Results 101 to 110 of about 789 (216)
Single‐Chromophore Homojunction Organic Solar Cells: A Path to Simplicity and Efficiency
This perspective discusses how the intrinsic optoelectronic properties of organic semiconductors, their molecular packing in the solid‐state, and internal energetic gradients within a device can enable free‐charge carrier generation in homojunction organic solar cells.
Shaun McAnally +2 more
wiley +1 more source
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
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
Pursuer Assignment and Control Strategies in Multi-Agent Pursuit-Evasion Under Uncertainties. [PDF]
Zhang L, Prorok A, Bhattacharya S.
europepmc +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Inverse Design of Nanoparticulate Materials
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré +5 more
wiley +1 more source
Flexible prediction of opponent motion with internal representation in interception behavior. [PDF]
Tsutsui K, Fujii K, Kudo K, Takeda K.
europepmc +1 more source
Methanesulfonic Acid as a Dual‐Role Reagent for Porous Polymer Network Design
The design of porous polymer networks (PPNs) using methanesulfonic acid (MSA) as a dual‐role reagent facilitates the synthesis of robust PPNs for specific applications. It also makes the scale‐up process techno‐economically feasible because MSA functions simultaneously as both a solvent and a catalyst for the reaction.
Kelechi Festus +8 more
wiley +1 more source
Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng +24 more
wiley +1 more source

