Results 101 to 110 of about 68,936 (260)

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

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

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Facet‐Dependent Water Inhibition of Alkanol Dehydration on TiO2 via Distinct Water–Alkanol Complexes

Angewandte Chemie, EarlyView.
Water inhibits alkanol dehydration on TiO2 through facet‐dependent manners via distinct IPA‐water complexes. On TiO2(001), water forms a strongly hydrogen‐bonded isopropoxide–H2O complex that readily dominates the surface and substantially elevates the activation barrier, whereas on TiO2(101), water weakly hydrogen‐bonds to molecular IPA, resulting in ...
Wenda Hu, Haiting Cai, Anthony Savoy, Jinshu Tian, Sungmin Kim, Fan Lin, Junrui Li, Hao Xu, Yiqing Wu, Zihao Zhang, Nicholas Jaegers, Huamin Wang, Feng Gao, Jianzhi Hu, Yong Wang   +14 more
wiley   +2 more sources

Visual and Visual‐Inertial SLAM Based on Enhanced Deep Learning Features and Motion Smoothness Constraints

Advanced Intelligent Systems, EarlyView.
A visual and visual‐inertial simultaneous localization and mapping (SLAM) algorithm, leveraging enhanced deep learning features and motion smoothness constraints, is proposed in this research work. This method retains the advantages of geometry‐based SLAM methods while effectively utilizing the powerful representational capabilities of data‐driven ...
Maosheng Jiang, Lei Ma, Muhua Zhang, Kai Shen   +3 more
wiley   +1 more source

Automated Dynamic Flow Experimentation for Rapid Kinetic Fitting of Transition Metal Catalysis

Angewandte Chemie, EarlyView.
We have developed an automated dynamic flow experimentation platform to automatically fit and identify the most accurate kinetic model from a generated set of candidates. Three transition metal‐catalyzed transformations were performed using this workflow.
Florian L. Wagner, Klara Silber, Tobias A. Doliner, C. Oliver Kappe   +3 more
wiley   +2 more sources

Tandem Neural Network Rapidly Solves Multivalued Inverse Problems: Application to Oxide‐Semiconductor Characterization

Advanced Intelligent Systems, EarlyView.
A tandem neural network directly solves the multivalued inverse problem of extracting semiconductor parameters from transistor measurements. Trained on only 1000 simulations, the network infers six material parameters (e.g., defect states, carrier concentration, mobility) in under 1 ms, demonstrating a broadly applicable framework for semiconductor ...
Masatoshi Kimura, Keisuke Ide, Kuan‐Ju Zhou, Atsushi Shimizu, Takayoshi Katase, Hidenori Hiramatsu, Kei Terayama, Hideo Hosono, Toshio Kamiya   +8 more
wiley   +1 more source

Linking community structure and climate vulnerability in desert plant assemblages of southern California

American Journal of Botany, EarlyView.
Abstract Premise Desert plant assemblages in southern California provide an opportunity to link patterns of community structure with climate‐driven vulnerability in a rapidly changing environment. California sustains an exceptionally diverse flora of approximately 4300 plant species, with 31% identified as endemic.
Hector Zumbado‐Ulate, Luis E. Barrios, Danelle A. Baronia, G. Darrel Jenerette, Lynn C. Sweet   +4 more
wiley   +1 more source

Milkshake Prices, International Reserves, and the Mexican Peso

Frontera Norte, 2005
Menu prices from 13 international restaurant franchises that operate in both El Paso and Ciudad Juárez are utilized to examine the behavior over time of the peso/dollar exchange rate.
Thomas M. Fullerton Jr., David Torres
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