Results 151 to 160 of about 296,784 (294)

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

Life‐Cycle Assessment of Printed Electronic Components ‐ Case Study for Organic Electrochemical Transistors

Advanced Electronic Materials, EarlyView.
This tutorial introduces a practical framework for implementing early‐stage Life‐Cycle Assessment (LCA) in flexible and printed electronics. Using organic electrochemical transistors (OECTs) as a case study, the modular Process‐of‐Record and open‐access inventory provides a rich resource adaptable to a plethora of technologies in printed electronics ...
Laura Teuerle, Tommy Meier, Klara Hänisch, Finn Jaekel, Yeohoon Yoon, Andreas Wendel, Hans Kleemann   +6 more
wiley   +1 more source

Ensuring end-to-end privacy in IoT-based healthcare systems through hyperledger fabric and identity mixer. [PDF]

PLoS One
Nasr Esfahani M, Shahgholi Ghahfarokhi B, Etemadi Borujeni S.   +2 more
europepmc   +1 more source

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

Advanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang, Luca Weckelmann, Baolin Wu, Chih‐Long Tsai, Luc Raijmakers, Rüdiger‐A. Eichel, Anna Windmüller   +6 more
wiley   +1 more source

The quantitative economon model as a novel computational tool for addiction research. [PDF]

Exp Clin Psychopharmacol
Haynes JM, Correa da Rosa J, Butelman ER, Hursh SR, Negus SS.   +4 more
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

A high utility itemsets mining algorithm based on co-evolution. [PDF]

Sci Rep
Yang W, Han M, Dai Z, Li J, Ding J.
europepmc   +1 more source

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

Advanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher, Katarzyna P. Sokol, Philipp Simons, Kun Joong Kim, Michael Foshey, Yunsheng Tian, Thorben Prein, Lincoln J. Miara, Elsa Olivetti, Wojciech Matusik, Jennifer L. M. Rupp   +10 more
wiley   +1 more source

An innovative blockchain framework for strengthening security and efficiency in banking. [PDF]

Sci Rep
Ahammad MS, Maliha M, Nila NE, Islam MS.
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source