Industries worldwide are facing increasing pressure for higher product quality, faster R&D cycles, and stricter regulatory compliance, particularly in fields relying on nanoparticle characterization. The rising complexity of advanced materials and biopharmaceuticals necessitates robust, efficient analytical tools. This technology directly addresses these trends by enhancing the reliability and speed of critical particle sizing, reducing waste, and streamlining quality assurance processes across global supply chains.
Automatically Eliminates Contaminant Noise: An information processing unit automatically identifies and removes scattered light noise caused by contaminants in liquid samples, significantly enhancing measurement accuracy.
Reduces Measurement Cycles by 50%, Boosts Efficiency: Measurements that previously required multiple repetitions can now be accurately completed in a single run, substantially reducing re-measurement effort and time, and improving operational efficiency.
Rapid Results with Automated Analysis Program: Based on the photon arrival time list, the system automatically processes everything from noise removal to particle size calculation, accelerating R&D cycles.
This patent protects a robust noise removal technology for dynamic light scattering measurements, encompassing a broad range of claims across 12 items. It covers an apparatus, method, and program for accurately measuring particle size and distribution in liquid samples by automatically identifying and eliminating contaminant-induced noise. The patent successfully navigated examination, demonstrating a strong, difficult-to-invalidate right.
This patent primarily covers algorithmic noise removal for DLS. White space exists in developing integrated multi-modal particle characterization systems, applying similar noise reduction principles to other optical sensing methods, or innovating DLS hardware components for enhanced signal-to-noise ratios.
Implementing this technology could reduce re-measurement due to errors and sample preparation time. For example, assuming a 20% reduction in re-measurement rates and a 30-minute reduction per measurement, a company performing 5,000 measurements annually could save 5,000 measurements × (20% × 30 min + 30 min) = 5,000 measurements × 36 min = 3,000 hours of annual labor. At an estimated labor cost of ~$65/hour (AI est.), this translates to an annual direct cost reduction of ~$200K (AI est.).
X: Measurement Accuracy and Reliability
Y: Operational Efficiency and Cost Advantage