Results 211 to 220 of about 47,364 (306)

Mapping Metabolomic Relationships of Hop Cultivars in an Ancestral Lineage Context. [PDF]

ACS Omega
Dias GS, Gallon ME, Gobbo-Neto L.
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

Comprehensive Characterization of Bioactive Properties in Extracts from Different Chilean Hop Ecotypes (<i>Humulus lupulus</i> L.): Antioxidant, Antimicrobial and Antitumor Activities. [PDF]

Antioxidants (Basel)
Betancur MC, Salazar F, Araya M, Behn A, López J, Quesille-Villalobos A, Villatoro JM, Poblete J, Zambrano A.   +8 more
europepmc   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

Phytochemical Profile, Antioxidant Capacity, and Photoprotective Potential of Brazilian <i>Humulus Lupulus</i>. [PDF]

Pharmaceuticals (Basel)
Silva GCC, da Silva FPA, Beirão GAR, Severino JJ, Machado MA, Barbosa MPDSB, Reyes GB, Rickli ME, Lopes AD, Jacomassi E, Nunes MGIF, Francisco JP, Barros BCB, do Valle JS, Gonçalves JE, Gazim ZC.   +15 more
europepmc   +1 more source

TWENTY-EIGHTH REPORT ON THE TRIAL OF NEW VARIETIES OF HOPS, 1943

, 1945
E. S. Salmon
openalex   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
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, Christian Mark Pelicano   +1 more
wiley   +1 more source

Green Antimicrobials: Innovative Applications of Hops Extracts as Biocontrol Agents. [PDF]

Pathogens
Paniagua-García AI, Ibáñez A, Díez-Antolínez R.   +2 more
europepmc   +1 more source

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

Fingerprinting and chemotyping approaches reveal a wide genetic and metabolic diversity among wild hops (Humulus lupulus L.). [PDF]

PLoS One
Ducrocq F, Piutti S, Henychová A, Villerd J, Laflotte A, Girardeau L, Grosjean J, Patzak J, Hehn A.   +8 more
europepmc   +1 more source