Particle4X combines advanced computational imaging with proprietary physics-informed analytics to enable real-time, information-rich particle analysis. Our technology stack is designed to capture particles in their native environment, extract meaningful physical information from holograms, and convert those measurements into actionable insight for research and industry.
Digital Inline Holography
Digital inline holography (DIH) is the core imaging technology behind Particle4X. DIH records the interference pattern formed when light interacts with particles suspended in air or liquid, capturing rich optical information within a three-dimensional sample volume. These holograms can then be reconstructed to recover particle size, morphology, spatial location, and optical properties such as phase, enabling in situ analysis with substantially richer information than conventional imaging approaches.
Compared with conventional brightfield microscopy, DIH offers important advantages for particle characterization. In addition to morphology, reconstructed holograms can provide phase-related information linked to particle optical properties, which improves particle differentiability beyond methods that rely primarily on shape and appearance alone. DIH also does not require precise mechanical focusing and provides a much larger depth of field, making it well suited for high-throughput measurements across extended sample volumes. The technique is label-free, requires minimal sample preparation, and can be implemented in compact optical systems with stable calibration over long operating periods. By integrating DIH with advanced detection, reconstruction, and particle characterization workflows, Particle4X enables fast, scalable, and information-rich particle analysis for both industrial and scientific applications.
Physics-Informed AI Analytics
Particle4X pairs holographic imaging with proprietary physics-informed AI and high-performance computing algorithms to enable accurate, generalizable, and real-time hologram analysis. Our processing framework is designed to efficiently analyze holographic data while preserving the physical information required for reliable particle characterization. It is optimized for deployment across a wide range of hardware environments, from edge computing devices for field and embedded operation to multi-GPU servers for large-scale, high-throughput analysis.
These models support end-to-end analysis workflows, including particle detection, classification, and characterization of morphology and optical properties. By integrating physical modeling with neural-network-based inference and parallel computing, Particle4X delivers robust performance across diverse sample types and operating conditions. This computational foundation allows our platform to move beyond image reconstruction alone and provide actionable particle intelligence in real time.