Results 151 to 160 of about 14,957 (259)

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Error-State Model Predictive Path Integral Control of Tendon-Driven Continuum Robots using Cosserat Rod Dynamics with Strain Parametrization. [PDF]

IEEE Robot Autom Lett
Arefinia E, Feizi N, Pedrosa FC, Patel RV, Jayender J.   +4 more
europepmc   +1 more source

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Probing individual quantum emitters in bulk semiconductors via photonic nanojets. [PDF]

Sci Adv
Semnani B, Venuturumilli SS, Soltani M, Adhikary P, Pasharavesh A, Videnov N, Anderson P, Sarkar S, Muthu VRR, Bajcsy M.   +9 more
europepmc   +1 more source

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Dictionary Learning Methods for Brain Activity Mapping with MEG Data. [PDF]

Brain Topogr
Calvetti D, Somersalo E.
europepmc   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

Machine‐Learning‐Guided Discovery of Boron‐Free Narrowband Blue Thermally Activated Delayed Fluorescence Emitters

Angewandte Chemie, EarlyView.
A data‐driven discovery engine—exhaustive enumeration of carbazole‐containing polycyclic aromatic hydrocarbons (Cz‐PAHs) followed by machine learning—identifies boron‐free, narrowband blue thermally activated delayed fluorescence emitters for organic light‐emitting diodes (OLEDs).
Masaya Hagai, Jie Sun, Jun Hyeon Lee, Kazuhiro J. Fujimoto, Shigehiro Yamaguchi, Takuma Yasuda, Takeshi Yanai   +6 more
wiley   +2 more sources

Generating the Critical Ising Model via SRGAN: A Schramm-Loewner Evolution Analysis from a Geometric Deep Learning Perspective. [PDF]

Entropy (Basel)
Yang Y, Li W, Wang Y, Liu Z, Tuo K.
europepmc   +1 more source

MDSC: Unsupervised Multipath Decomposition and Synergistic Correction for Efficient Low‐Light Image Enhancement with Detail‐Aware Smoothing

Advanced Intelligent Systems, EarlyView.
This work proposes MDSC, an unsupervised low‐light enhancement framework integrating three core innovations: detail‐aware smoothing, multipath decomposition, and synergistic correction. It suppresses noise, handles rapid illumination variations, and prevents reflectance‐contrast amplification inherent to Retinex separation.
Yong Cheng, De Yu, Yongqi Yuan, Mengjie Ye, Huan Wang, Qian Zhang, Ge Jin   +6 more
wiley   +1 more source