Results 101 to 110 of about 1,239,591 (239)

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

Practical Computational Exploration of Chemical Reaction Space: Assessing the Chemical Stability of Active Pharmaceutical Ingredients Under Acidic Conditions

Angewandte Chemie, EarlyView.
Metadynamics simulations drive automated reaction exploration of acid‐catalysed drug degradation, generating a network spanning 1720 species and 2471 elementary steps. QM‐based filtering reduces the network to eight candidate pathways for rigorous DFT refinement and microkinetic modelling.
Julius Seumer, Maria Harris Rasmussen, Oriana Brea, Mikko Muuronen, Andreas H. Göller, Jan H. Jensen   +5 more
wiley   +2 more sources

STATE ESTIMATION IN ALCOHOLIC CONTINUOUS FERMENTATION OF ZYMOMONAS MOBILIS USING RECURSIVE BAYESIAN FILTERING: A SIMULATION APPROACH

BioResources, 2008
This work presents a state estimator for a continuous bioprocess. To this aim, the Non Linear Filtering theory based on the recursive application of Bayes rule and Monte Carlo techniques is used. Recursive Bayesian Filters Sampling Importance Resampling (
Olga Lucia Quintero, Adriana Amicarelli, Fernando di Sciascio, Gustavo Scaglia   +3 more
doaj  

Influence of Sample Vector Normalization on Cooperative Spectrum Sensing Under Direct-Conversion Receiver Effects

IEEE Access
This paper investigates sample vector normalization as a statistical preprocessing technique for cooperative spectrum sensing under realistic direct-conversion receiver (DCR) impairments.
Luiz Renault Leite Rodrigues, Dayan Adionel Guimaraes   +1 more
doaj   +1 more source

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +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

An X‑Shaped Chiral Non‑Fullerene n‐Type Semiconductor: Application in Perovskite Solar Cells and Chirality‑Induced Spin Selectivity

Angewandte Chemie, EarlyView.
A highly electron‑accepting derivative of cyclobisbiphenylenecarbonyl (CBBC‐TIC) is reported. CBBC‐TIC functions as an electron‐transport layer for perovskite solar cells, achieving a power conversion efficiency of 20.6%. Furthermore, the enantiomers of CBBC‐TIC exhibited spin‐selective electron transport with high enantiospecific magnetic conductance ...
Yuki Sakamoto, Koki Otsuka, Kuraudo Ishihara, Shuang Li, Ai Shimazaki, Megumi Haramatsu, Junichiro Hirano, Juntaro Nogami, Hiroshi Shinokubo, Hiroki Uratani, Hironori Kaji, Fumitaka Ishiwari, Akinori Saeki, Tomoya Nakamura, Atsushi Wakamiya, Norihito Fukui   +15 more
wiley   +2 more sources

A Multistrategy AI‐Assisted Consensus Screening Pipeline for Discovery of Candidate p53 Monomer Binders

Advanced Intelligent Discovery, EarlyView.
An ultra‐fast small‐sample AI consensus pipeline combines co‐folding and docking to target structure‐lacking p53 monomers. Its optimal mini‐protein binder shows robust interfacial affinity and promising druggability, supplying unprecedented antitumor p53 templates.
Ningyao Li, Xueyi Liu, Qiuyue Li, Chengfeng Yue, Xin Li, Yugang Huang, Xin Deng, Junfei Zhang, Xue Liang, Guodong Ye   +9 more
wiley   +1 more source

Energy-Adaptive SGHSMC: A Particle-Efficient Nonlinear Filter for High-Maneuver Target Tracking

Mathematics
Tracking targets with nonlinear motion patterns remains a significant challenge in state estimation. We propose an energy-adaptive stochastic gradient Hamiltonian sequential Monte Carlo (SGHSMC) filter that combines adaptive energy dynamics with ...
Chang Ho Kang, Sun Young Kim
doaj   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source