Results 81 to 90 of about 6,930,474 (290)

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

Constrained Exploration in Reinforcement Learning with Optimality Preservation

CoRR, 2023
We consider a class of reinforcement-learning systems in which the agent follows a behavior policy to explore a discrete state-action space to find an optimal policy while adhering to some restriction on its behavior. Such restriction may prevent the agent from visiting some state-action pairs, possibly leading to the agent finding only a sub-optimal ...
openaire   +3 more sources

3D‐Printed Titanium Gyroid Scaffold Structure Integrated With Tough Hybrid Materials for Cartilage Replacement

Advanced Engineering Materials, EarlyView.
This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin, Gloria R. Young, Francesca Tallia, Reece N. Oosterbeek, Shaaz Ghouse, Edward Spiers, Nupur Kohli, Tom Briggs, Marc Masen, Siwei Li, Ren‐Jei Chung, Jonathan R. T. Jeffers, Julian R. Jones   +12 more
wiley   +1 more source

Vehicle Lateral Control Based on Augmented Lagrangian DDPG Algorithm

Applied Sciences
This paper studies the safe trajectory tracking control of intelligent vehicles, which is still an open and challenging problem. A deep reinforcement learning algorithm based on augmented Lagrangian safety constraints is proposed to the lateral control ...
Zhi Li, Meng Wang, Haitao Zhao
doaj   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source

Advances in Sustainable and Wearable Textile Based Soft Robotics

Advanced Functional Materials, EarlyView.
This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas, Marzia Dulal, Sophia K. Novoselov, Victoria K. Novoselov, Kostya S. Novoselov, Shaila Afroj, Nazmul Karim   +6 more
wiley   +1 more source

Hyperproperty-Constrained Secure Reinforcement Learning

Proceedings of the International Symposium on Formal Methods and Models for System Design
Accepted in IEEE/ACM MEMOCODE ...
Ernest Bonnah, Luan Viet Nguyen, Khaza Anuarul Hoque   +2 more
openaire   +3 more sources

Exploring the Preference for Discrete over Continuous Reinforcement Learning in Energy Storage Arbitrage

Energies
In recent research addressing energy arbitrage with energy storage systems (ESSs), discrete reinforcement learning (RL) has often been employed, while the underlying reasons for this preference have not been explicitly clarified.
Jaeik Jeong, Tai-Yeon Ku, Wan-Ki Park
doaj   +1 more source

Functionalizing Micro‐to‐Mesoscopic Electrode Architectures for Regulating Electron Transfer Behaviors in Electrocatalysis

Advanced Functional Materials, EarlyView.
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao, Jiaojiao Zhang, Shideng Yuan, Xinmeng Yu, Keming Wan, Xiaoguang Duan, Zhining Wang   +6 more
wiley   +1 more source

Logically-Constrained Reinforcement Learning

, 2018
We present the first model-free Reinforcement Learning (RL) algorithm to synthesise policies for an unknown Markov Decision Process (MDP), such that a linear time property is satisfied. The given temporal property is converted into a Limit Deterministic Buchi Automaton (LDBA) and a robust reward function is defined over the state-action pairs of the ...
Hasanbeig, Mohammadhosein, Abate, Alessandro, Kroening, Daniel   +2 more
openaire   +2 more sources