Results 171 to 180 of about 198,528 (317)
Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine
Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee +3 more
wiley +1 more source
Xenes for Sustainable Energy: A Roadmap From First‐Principles Design to Practical Deployment
Emerging 2D Xenes are advancing from theoretical predictions toward practical energy‐storage and conversion technologies through the integration of first‐principles modelling, experimental synthesis, electrochemical validation, and AI‐assisted materials design, enabling accelerated discovery of high‐performance and sustainable electrochemical systems ...
Onur Karaman, Ceren Karaman
wiley +1 more source
Two‐Way Shape Memory Polymer Composite Gripper for Adaptive Robotic Applications
A two‐way shape memory polymer (SMP) composite is developed with intrinsic shape‐changing capability driven solely by temperature, eliminating external actuation loads. Embedding the SMP in a low‐stiffness elastomeric matrix enabled reversible transformations during heating and cooling cycles.
Aamna Hameed, Kamran Ahmed Khan
wiley +1 more source
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu +8 more
wiley +1 more source
Learning within a Markovian Environment [PDF]
We investigate learning in a setting where each period a population has to choose between two actions and the payoff of each action is unknown by the players. The population learns according to reinforcement and the environment is non-stationary, meaning
Javier Rivas
core
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
3D Printing of Stretchable, Compressible and Conductive Porous Polyurethane for Soft Robotics
A 3D‐printable porous dopamine‐polyurethane acrylate elastomer results in conductive, stretchable, and compressible structures that can be metallized in situ through catechol‐mediated silver reduction. The resulting material function as both compliant soft robot with a and strain sensors without complex assemblies, enabling fully 3D‐printed soft ...
Ouriel Bliah +3 more
wiley +1 more source
Reinforcement learning for policymaking in epidemic control: A scoping review. [PDF]
Bolshov O, Chumachenko D.
europepmc +1 more source
A Comparative Analysis of Reinforcement Learning Methods
This paper analyzes the suitability of reinforcement learning (RL) for both programming and adapting situated agents. We discuss two RL algorithms: Q-learning and the Bucket Brigade.
Mataric, Maja
core
Shaping Carbon Nitrides for Advanced Macrostructures
This review examines how carbon nitride can be shaped through a range of printing and interfacial assembly methods. By bringing together additive manufacturing and liquid–liquid structuring concepts, carbon nitride is moving beyond its traditional powder‐based photocatalyst form toward digitally designed robust macroscale architectures with high design
Simona Baluchová, Baris Kumru
wiley +1 more source

