Results 231 to 240 of about 179,012 (271)

2D population balance modeling and ML‐based multi‐objective optimization for the crystallization process of resveratrol

AIChE Journal, EarlyView.
Abstract Crystallization is critical in pharmaceutical manufacturing, influencing active pharmaceutical ingredient (API) purity and processability. This study models the cooling crystallization of resveratrol in a water‐ethanol solvent using a two‐dimensional population balance model (2D‐PBM). Experimental data from Focused Beam Reflectance Measurement
Álmos Orosz, Monika Neal, Rekha Rao, Christine Roberts, Botond Szilágyi, Zoltán K. Nagy   +5 more
wiley   +1 more source

Bayesian Geostatistics Using Predictive Stacking. [PDF]

J Am Stat Assoc
Zhang L, Tang W, Banerjee S.
europepmc   +1 more source

Fractional integral inequalities for strongly convex functions via multiplicative calculus with applications

Saad Ihsan Butt, Dawood Khan, Valer-Daniel Breaz, Luminiţa-Ioana Cotîrlă, Bandar Bin‐Mohsin   +4 more
openalex   +1 more source

Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning

Advanced Intelligent Discovery, EarlyView.
End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley   +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

Ferrofluid droplet generation on a zero-thickness nozzle by a magnetic field using a wedge-shaped functional surface. [PDF]

PLoS One
Favakeh A, Bijarchi MA, Mohammadrashidi M, Yaghoobi M, Shafii MB.   +4 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

The Role of Psoas Muscle in Scoliosis: A Review of the Literature. [PDF]

Cureus
Fryda Z, Passadi KA, Giannakou S, Vasilakou A, Pouli K, Lepetsos P, Zafeiris CP.   +6 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source