web-based collaborative environment for materials design, modeling and informatics
cloud-based high-performance computing platform, up to 2-3x faster than incumbents
integrated support for high-fidelity multi-scale models and associated workflows
more virtual tests for materials discovery,
innovate faster than competition
shorter turnaround time for prototyping,
reduced time = direct savings
Emerging memory technology and TCAD can use high-fidelity and high-throughput first-principles modeling to speed up the selection of materials for next generation semiconductor devices.
Materials scientists in high productivity research area demonstrate how to use our scalable infrastructure to predict and assess the stability of lightweight metallic alloys.
Our end-to-end platform lets infastructure engineers, materials scientists and data scientists collaborate more efficiently and helps speed up the design of new compounds from atoms up.
Materials modeling today is an esoteric, albeit critical, discipline, hamstrung by a proliferation of specialized point tools, computational complexity, lack of standards, and an unmanaged explosion of data.
In order for the promise of materials modeling to be realized, the technology has to become easy to use, flexible and accessible. We think these goals are attainable now - and are already proving it, with examples listed here.
Here is what we believe:
- Faster, more precise systems for modeling cut the time-to-market for new materials and resulting products in many application areas
- Researchers must be able to exploit the best-in-class modeling tools for each type of simulation, whether they are intimately familiar with the tool or not
- Simulations deliver the most precise answers when modelers and experimentalists collaborate efficiently, using agreed standards
- Cloud computing is taking the lead in performance, scalability, and security for HPC workflows, including materials modeling
This is why Exabyte.io is building a cloud-native, modular, accessible and collaborative modeling platform.
Cloud HPC is the fastest-growing segment of HPC, and for good reasons. The vendors have the resources to offer instant access and scalability on the leading current technology. They also know security is central to their business and can afford the most reliable solutions, which is why companies now run critical functions such as HR, payroll, and finance in the cloud. The cloud service providers' lead will only extend over time helping to solve the computational complexity of materials modeling.
Modular and Accessible
Because of the computational complexity, no single developer has the best-in-class tools across all scales and physical-model types. Researchers want the flexibility to use the optimum tool for a specific analysis, without having to learn yet another new language and data format. Instead, a plug-in modular architecture will allow researchers to pick the best combination of tools, and get the job done faster. Data standards and an intuitive interface allow to control the ever-growing data and cut learning time, making the discipline less esoteric.
The way to improve any R&D process is to first define it and allow great minds to participate, build on what has been learned already, then provide feedback from the results achieved so the process can be improved. This means scientists need to be able to review and comment on each other's work, to define and refine workflows, and to engage experimentalists to evaluate the results. Instead of having modelers and experimentalists work independently and continue speaking different languages, exchanging information regularly lets teams achieve R&D goals faster and more accurately.
Materials modeling has the potential to speed the discovery of extraordinary new materials for many industries and applications. To do so, it must be set free from the ivory tower and in-house supercomputers, and become more widely accessible, easier to use, faster, and more precise.
This is Materials Modeling 2.0. This is Exabyte.
Do you share our vision? We'd love to hear what you think.
Contact us at email@example.com.
Exabyte.io is a cloud-based nanoscale modeling platform that accelerates research and development of new materials and helps speed up time to market. Exabyte.io allows scientists in the enterprise R&D units to reliably exploit state-of-the-art nanoscale modeling tools, collaborate and organize research in a single easy-to-use platform in order to make intelligent decisions faster.
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Timur conceived Exabyte.io in 2014, after obtaining a Ph.D. degree in physics at UC Berkeley under Marvin L. Cohen. Timur published 15 peer-reviewed articles on computational studies of materials cited over 200 times. His research was focused on high-fidelity first-principles simulation techniques for semiconductors and superconductors. Timur graduated with honors from Moscow Institute of Physics and Technology, is a regular reviewer of Physical Review Letters, speaks Russian and Tatar.
