Results 61 to 70 of about 305,569 (242)
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng +9 more
wiley +1 more source
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Computational and structure‐guided arginine scanning rewires the DNA‐binding interface of APE1 to create APE1‐Evo, a hyperactive yet specific AP endonuclease. Integrated into the NAPTUNE‐V2.0 cascade, APE1‐Evo enables amplification‐free, multiplex viral RNA sensing for dengue virus and influenza A/B, highlighting a general strategy for engineering ...
Junlan Wang +20 more
wiley +1 more source
CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su +5 more
wiley +1 more source
Bistable Networks Enable Complex Shape Changes
Transition‐controlled metamaterials are networks of bistable mechanical memory that store local binary states and express them as global shape change. By decoupling low‐force programming from high‐force holding, a single lattice is reconfigured into distinct 2D profiles and 3D surfaces without continuous actuation, enabling reusable morphing materials ...
Sawyer Thomas, Jeffrey Lipton
wiley +1 more source
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao +8 more
wiley +1 more source
In this paper, we will study the permutation flow shop scheduling problem (PFSSP) with sequence independent setup time (SIST). This constraint is the most common encountered in industrial production.
Sadki Hajar, Allali Karam
doaj +1 more source
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
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 +4 more
wiley +1 more source

