Results 41 to 50 of about 159,702 (261)

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Advanced Functional Materials, EarlyView.
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam, Ouassim L'Karkouri, Danqing Liu   +2 more
wiley   +1 more source

Machine Learning‐Informed Nano Co‐Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue

Advanced Materials, EarlyView.
We present SP‐13786 (SP), a fibroblast activation protein (FAP) inhibitor, as a universal excipient for co‐assembling stable drug nanoparticles (SCAN). Assembly mechanism deciphered by molecular dynamics and explainable machine learning, SCAN attenuate fibrosis‐induced stromal barriers, enhances lesional drug accumulation, and improves therapeutic ...
Zehua Liu, Qiang Long, Yihao Liu, Xiuqiao Sun, Baoding Zhang, Binxin Liao, Weibin Wu, Wangxi Hai, Pei Zhang, Wenhua Lian, Yuewen Zhu, Zheng Wang, Caisheng Wu, Xianming Deng, Hélder A. Santos, Xiaofeng Ye   +15 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers

Complexity, 2018
Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization.
Gonzalo A. Ruz, Pamela Araya-Díaz
doaj   +1 more source

Superionic Amorphous Li2ZrCl6 and Li2HfCl6

Advanced Materials, EarlyView.
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley   +1 more source

Commutativity of probabilistic belief revision

Frontiers in Cognition
Bayesian updating, also known as belief revision or conditioning, is a core mechanism of probability theory, and of AI. The human mind is very sensitive to the order in which it is being “primed”, but Bayesian updating works commutatively: the order of ...
Bart Jacobs
doaj   +1 more source

Some Applications of Bayes' Rule in Probability Theory to Electrocatalytic Reaction Engineering

International Journal of Electrochemistry, 2011
Bayesian methods stem from the principle of linking prior probability and conditional probability (likelihood) to posterior probability via Bayes' rule.
Thomas Z. Fahidy
doaj   +1 more source

A Bayesian Density Model Based Radio Signal Fingerprinting Positioning Method for Enhanced Usability

Sensors, 2018
Indoor navigation and location-based services increasingly show promising marketing prospects. Indoor positioning based on Wi-Fi radio signal has been studied for more than a decade because Wi-Fi, a signal of opportunity without extra cost, is ...
Zheng Li, Jingbin Liu, Fan Yang, Xiaoguang Niu, Leilei Li, Zemin Wang, Ruizhi Chen   +6 more
doaj   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source