Results 191 to 200 of about 2,844,778 (299)

Maximum Stability Point Tracking Stabilizes Wide‐Bandgap Mixed‐Halide Perovskite Solar Cells

Advanced Energy Materials, EarlyView.
A maximum stability point tracking (MSPT) strategy suppresses charge trapping‐induced halide segregation, enabling wide‐bandgap perovskite solar cells to achieve significantly enhanced operational stability compared to conventional maximum power point tracking (MPPT).
Seongheon Kim, Geon Kim, Taeeon Kim, Kwang Seop Shin, Jongchan Kim, Mansoo Choi, Yun Seog Lee, Namyoung Ahn   +7 more
wiley   +1 more source

Forecasting nonlinear chaotic time series with function expression method based on an improved genetic-simulated annealing algorithm. [PDF]

Comput Intell Neurosci, 2015
Wang J, Zhou BH, Zhou SD, Sheng Z.
europepmc   +1 more source

Beyond the Gold Standard: Towards Industrially Viable Electrodes for Durable Perovskite Solar Cells

Advanced Energy Materials, EarlyView.
Transparent and opaque electrode materials are mapped by raw material cost per 1 m2 electrode area and retained median device efficiency after heat–light ageing. FTO offers a lower‐cost and more stable alternative to ITO, while Cr/Al provides the lowest‐cost rear electrode investigated with Au‐like stability and substantially improved durability ...
Tino Lukas, Manuel Kober‐Czerny, Ali Reza Nazari Pour, James McGettrick, Georgios Loukeris, Clemens Baretzky, Shuaifeng Hu, Junke Wang, Chia‐Yu Chang, Sam Teale, Bowei Li, Trystan M. Watson, Martin Stolterfoht, Robert L. Z. Hoye, Philippe Holzhey, Lukas Wagner, Markus Kohlstädt, Henry J. Snaith   +17 more
wiley   +1 more source

Population balance modeling and digital design of degree of agglomeration in industrial crystallization

AIChE Journal, EarlyView.
Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends ...
Yung‐Shun Kang, Hemalatha Kilari, Neda Nazemifard, C. Benjamin Renner, Yihui Yang, Charles Papageorgiou, Zoltan K. Nagy   +6 more
wiley   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

An adaptive simulated annealing algorithm

In this paper, inspired by the idea of Metropolis algorithm, a new sample adaptive simulated annealing algorithm is constructed on finite state space. This new algorithm can be considered as a substitute of the annealing of iterative stochastic schemes ...
Gong, Guanglu, Qian, Minping, Liu, Yong
core  

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

Investigation of Analog Memristor Characteristics for Hardware Synaptic Weight in Multilayer Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley   +1 more source