Results 141 to 150 of about 860,181 (267)
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
THE CAREER PLATEAU IN CAMEROONIANS COMPANIES
The main aim of this study is to show the impact of career plateauing on Cameroonian employees and to suggest possible solutions that can help solve out the problem. More precisely, our aim is to show the effects of career plateauing on job satisfaction as well as on stress experienced by plateaued employees of Cameroonian Big Companies; in other to ...
openaire +1 more source
LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler +7 more
wiley +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Majority‐Voting Overlapping Method for Error Correction in DNA Data Storage
We propose an overlapping‐based majority‐voting method for DNA data storage error correction. By aligning multiple reads and choosing the most frequent base per position, it suppresses substitution errors without prior models. Validated on synthetic and real sequencing data, it achieves high‐fidelity, scalable, and cost‐effective reconstruction ...
Thi Bich Ngoc Nguyen +5 more
wiley +1 more source
DNA structures with short single‐strand gaps in the non‐template strand of the T7 promoter prevent transcription by T7 RNA polymerase. Contrary to intuition, however, transcriptional activity can be observed again when the size of the gap increases toward the transcription start site, thereby reducing the proportion of double‐stranded DNA in the ...
Michael W. Haydell +2 more
wiley +2 more sources
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Heavy‐Atom Tunneling at Room Temperature Revealed by Instanton Theory
Usually, tunneling does not play a significant role in chemical reactions except at low temperature, especially when heavy atoms are involved. However, using nonadiabatic instanton theory we find that heavy‐atom tunneling dominates the reaction mechanism for spin‐forbidden processes in the synthesis of strained organic molecules even at room ...
Debaarjun Mukherjee +2 more
wiley +2 more sources
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 +2 more
wiley +1 more source

