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New protein bridges chemical divide for 'seamless' bioelectronics devices

Life has always played by its own set of molecular rules. From the biochemistry behind the first cells, evolution has constructed wonders like hard bone, rough bark and plant enzymes that harvest light to make food.

Tokyo
Japan
Xiaodong-xu
Yuhei-hayamizu
Valerie-daggett
David-starkebaum
Mehmet-sarikaya
Technology-agency
Tokyo-institute-of-technology
National-institutes-of-health
Naval-research-laboratory
National-science-foundation-materials-genome-initiative

CENIC Recognizes CSU San Bernardino's High Performance Computing Program for Improving CSU Access to National Research Platform Resources

The High Performance Computing Program (HPCP) at CSU San Bernardino has been selected to receive the CENIC 2024 Innovations in Networking Award for Research Applications in recognition of its work supporting faculty who wish to avail themselves of.

Egypt
Stanford
California
United-states
San-bernardino
Dihmit
Aswan
Bryan-kraemer
Youngsu-kim
Samuel-sudhakar
El-hudi
Kate-liszka

CENIC Recognizes CSU San Bernardino's High Performance Computing Program for Improving CSU Access to National Research Platform Resources

CENIC Recognizes CSU San Bernardino's High Performance Computing Program for Improving CSU Access to National Research Platform Resources
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California
United-states
Dihmit
Aswan
Egypt
Stanford
San-bernardino
Bryan-kraemer
Kate-liszka
Youngsu-kim
Benjamin-becerra
El-hudi

Patterns Lead the Way to Far-from-Equilibrium Materials

Patterns Lead the Way to Far-from-Equilibrium Materials
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Australia
California
United-states
Juan-manuel-garc
Raphael-eduard-liesegang
Gerhard-ertl
Donald-mikulecky
Irving-epstein
Raphael-liesegang
Stanley-miller
Charles-darwin
Andrew-white

How Machine Learning can speed up material design, testing and manufacturing, ET Auto

Machine Learning: The conventional alloy design process is multistage and thus multivariable, leading to tremendous effort. Further, alloy design is also about meeting a well-defined target of properties like yield strength, ultimate tensile strength, fracture toughness, fatigue life etc. ML method can eliminate long hit-and-trial-based expensive methodology of material design to smart discovery and deployment. A tangible effort is going on across the globe to curate, capture, generate and manage data and to come up with algorithms to predict the next processes and materials.

Bombay
Maharashtra
India
New-delhi
Delhi
Department-of-mechanical-engineering
Materials-genome-imagen-lab
Associate-professor
Materials-genome
Mechanical-engineering
Machine-learning

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