Mohammad is leading the development of the computational infrastructure since 2015, when he decided to merge his entrepreneurial efforts in building cloud supercomputers with Exabyte.io. He holds a Ph.D. degree in Telecommunication Engineering and has 10 years of experience in cloud computing including large-scale grid computing and on-premise infrastructure. His prior research was in resource management and allocation. Speaks Persian and plays Badminton.
Dominic joined Exabyte in 2018 bringing 25 years of experience building sales for new ventures, with a focus on bringing technology and software to enterprises. He has closed 8-figure deals worldwide, most recently at Zoomforth, developed technology and channel partnerships, participated in fundraising, and published over 30 articles and conference papers. Dominic holds an MBA from INSEAD and an MA in physics from Cambridge, speaks French, plays drums in an R&B band, and sculls competitively.
Professor of Physics at UC Berkeley. Author of over 800 technical publications and one of the world's most cited physicists. Recipient of numerous awards and distinctions. Shares wisdom on nanoscale simulation techniques.
Senior faculty scientist in the Materials Sciences Division at Lawrence Berkeley Laboratory. Professor of Physics at UC Berkeley. Globally recognized expert with h-index 124. Assists in developing methods for materials modeling.
Founder and leading mind behind OpenStack. Previously - CTO of NASA, founder and CEO of Nebula, Escapia and Netran. Providing guidance on business and technological aspects of cloud computing.
Founder and CTO of MemSQL. Previously at Facebook and Microsoft. Expert in distrubuted systems. Computer Science Ph.D., ACM ICPC winner. Providing guidance on business and technological aspects of big data. More here.
Professor of Materials Science at UT Dallas and one of the pioneers of multiscale modeling for nanomaterials. Co-founder of 3 material design companies. Published over 250 journal articles, with some highlighted in US President's Council of Advisors On Science And Technology.
Business incubator focused on accelerating startups whose revenue comes from enterprises, backed by: Draper Fisher Jurvetson, Khosla Ventures, US Venture Partners, Foundation Capital, Cisco Systems, SAP Ventures, and Salesforce.com.
Impulse VC is a seed stage venture capital firm headquartered in Moscow, Russia, with a global focus on technological internet companies. The set of limited partners of the firm includes well-known engineers and highly successful international businessmen.
Breakout Labs is a grant-making body operating as part of the Thiel Foundation (a philanthropic organization created by Peter Thiel). Breakout Labs gives grants for early-stage scientific research of radical or offbeat nature .
"We extract electronic band gaps and band structures with high precision for a diverse set of 71 semiconductors, from pure elements to ternary oxides and alloys. We find that for HSE and G0W0, the average relative error fits within 20%, whereas for conventional GGA it is 55%."
A team of researchers from Intermolecular Inc. compressed what would otherwise be 10 years of computing into under 2 days and screened 296 promising structural alloys for potential applications in automotive and aerospace fields.
Professor Adelstein at the San Francisco State University benchmarked Exabyte.io platform against a set of incumbents using atomistic simulations of solid-state lithium electrolytes, and found a 2-3x improvement in speed.
ITOCHU Techno-Solutions Corporation offers a comprehensive service package ranging from platform on-boarding and technical support to helping optimize the product utilization and consulting on specific research topics. More information is here.
Below is the list of institutional affiliations as submitted by users attempted to register in our platform. This list is included for informational purposes only and has no implication about any potential relationship between our company and the organizations included.
Security and privacy of your data is our first priority. We designed our product to the highest standards of data protection. Below we highlight some of the features that we adopt to keep your data safe.
Encryption in transfer with high-grade SSL/TLS
Encryption at rest with 256-bit AES and kernel-encrypted hard drives
Private simulations on isolated clusters protected by firewall
Secure and comprehensive key management system
Security features inherited from our cloud datacenters
Complete Data backups
Redundant highly-available storage system
Distributed high-performant systems architecture
and identity verification