Data for PhD thesis: Taming Crystallization with Light

Crystallization is one of the most widely used purification and separation processes applied in a multitude of industries such as pharmaceuticals, food &amp; beverages, agriculture, and fine chemicals. However, the initial step of the crystallization process, nucleation, is still poorly understood and highly stochastic. As a result, most crystallization processes lack proper control over the properties of the crystals produced. Among many techniques for achieving better control over the nucleation process, the application of non-photochemical laser induced nucleation (NPLIN) has gathered significant interest. This is because of its potential to improve product quality in crystallization processes by directly controlling the nucleation rate, both spatially and temporally. Additionally, NPLIN can induce crystallization in solutions that would otherwise take a long time to nucleate, offering a unique advantage over traditional methods. However, despite its promising capabilities, NPLIN is not widely used in practice yet. The fundamental mechanism behind NPLIN is not fully understood, making it unclear how it should be applied effectively in practice and for which systems NPLIN could be beneficial.<br>This Ph.D. project aims to delve into the fundamental mechanisms of NPLIN, by examining how specific laser and solution parameters influence nucleation kinetics, leveraging innovative experimental setups. Laser parameters being studied include laser-exposed volume, laser irradiation position, laser intensity, and laser wavelength, and solution parameters include supersaturation levels, solution filtration, and the presence of impurities or dopants, particularly nanoparticles.The thesis begins with a comprehensive review of the experimental and computational literature on NPLIN. It then presents a detailed study on the effect of the laser-exposed volume and laser irradiation position on the nucleation probability within partly illuminated supersaturated aqueous potassium chloride solutions. An increase in the laser-exposed volume resulted in a higher nucleation probability and a higher number of crystals per nucleated sample. Furthermore, laser irradiation, particularly through the air/solution interface, not only enhances nucleation probability but also influences the formation of different crystal morphologies. These observations are partly explained by the Nanoparticle Heating mechanism and the Dielectric Polarization model (Chapter 2).<br>The research then transitions to a microfluidic platform, which allows for high-throughput and crystallization detection using the deep learning method. This innovative approach addresses the need for large data sets in NPLIN research, which has been a significant challenge due to the manual nature of traditional experiments. The study examines the effects of laser intensity, wavelength, supersaturation, solution filtration, and intentional doping on nucleation probability in supersaturated potassium chloride solutions. Higher laser intensities and increased supersaturation significantly enhance nucleation probabilities. The laser wavelength effect was only observed for 355 nm at higher laser intensities. Solution filtration suppresses the NPLIN effect, whereas the addition of nanoparticles as dopants into the solution not only increases the NPLIN probabilities but also affects the crystal morphology. The results highlight the importance of impurities in the solution and support the hypothesis that nanoparticle or impurity heating could be the key mechanism in understanding NPLIN (Chapter 3).<br>The study finally investigated the effects of solution filtration, laser intensity, and nanoparticle properties including nanoparticle concentration and material on NPLIN probability in supersaturated aqueous urea solutions. The study highlights the significant role of impurities in NPLIN, demonstrating that doping with different nanoparticle materials leads to varied nucleation probabilities. In particular, gold nanoparticles were found to enhance nucleation more effectively than silica nanoparticles. Additionally, it was observed that NPLIN probabilities followed a Poisson distribution to changes in nanoparticle concentration and laser intensity respectively. The findings in this chapter enhance our understanding of the critical role of impurities in comprehending the NPLIN mechanism (Chapter 4).

结晶是制药、食品饮料、农业以及精细化学品等众多行业中应用最为广泛的纯化与分离工艺之一。然而，结晶过程的起始步骤——成核（nucleation）仍未被充分理解且具有高度随机性。因此，绝大多数结晶工艺难以对所制备晶体的性能实现精准调控。在诸多可实现成核过程精准调控的技术中，非光化学激光诱导成核（non-photochemical laser induced nucleation, NPLIN）受到了广泛关注。这是因为其可通过在空间与时间维度上直接调控成核速率，有望提升结晶工艺的产品质量。此外，NPLIN可在原本需漫长诱导期才能发生成核的溶液中诱导结晶，相较传统方法具备独特优势。然而，尽管NPLIN具备可观的应用潜力，目前仍未在工业界得到广泛应用。其背后的核心机理尚未被完全阐明，这导致我们无法明确其实际应用的有效方式，以及适配的适用体系。<br>本博士项目旨在借助创新实验装置，通过探究特定激光参数与溶液参数对成核动力学的影响，深入解析NPLIN的核心机理。所研究的激光参数包括激光作用体积、激光辐照位置、激光强度与激光波长；溶液参数则包括过饱和度水平、溶液过滤处理以及杂质或掺杂剂（尤其是纳米颗粒）的存在情况。本论文首先对NPLIN相关的实验与计算类文献开展了全面综述。随后针对部分辐照的过饱和氯化钾水溶液体系，详细探究了激光作用体积与激光辐照位置对成核概率的影响。研究发现，激光作用体积的增大可提升成核概率，且每个成核样品中的晶体数量也随之增加。此外，激光辐照（尤其是通过气液界面进行辐照时）不仅可提升成核概率，还会对不同晶体形貌的形成产生影响。上述实验现象可通过纳米颗粒热效应机理与介电极化模型得到部分解释（第2章）。<br>随后本研究转向微流控平台，该平台可借助深度学习方法实现高通量的结晶检测。这一创新方法解决了NPLIN研究中对大规模数据集的需求问题——而传统实验因依赖人工操作，一直难以满足这一需求。本研究针对过饱和氯化钾溶液体系，探究了激光强度、波长、过饱和度、溶液过滤处理以及有意掺杂对成核概率的影响。研究结果显示，更高的激光强度与更高的过饱和度可显著提升成核概率。仅在较高激光强度下，355 nm波长的激光才表现出显著的波长效应。溶液过滤处理会抑制NPLIN效应，而向溶液中添加纳米颗粒作为掺杂剂不仅可提升NPLIN成核概率，还会改变晶体形貌。本研究结果凸显了溶液中杂质的重要性，并支持了“纳米颗粒或杂质热效应可能是解析NPLIN核心机理的关键”这一假说（第3章）。<br>最后，本研究针对过饱和尿素水溶液体系，探究了溶液过滤处理、激光强度以及纳米颗粒属性（包括纳米颗粒浓度与材质）对NPLIN成核概率的影响。本研究再次强调了杂质在NPLIN过程中的关键作用，结果表明掺杂不同材质的纳米颗粒会导致成核概率出现差异。具体而言，金纳米颗粒相较二氧化硅纳米颗粒可更有效地提升成核概率。此外，研究发现NPLIN成核概率分别随纳米颗粒浓度与激光强度的变化符合泊松分布。本章的研究结果进一步加深了我们对杂质在解析NPLIN机理中关键作用的认知（第4章）。