Results 211 to 220 of about 131,967 (276)

Design of an ankle exoskeleton with twisted string actuation for running assistance. [PDF]

Wearable Technol
Tan GR, Collins SH.
europepmc   +1 more source

Exploring Thermal and Mechanical Strains During Laying Down Process in Fused Filament Fabrication

Macromolecular Materials and Engineering, EarlyView.
This study analyzes strain evolution and thermal behavior during FFF of PLA using strain gauges and infrared imaging. Microstrain levels depend on printing conditions, with adhesion‐induced compression during cooling and peak strains in early layers. Microtomography shows minimal porosity, while thermal imaging reveals rapid heat penetration, strong ...
Boubakeur Mecheri, Jaianth Vijayakumar, Elodie Boller, Sofiane Guessasma   +3 more
wiley   +1 more source

Crossbow Bioreactors for Studying the Effects of Time-Varying Mechanical Preload and Afterload on Engineered Cardiac Tissues. [PDF]

Adv Funct Mater
Helfer A, Strash N, Patsy M, Bursac N.
europepmc   +1 more source

How to Conduct a Multi‐Domain Systematic (Literature) Review? Guidelines Using The Lotus Protocol

Psychology &Marketing, EarlyView.
ABSTRACT Complex challenges increasingly demand multidisciplinary research across intersecting knowledge domains. However, existing systematic (literature) review protocols offer limited guidance and tend to confine scholars to single‐domain or single‐intersection reviews.
Bart J. A. van Bueren, Weng Marc Lim, Naveen Donthu, Kevin Argus, Julian M. Water‐Lynch, Alvedi Sabani, Mark A. A. M. Leenders   +6 more
wiley   +1 more source

Multiphase Transient Flow in Wellbore during Shallow Hydrate Reservoir Drilling in Deep Water. [PDF]

ACS Omega
Yin B, Chen C, Feng K, Liu S, Ren M, Wang Z, Sun B.   +6 more
europepmc   +1 more source

Benchmarking Large Language Models for Polymer Property Predictions

Macromolecular Rapid Communications, EarlyView.
Large language models (LLMs) are fine‐tuned on polymer thermal property datasets to directly predict glass transition, melting, and decomposition temperatures from SMILES inputs. Compared to state‐of‐the‐art models such as Polymer Genome, polyGNN, and polyBERT, LLMs achieve competitive yet lower accuracy.
Sonakshi Gupta, Akhlak Mahmood, Shivank Shukla, Rampi Ramprasad   +3 more
wiley   +1 more source

Hydrodynamical pathways in the phase change of real fluids.

Gallo M, Occhioni F, Daniele R, Casciola C.   +3 more
europepmc   +1 more source

Mechanism of wellbore instability considering tubular-string contact with the wellbore wall. [PDF]

Sci Rep
Zhou Y, Zhang H, Wu Y, Li X, Xi C, Lv K, Zhang H, Wang X.   +7 more
europepmc   +1 more source

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

TheMeCat: Dataset of Thermocatalytic Conversion of CO₂ to Methanol. [PDF]

Sci Data
Toldy ÁI, Pisal P, Krejčí O, Rinke P, Santasalo-Aarnio A.   +4 more
europepmc   +1 more source