http://propertyvectors.com
Impacts from R&D to Manufacturing with Atomic-Scale Modeling: Expert Modeling, Informatics, Computing in Materials and Chemistry
Exploring the use of atomic-scale modeling, but not sure where to start or ready to commit the investment on your own private cluster? Work with us to test the viability of your modeling needs, train your internal employees, and explore various cloud computing options.
The staff at Property Vectors have decades of experience working in industrial, start-up, and academic settings with customers in research and manufacturing settings. We know the limitations of the tools and methods and won't over promise.
Moving beyond materials design and discovery requires a multi-property vector approach. By considering a range of possible compounds, defects, and structures we try to reduce the number of surprises and iterations when struggling through R&D into production and manufacturing.
We can provide expert insight and recommendations, train your employees, or provide your own private materials and chemistry modeling contract research team depending upon your needs.
We designed computing infrastructure at Fortune 50 companies and used multiple cloud providers and supercomputing centers in our career. We understand the complex interplay of security, cost, and flexibility in computing options.
Company Details
- Founded
- -
- Address
- Castro St., Mountain View,ca 94041,united States
- Industry
- Research
- Website
- propertyvectors.com
- Keywords
- materials modeling, high performance computing, materials informatics, First Principles Modeling, Ab-initio Modeling, Molecular Dynamics, Local-orbital Techniques, Plane-Wave Techniques, Electronic Transport, Non-equilibrium Green's Function.
- HQ
- Mountain View, CA
- Competitors
- Mat3ra.com, Rowan, Nextmol.
Property Vectors Questions
Property Vectors's website is propertyvectors.com
Property Vectors's LinkedIn profile is https://www.linkedin.com/company/property-vectors
Property Vectors's industry is
Research
Property Vectors's categories are Research
Property Vectors's founding year is 2017
