Results 151 to 160 of about 142,438 (266)

Measurement of Weld Penetration Depth Using Non-Contact Ultrasound Methods

, 2005
Akio Kita
openalex   +1 more source

High precision penetration depth measurements : probing the superfluid density and the order parameter of high-T[c] superconductors

, 1997
C. Panagopoulos
openalex   +2 more sources

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Wavelength-dependent correlation of LIPSS periodicity and laser penetration depth in stainless steel. [PDF]

Beilstein J Nanotechnol
Chaudhary N, Naik CA, Mangalassery S, Gautam JP, Naraharisetty SRG.   +4 more
europepmc   +1 more source

Comparison of Wavelength-Dependent Penetration Depth of 532 nm and 660 nm Lasers in Different Tissue Types. [PDF]

J Lasers Med Sci, 2023
Aldalawi AA, Suardi N, Ahmed NM, Al-Farawn MAS, Dheyab MA, Jebur WI, Kadhim FJ.   +6 more
europepmc   +1 more source

Comparative evaluation of depth of penetration of root canal irrigant after using manual, passive ultrasonic, and diode laser–assisted irrigant activation technique

, 2019
Arasappan Rajakumaran, Arathi Ganesh
openalex   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Prediction of Electron Beam Welding Penetration Depth Using Machine Learning-Enhanced Computational Fluid Dynamics Modelling. [PDF]

Sensors (Basel), 2023
Yin Y, Tian Y, Ding J, Mitchell T, Qin J.   +4 more
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

A New Penetration Depth Method Using Proctor Compaction Test for Determining the Optimal Starting Time of Hardening Topping in Concrete Flooring. [PDF]

Materials (Basel)
Michalik A, Zychowicz J.
europepmc   +1 more source