The role of sulfur cycle in new particle formation: Cycloaddition reaction of SO3 to H2S

The chemistry of sulfur cycle contributes significantly to the atmospheric nucleation process, which is the first step of new particle formation (NPF). In the present study, cycloaddition reaction mechanism of sulfur trioxide (SO3) to hydrogen sulfide (H2S) which is a typical air pollutant and toxic gas detrimental to the environment were comprehensively investigate through theoretical calculations and Atmospheric Cluster Dynamic Code simulations. Gas-phase stability and nucleation potential of the product thiosulfuric acid (H2S2O3, TSA) were further analyzed to evaluate its atmospheric impact. Without any catalysts, the H2S + SO3 reaction is infeasible with a barrier of 24.2 kcal/mol. Atmospheric nucleation precursors formic acid (FA), sulfuric acid (SA), and water (H2O) could effectively lower the reaction barriers as catalysts, even to a barrierless reaction with the efficiency of cis-SA > trans-FA > trans-SA > H2O. Subsequently, the gas-phase stability of TSA was investigated. A hydrolysis reaction barrier of up to 61.4 kcal/mol alone with an endothermic isomerization reaction barrier of 5.1 kcal/mol under the catalytic effect of SA demonstrates the sufficient stability of TSA. Furthermore, topological and kinetic analysis were conducted to determine the nucleation potential of TSA. Atmospheric clusters formed by TSA and atmospheric nucleation precursors (SA, ammonia NH3, and dimethylamine DMA) were thermodynamically stable. Moreover, the gradually decreasing evaporation coefficients for TSA-base clusters, particularly for TSA-DMA, suggests that TSA may participate in NPF where the concentration of base molecules are relatively higher. The present new reaction mechanism may contributes to a better understanding of atmospheric sulfur cycle and NPF.

Aβ-protein polymerization in Alzheimer disease: Optimal control for nucleation parameter estimation

In this paper, we are interested in the modeling of Alzheimer's disease from the angle of the amyloid cascade hypothesis, where the pathogenic agent is the Aβ protein in its oligomeric form. The formation dynamics of this pathogenic form is modeled by a Becker-Doring type model where APP (Amyloid Precursor Protein) protein, after cleavage by specific enzymes, forms monomeric Aβ proteins, which, by polymerization and/or nucleation, lead to the formation of oligomeric Aβ. We propose an optimal control problem to estimate the rate of nucleation which seems to be at the base of this amyloid cascade hypothesis and for which no (experimental) measurement exists for the moment.

Machine learning insights into calcium phosphate nucleation and aggregation

In this study, we utilized machine learning interatomic potentials (MLIPs) to investigate the nucleation mechanisms of calcium phosphate, a critical component of bone and teeth. Our analysis encompassed the process from pre-nucleation stage to the growth of amorphous calcium phosphate (ACP) in solution. We observed fluctuations in free calcium ion concentration and tracked the formation of uniform clusters in the early nucleation phases, confirming the existence of pre-nucleation clusters (PNCs). The PNCs are characterized by the composition Ca2[(PO4)1.6(HPO4)(H2PO4)0.4] and predominantly exhibit a triangular structure formed by phosphate groups. This structure is not only the core of the short-range ordered units in ACP but also exhibits the structural characteristics of the fundamental building blocks of HAP. Importantly, these clusters interact dynamically with water molecules through hydrogen bonding and proton exchange, which is essential for their stability and growth. The gradual growth of these clusters occurs via ion attachment and cluster adsorption. This work provides insights into calcium phosphate mineralization, with implications for materials science and biomedical engineering, particularly in biomaterial synthesis. The application of MLIPs demonstrates a high-accuracy, efficient approach for simulating complex systems may advance our understanding of crystallization and biomineralization processes. STATEMENT OF SIGNIFICANCE: Calcium phosphate nucleation is crucial in biological mineralization and the synthesis of biomaterials, serving as a key aspect in the design of hydroxyapatite (HAP)-based biomaterials. However, the mechanisms of early nucleation remain unclear due to the complex ion-water interactions, which lead to rapid nucleation rates and small cluster sizes. This study combines MLIP with MD simulations to explore the nucleation process of calcium phosphate, revealing the transition from pre-nucleation to the formation of ACP. It clarifies the relationship between PNCs and the crystalline structure of HAP. This work addresses the knowledge gap regarding early-stage calcium phosphate nucleation and highlights the potential of MLIP in simulating complex ionic solutions, laying a solid foundation for AI-guided research in biological and biomedical materials.