History
The company name ai-quanton (aiQ) may appear new, but its origins go back more than a decade. aiQ was founded in 2013 under exactly this name as a spin-off from Technical University Darmstadt . The founder, Walter Schäfer, together with his professor Cameron Tropea, developed the first prototypes based on the TSTOF technique [1], which were first presented at ACHEMA 2012 [2].
The first prototype was developed during PhD research between 2008 and 2012 [3]. Already at that time, the idea emerged to combine the TSTOF technique with artificial intelligence in order to detect not only droplets but also particles. However, due to the limited availability of practical AI tools at that time, aiQ initially followed a more classical technological approach.
Later, the company AOM-Systems was co-founded together with aiQ. Within this collaboration, aiQ developed measurement instruments based on the TSTOF technique, most notably known under the brand name SpraySpy®. These systems relied on classical signal analysis methods as described in [3,4].
With the increasing availability of modern AI technologies, aiQ began actively developing new AI-assisted analysis methods in 2021 [5–7]. These approaches remain based on the TSTOF measurement principle but incorporate machine learning techniques for the evaluation of optical scattering signals. This development led to new analysis platforms such as SprayQuantAI®, ParticleTensorAI®, and SprayConeAI®, which extend classical measurement techniques with modern AI-based data evaluation.
Today, aiQ is working on hybrid analysis approaches, combining classical signal processing with AI-based methods to address emerging scientific and industrial challenges in spray diagnostics and particle characterization.
Technology and Expertise
ai-quanton provides customized software and hardware solutions supporting TSTOF, LDT. We specialize in the research and development of optical measurement instruments for the characterization of solid particles and complex droplets in sprays. Our technologies are used both in scientific research and in industrial process monitoring, helping to bridge the gap between laboratory investigations and real production environments.
Based in Baden-Württemberg, Germany, our mission is to deliver integrated measurement and analysis solutions by combining precision hardware, dedicated software, and AI-based data analysis tools. Our AI technologies increase the effective information content of measurement data and are tailored to applications in fluid mechanics, aerodynamics, spray processes, and particle production.
The performance and reliability of our technologies are supported by numerous scientific publications and patent applications. Over the years, we have developed a modular system architecture that allows flexible instrument configurations and direct access to relevant measured variables.
Our software platforms are designed primarily as stand-alone systems but can also be seamlessly integrated into existing infrastructures. Through clearly defined interfaces, customers can independently connect our systems to gateways, cloud platforms, or external AI applications, ensuring flexibility and scalability.
Collaboration
Since its foundation in 2013 as a partner company of AOM-Systems, aiQ has continuously collaborated with universities and industrial partners on scientific publications and applied research projects.
With the growing availability of AI technologies, the company expanded its activities in 2021 to include the development of AI-assisted analysis tools for optical spray diagnostics. The introduction of platforms such as SprayQuantAI®, ParticleTensorAI®, and SprayConeAI® has significantly expanded the analytical capabilities of TSTOF, LDT, and camera-based measurement systems.
Below you will find a selection of universities and industrial partners with whom we have collaborated in scientific and applied research projects, reflecting our commitment to innovation, reliability, and long-term partnerships.
Team
Our interdisciplinary team combines expertise in mathematics, physics, computer science, and design to develop solutions in the field of optical measurement technology with AI-driven analysis.
AI-DEV: A young mathematician specializing in artificial intelligence, with a focus on applications in fluid dynamics and aerodynamics. (E. Goldberg)
HARDWARE: Computer scientist focused on the development of hardware solutions for optical measurement instruments (since 2015). (A. Sapega)
UI-DEV: Web developer and designer with experience since 2021 in developing user-friendly interfaces for optical measurement instruments. (S. Navalew)
EXPERIMENTAL: Physicist with many years of experience (since 2008) in optical sensing and the development of new measurement systems. (W. Schaefer)
Bibliography
[1] Schaefer, W., Li, L., Stegmann, P., & Terada, M. (2026). Technical Report on the TSTOF Measurement Method: Technical Basics, Historical Development, and Comparison with Other Laser-Based Measurement Methods. Photonics, 13(1), 56. https://doi.org/10.3390/photonics13010056
[2] TU Darmstadt. Größe und Geschwindigkeit von Partikeln und Tropfen messen. ACHEMA Daily, 2012, Frankfurt am Main, Germany.
[3] Schäfer, W. Time-Shift Technique for Particle Characterization in Sprays. PhD Thesis, Technische Universität Darmstadt, Darmstadt, Germany, 2012.
[4] Schäfer, W.; Tropea, C. The time-shift technique for measurement size of non-transparent spherical particles. In Proceedings of the International Conference on Optical Particle Characterization (OPC 2014), Tokyo, Japan, 10–14 March 2014.
[5] Tropea, C.; Schaefer, W. Method and Device for Determining Characteristic Properties of a Transparent Particle. US Patent Application US20170010197A1, 2 February 2017.
[6] Schaefer, W.; Li, L. Particle characterization by analyzing light scattering signals with a machine learning approach. Applied Optics, 2024, 63, 7701.
[7] Schaefer, W. Refractive index determination of dynamic droplets in a flow by analyzing light scattering signals with a machine learning approach. In Proceedings of THMT-25 Turbulence, Heat and Mass Transfer 11, Tokyo, Japan, 21–25 July 2025; Begellhouse: Danbury, CT, USA, 2025.mechanics.
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