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Sophia Space and Caltech Secure U.S. Patent for Space-Based Data Centers, Deepen R&D Program
Sophia Space said the patent supports modular orbiting systems that use solar power and deep-space cooling as it expands research with Caltech.
- On Thursday, July 30, 2026, Sophia Space Inc. and Caltech announced the issuance of U.S. Patent No. 12,679,564, covering architecture for large, modular space-based data centers.
- The patent stems from Caltech's Space Solar Power Project, which originally investigated wireless energy transmission to Earth before researchers pivoted to using deployable structures for orbital computing instead.
- Sophia Space developed the 'TILE' architecture, a modular, passively-cooled unit powered by solar energy; after raising $22 million, the company plans a 2027 demonstration aboard an Apex Nova satellite bus.
- Expanding their partnership, Caltech and Sophia Space are advancing thermal and structural technologies through a new research agreement supporting future orbiting data centers.
- Growing demand for AI inference at the edge makes processing data in space a decisive capability, enabling satellites to reduce latency and bandwidth reliance for commercial operations.
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Sophia Space and Caltech claim patent for space data centers
SAN FRANCISCO – Sophia Space announced the award July 30 of a patent, shared with the California Institute of Technology, covering large, modular space-based data centers. The patent, issued July […] The post Sophia Space and Caltech claim patent for space data centers appeared first on SpaceNews.
·Denver, United States
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Sophia Space and Caltech secure U.S. Patent for Space-Based Data Centers, Deepen R&D Program
PASADENA, Calif., July 30, 2026 /PRNewswire/ -- Sophia Space Inc., a portfolio company of Mandala Space Ventures, today announced the issuance of U.S. Patent No. 12,679,564, titled Space-Based Data Centers, which is jointly owned by Sophia Space and Caltech. The…
·Billings, United States
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Leaning Left2Leaning Right0Center13Last UpdatedBias Distribution87% Center
Bias Distribution
- 87% of the sources are Center
87% Center
13%
C 87%
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