# AI-Enabled Compact and Efficient Dynamic Light Scattering System for Precise Microparticle Sizing
## 4 Conclusions  
A low-cost and compact DLS system capable of overcoming the challenge of signal noise that is unmanageable by conventional methods was developed, with the detailed performance shown in Table 1. We acknowledge that directly comparing our manufacturing costs to the sales prices of commercial systems may not be entirely appropriate, as the latter includes significant markups beyond production costs. Since the exact production costs of commercial instruments are proprietary, we have assumed their manufacturing costs to be approximately one-fifth of their sales price, as suggested. Accordingly, we revised our comparison by estimating a hypothetical selling price for our device using a 5\(\times\) markup on its manufacturing cost, ensuring a fairer and more accurate evaluation. The AI DLS, priced at USD 4000, is significantly more affordable than the commercial DLS (USD 16,000) while demonstrating superior accuracy (1.82% average error vs. 2.01%) and  
Figure 5: (**a–e**) ACFs for five repeated measurements at particle diameters of 100 nm, 500 nm, 700 nm, 1000 nm, and 1500 nm, respectively. (**f**) PCA analysis demonstrating clear separation of ACFs for the five diameters. (**g**) Predicted diameters with Std and error for each diameter. (**h**) Comparative analysis of errors and measured diameters among SEM, AI-DLS, and commercial DLS systems. faster testing time (<12 s vs. <60 s). Additionally, its compact size (5 kg, 0.08 m\({}^{3}\)) makes it more portable and space-efficient compared to the commercial DLS (30 kg, 0.18 m\({}^{3}\)). Both systems share similar environmental requirements (temperature: 10-30 \({}^{\circ}\)C, humidity: 10-80%), repeatability (<1% error), laser parameters (633-635 nm, 2 mW), and sample cell compatibility (quartz and glass). However, their software capabilities differ significantly. The AI DLS integrates advanced machine learning modes (1D-CNN, 2D-CNN), offering cutting-edge analytical capabilities, while the commercial DLS provides classic models (NNLS, CONTIN) and supports exporting raw data for further analysis. Commercial DLS can measure both monodisperse and polydisperse microspheres, while our current method is limited to monodisperse measurements. However, by expanding our dataset and leveraging AI-based approaches, size distribution prediction can also be achieved in the future. Moreover, the commercial DLS uniquely supports both 90\({}^{\circ}\) dynamic and backward light scattering, offering flexibility for specialized applications. The AI DLS stands out for its affordability, speed, and innovative analysis tools. Future strategies to lower system costs may include: switching to a single-channel data acquisition card, utilizing standalone avalanche photodiodes with a separate amplification circuit instead of the full component set, and optimizing 3D printing designs to make components more compact, thereby reducing material usage and simplifying assembly processes. Additionally, as part of future developments, we plan to establish a new predictive model tailored to accurately determine the particle size distribution of microspheres. This model aims to extend the system's capabilities to handle polydisperse suspensions, enabling effective prediction and analysis of more complex samples. The commercial DLS, however, remains a strong option for traditional analysis methods and advanced scattering principles. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15041900/s1](https://www.mdpi.com/article/10.3390/app15041900/s1)]([https://www.mdpi.com/article/10.3390/app15041900/s1](https://www.mdpi.com/article/10.3390/app15041900/s1)), Figure S1: Raw signal, Kalman filtered signal, ACF curve of microspheres with diameters of 300 nm, 1200 nm and 1300 nm; Figure S2: deep learning effect of the raw signal; Figure S3: the software interface; Figure S4: The MAE versus the diameter.