Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Tu C Le

Showing results (11-20 of 39) with videos related to

Pageof 4
Sort By:
The Journal of Physical Chemistry. B|April 17, 2019
Machine Learning Approaches for Further Developing the Understanding of the Property Trends Observed in Protic Ionic Liquid Containing SolventsDilek Yalcin, Tu C Le, Calum J Drummond, et al.
The Journal of Chemical Physics|November 10, 2009
The effect of interbranch spacing on structural and rheological properties of hyperbranched polymer meltsTu C Le, B D Todd, P J Daivis, et al.
Communications Chemistry|October 3, 2023
Accelerating the prediction of CO<sub>2</sub> capture at low partial pressures in metal-organic frameworks using new machine learning descriptorsIbrahim B Orhan, Tu C Le, Ravichandar Babarao, et al.
The Journal of Chemical Physics|February 26, 2009
Structural properties of hyperbranched polymers in the melt under shear via nonequilibrium molecular dynamics simulationTu C Le, B D Todd, P J Daivis, et al.
Molecules (Basel, Switzerland)|March 6, 2021
Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame RetardancyHoang T Nguyen, Kate T Q Nguyen, Tu C Le, et al.
ACS Applied Materials & Interfaces|December 20, 2021
Prediction of O<sub>2</sub>/N<sub>2</sub> Selectivity in Metal-Organic Frameworks via High-Throughput Computational Screening and Machine LearningIbrahim B Orhan, Hilal Daglar, Seda Keskin, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 26, 2022
Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas CaptureHaoxin Mai, Tu C Le, Dehong Chen, et al.
Molecules (Basel, Switzerland)|February 13, 2025
Machine Learning Descriptors for CO<sub>2</sub> Capture MaterialsIbrahim B Orhan, Yuankai Zhao, Ravichandar Babarao, et al.
International Journal of Nanomedicine|November 7, 2019
Janus particles: recent advances in the biomedical applicationsTu C Le, Jiali Zhai, Wei-Hsun Chiu, et al.
Molecular Informatics|August 5, 2016
Illuminating Flash Point: Comprehensive Prediction ModelsTu C Le, Mathew Ballard, Phillip Casey, et al.
Pageof 4

Showing results (11-20 of 39) with videos related to

Sort By:
Pageof 4
The Journal of Physical Chemistry. B|April 17, 2019
Machine Learning Approaches for Further Developing the Understanding of the Property Trends Observed in Protic Ionic Liquid Containing SolventsDilek Yalcin, Tu C Le, Calum J Drummond, et al.
The Journal of Chemical Physics|November 10, 2009
The effect of interbranch spacing on structural and rheological properties of hyperbranched polymer meltsTu C Le, B D Todd, P J Daivis, et al.
Communications Chemistry|October 3, 2023
Accelerating the prediction of CO<sub>2</sub> capture at low partial pressures in metal-organic frameworks using new machine learning descriptorsIbrahim B Orhan, Tu C Le, Ravichandar Babarao, et al.
The Journal of Chemical Physics|February 26, 2009
Structural properties of hyperbranched polymers in the melt under shear via nonequilibrium molecular dynamics simulationTu C Le, B D Todd, P J Daivis, et al.
Molecules (Basel, Switzerland)|March 6, 2021
Review on the Use of Artificial Intelligence to Predict Fire Performance of Construction Materials and Their Flame RetardancyHoang T Nguyen, Kate T Q Nguyen, Tu C Le, et al.
ACS Applied Materials & Interfaces|December 20, 2021
Prediction of O<sub>2</sub>/N<sub>2</sub> Selectivity in Metal-Organic Frameworks via High-Throughput Computational Screening and Machine LearningIbrahim B Orhan, Hilal Daglar, Seda Keskin, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 26, 2022
Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas CaptureHaoxin Mai, Tu C Le, Dehong Chen, et al.
Molecules (Basel, Switzerland)|February 13, 2025
Machine Learning Descriptors for CO<sub>2</sub> Capture MaterialsIbrahim B Orhan, Yuankai Zhao, Ravichandar Babarao, et al.
International Journal of Nanomedicine|November 7, 2019
Janus particles: recent advances in the biomedical applicationsTu C Le, Jiali Zhai, Wei-Hsun Chiu, et al.
Molecular Informatics|August 5, 2016
Illuminating Flash Point: Comprehensive Prediction ModelsTu C Le, Mathew Ballard, Phillip Casey, et al.
Pageof 4