Results 181 to 190 of about 41,155 (321)

Role of High Fidelity Vs. Low Fidelity Experimental Data in Machine Learning Model Performance for Predicting Polymer Solubility

Macromolecular Rapid Communications, EarlyView.
The performance of machine learning models for classifying polymer solubility improves when a high‐fidelity experimental dataset is used compared to a low‐fidelity experimental dataset. This has important implications for justifying the value of spending additional time and resources preparing detailed experimental datasets.
Mona Amrihesari, Manali Banerjee, Raul Olmedo, Blair Brettmann   +3 more
wiley   +1 more source

ABA triblock copolymers prepared with poly(ε-caprolactone) and PEG, PTHF, and PPG macroinitiators as the central segment: synthesis, characterization, and thermal properties. [PDF]

RSC Adv
Barrera-Nava MP, García GG, Cruz JB, Shea KJ, Báez JE.   +4 more
europepmc   +1 more source

Recent Advances in the Laser‐Based Fabrication and Applications of High‐Entropy Alloy Nanoparticles

MetalMat, EarlyView.
This review presents recent advances in the laser‐based fabrication of high‐entropy alloy nanoparticles, focusing on scalable, environmentally friendly, and compositionally tunable synthesis methods. It highlights the critical influence of laser parameters on nanoparticle size, phase, and morphology, enabling tailored properties for applications in ...
Bibek Kumar Singh, Rajesh Rawat, Archana Tiwari, Venugopal Rao Soma, Ajay Tripathi   +4 more
wiley   +1 more source

The relevance of nitrogen-based, high-enthalpy plasmas for effective feedstock treatment in thermal spraying of suspensions. [PDF]

Sci Rep
Mauer G, Vaßen R.
europepmc   +1 more source

Application of Machine Learning in Heat Treatment Process Design of Carburized Steel

Materials Genome Engineering Advances, EarlyView.
To accelerate heat treatment design, we constructed a closed‐loop machine learning strategy involving multi‐source datasets and feature screening. The optimized model accurately predicts hardness and friction coefficients, successfully guiding the process optimization for two typical carburized steels with high experimental consistency.
Di Jiang, Yihao Zheng, Chunyang Luo, Xuefei Wang, Chi Zhang, Zhaodong Wang   +5 more
wiley   +1 more source

PVDF/PGMA Blend Membranes: NIPS-Driven Microstructure, Thermodynamic Miscibility, and Enhanced Wettability. [PDF]

ACS Omega
Hakim MA, Mahadi Hasan M, Al-Mamun M, Hossan MS, Zahid AASM, Rahman MH.   +5 more
europepmc   +1 more source

Machine Learning Design of Tungsten Alloys With Strength–Ductility Synergy

Materials Genome Engineering Advances, EarlyView.
This study integrates machine learning with solid solution softening knowledge to design multielement tungsten alloys with strength‐ductility synergy. ML models identify promising compositions within W‐ Ta ‐ Re system that exhibit pronounced chemical short‐range order, resulting in exceptional mechanical performance. Experimental validation through the
Juan Ding, Jiayi Liu, Jiatao Zhou, Baishan Chen, Yunzhu Ma, Wensheng Liu, Yufeng Huang, Chaoping Liang   +7 more
wiley   +1 more source

Applications of Isothermal Titration Calorimetry in Studying Biomimetic Nanocarriers. [PDF]

Biomolecules
Guerrero M, Braden C, Bao Y.
europepmc   +1 more source

Enhancing the Performance of 3D‐Printed Polyamide Composites Through Pre‐ and Post‐Processing Methods

Polymer Composites, EarlyView.
FDM‐printed polyamide composites and post‐processing by annealing. ABSTRACT In this study, composite filaments with a short carbon fiber (CF) reinforced polyamide 612 (PA612) were produced using the FDM method at three different raster angles (0°, ±45°, 90°).
Busra Eyri, Yusuf Yagci, N. Gamze Karsli, Taner Yilmaz   +3 more
wiley   +1 more source

Modeling corium pool stratification and focusing effect in APR1400 using a multiphase CFD framework. [PDF]

Sci Rep
Mahboob K, Alkaabi A, Addad Y.
europepmc   +1 more source