Results 111 to 120 of about 12,416,883 (395)
Spartan Daily, February 5, 1988 [PDF]
Volume 90, Issue 5https://scholarworks.sjsu.edu/spartandaily/7664/thumbnail ...
San Jose State University, School of Journalism and Mass Communications
core +3 more sources
This study demonstrated single‐crystalline PbTiO3‐based memristors with atomically sharp interfaces, well‐ordered lattices, and minimal lattice mismatch. The devices exhibited an ON/OFF ratio exceeding 105, high stability, and rich resistance‐state modulation.
Haining Li +7 more
wiley +1 more source
Spartan Daily, April 21, 1988 [PDF]
Volume 90, Issue 50https://scholarworks.sjsu.edu/spartandaily/7709/thumbnail ...
San Jose State University, School of Journalism and Mass Communications
core +4 more sources
This study demonstrates that pulsed potential electrolysis significantly improves CO2 reduction performance on copper‐nitrogen doped carbon electrodes. The formation of cationic copper sites and metallic clusters as a function of applied intermittent potential leads to notable selectivity changes compared to potentiostatic reduction.
Dorottya Hursán +13 more
wiley +1 more source
Two‐dimensional electronic states are the foundation of modern semiconductor technology. Here, we report molecular‐beam epitaxy growth of fractional double perovskite, EuTa2O6. Reciprocal space mapping and transmission electron microscopy confirm a layered ordering of A‐site cations.
Tobias Schwaigert +15 more
wiley +1 more source
Accurate permeability prediction is essential for reservoir characterization, especially in building three-dimensional reservoir models. However, predicting permeability in the complex Tertiary reservoir/Ajeel oil field, with its different rock types ...
Vian M. Ahmed, Ayad A. Al-Haleem
doaj +1 more source
Spartan Daily, November 30, 1979 [PDF]
Volume 73, Issue 60https://scholarworks.sjsu.edu/spartandaily/6558/thumbnail ...
San Jose State University, School of Journalism and Mass Communications
core +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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 +7 more
wiley +1 more source
Spartan Daily, December 2, 1986 [PDF]
Volume 87, Issue 63https://scholarworks.sjsu.edu/spartandaily/7520/thumbnail ...
San Jose State University, School of Journalism and Mass Communications
core +2 more sources
A 3D disease model is developed using customized hyaluronic‐acid‐based hydrogels supplemented with extracellular matrix (ECM) proteins resembling brain ECM properties. Neurons, astrocytes, and tumor cells are used to mimic the native brain surrounding.
Esra Türker +16 more
wiley +1 more source

