Fiber-optic sensing · data analysis · AI
Fiber-optic sensing for high-temperature materials research
Calornet LLC is a scientific consulting and technology company in Rolla, Missouri. We provide fiber-optic distributed temperature sensing and material characterization, together with data analysis, machine learning, software and training, for universities and research companies.
What we do
From a measurement to something you can interpret
Fiber-optic sensing and material characterization
An optical fiber in contact with the material records temperature along its length, so you see how temperature varies through the sample rather than at a single point.
Data analysis and AI for temperature profiles
- Data analysis of temperature profiles
- Machine-learning and signal-processing models
- Software and dashboards
- Training and consulting
How it works
Temperature along the whole fiber
- An optical fiber is placed in direct contact with the material.
- It records temperature along its length, not at a single point.
- The resulting profile can show events such as recalescence, and where along the sample they occur.
Who it is for
Universities and research companies
Our services are intended for teams working on high-temperature materials synthesis, crystallization and critical minerals.
- High-temperature material synthesisSee ultra-high-temperature ceramics.
- Crystallization and solidificationA distributed profile can show recalescence and where it occurs along a sample: reading recalescence.
- Critical mineral processingRead the case for in-contact thermal data.
Latest articles
Sensing Beyond AI and Spatial Intelligence: The Extreme Physics Behind Tesla's 'Flying' Roadster
Elon Musk promised a flying car; the McGregor demo delivered mid-air kickflips. Here is the sub-millisecond sensor telemetry, reaction control physics, and underbody suction that made it possible.
Accelerating Sensor Intelligence: The Role of GPUs, Edge AI, and Parallel Computing
How parallel GPU architectures, high memory bandwidth, and edge accelerators bridge the gap between high-speed sensor acquisition and real-time industrial inference.
From G80 to Vera Rubin: Two Decades of Architectural Disruption in GPU Computing
Tracing the evolution of GPU architectures from the monolithic G80 unified shader revolution in 2006 to the multi-die Vera Rubin AI supercomputing platforms of 2026.
The Seven Eras of the GPU: From Fixed-Function Silicon to Neural Compute Engines
A comprehensive analysis of GPU evolution through 2026: tracing the seven distinct eras from hardware T&L and programmable shaders to neural rendering and multi-die architectures.
AI-Driven Sapphire Optical Fiber Sensors: Decoding Harsh Environment Distributed Sensing
How machine learning and physics-informed models overcome multimode modal dispersion and noise to unlock distributed sapphire fiber sensing above 1300°C.
The Multi-Gigawatt AI Bottleneck: What 600k GPUs Mean for Thermal Sensing and Liquid Cooling
Meta's multi-GW clusters and 600,000+ GPUs reveal the next physical frontier: why massive power density requires fiber-optic thermal monitoring and extreme-temperature power generation.
Free tools
Built for the work
- FBG calibration toolEstimate temperature from a fiber Bragg grating wavelength shift, with calibration curves for six optical fibers.
- Transformer explainerAn interactive visual explainer of how transformer models process text, compute self-attention and predict next tokens.
Tell us about your material
Tell us about your material, the temperature range you work in and what you need to learn from the data.