic Materials, EarlyView.
We develop a ternary logic‐in‐memory with an organic antiambipolar transistor combining a ternary inverter and ternary nonvolatile memory in the same circuit. The memory function of the circuit enables electrical reconfiguration to obtain standard, negative, and positive ternary inverters in the same device.
Ryoma Hayakawa, Taiga Kijima, Yuho Yamamoto, Yoichi Yamada, Yutaka Wakayama   +4 more
wiley   +1 more source

A novel allele of the FUT1 gene containing c.416C>G in a Chinese Han patient. [PDF]

Transfusion
Wu W, Huang X.
europepmc   +1 more source

Controllable Superconductivity in Suspended NbSe2

Advanced Electronic Materials, EarlyView.
Suspended NbSe2${\rm NbSe}_2$ provides two complementary routes for controlling superconducting transport. Gate‐driven deformation strains the suspended crystal and tunes its critical temperature and current. Weak thermal anchoring enhances thermal feedback, contributing to multistep hysteresis and negative differential resistance.
Ruihuan Fang, Cuiju Yu, Youqiang Huang, Tosson Elalaily, Yuvraj Chaudhry, Yaoqiang Zhou, Andres Castellanos‐Gomez, Sanshui Xiao, Jiwon Park, Hyunyong Choi, Fida Ali, Hanlin Fang, Jose L. Lado, Pertti Hakonen, Zhipei Sun   +14 more
wiley   +1 more source

The effect of the China-Thailand railway on Thailand's trade with China Guangxi Province. [PDF]

PLoS One
Wei S, Xia L.
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

Quality Variation Patterns and Predictive Modeling of Fermented Soybean Whey-Based Tofu Under Cold-Chain Conditions Using Kinetic and Machine Learning Approaches. [PDF]

Foods
Zhao D, Huang Z, Chen H, Zhao L, Zhou X, Zhou X, Fan L, Li F.   +7 more
europepmc   +1 more source

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

Advanced 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, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source