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Abstract Under-oil open microfluidic system, utilizing liquid-liquid boundaries for confinements, offers inherent advantages including clogging-free flow channels, flexible access to samples, and adjustable gas permeation, making it well-suited for studying multi-phase chemical reactions that are challenging for closed microfluidics. However, reports on the novel system have primarily focused on device fabrication and functionality demonstrations within biology, leaving their application in broader chemical analysis underexplored. Here, we present a visualization-enhanced under-oil open microfluidic system for in situ characterization of multi-phase chemical reactions with Raman spectroscopy. The enhanced system utilizes a semi-transparent silicon (Si) nanolayer over the substrate to enhance visualization in both inverted and upright microscope setups while reducing Raman noise from the substrate. We validated the system’s chemical stability and capability to monitor gas evolution and gas-liquid reactions in situ. The enhanced under-oil open microfluidic system, integrating Raman spectroscopy, offers a robust open-microfluidic platform for label-free molecular sensing and real-time chemical/biochemical process monitoring in multi-phase systems. 

In this work, we propose a linear machine learning force matching approach that can directly extract pair atomic interactions from ab initio calculations in amorphous structures. The local feature representation is specifically chosen to make the linear weights a force field as a force/potential function of the atom pair distance. Consequently, this set of functions is the closest representation of the ab initio forces, given the two-body approximation and finite scanning in the configurational space. We validate this approach in amorphous silica. Potentials in the new force field (consisting of tabulated Si–Si, Si–O, and O–O potentials) are significantly different than existing potentials that are commonly used for silica, even though all of them produce the tetrahedral network structure and roughly similar glass properties. This suggests that the commonly used classical force fields do not offer fundamentally accurate representations of the atomic interaction in silica. The new force field furthermore produces a lower glass transition temperature (Tg ∼ 1800 K) and a positive liquid thermal expansion coefficient, suggesting the extraordinarily high Tg and negative liquid thermal expansion of simulated silica could be artifacts of previously developed classical potentials. Overall, the proposed approach provides a fundamental yet intuitive way to evaluate two-body potentials against ab initio calculations, thereby offering an efficient way to guide the development of classical force fields. 

Short-timescale atomic rearrangements are fundamental to the kinetics of glasses and frequently dominated by one atom moving significantly (a rearrangement), while others relax only modestly. The rates and directions of such rearrangements (or hops) are dominated by the distributions of activation barriers ( E act ) for rearrangement for a single atom and how those distributions vary across the atoms in the system. We have used molecular dynamics simulations of Cu 50 Zr 50 metallic glass below T g in an isoconfigurational ensemble to catalog the ensemble of rearrangements from thousands of sites. The majority of atoms are strongly caged by their neighbors, but a tiny fraction has a very high propensity for rearrangement, which leads to a power-law variation in the cage-breaking probability for the atoms in the model. In addition, atoms generally have multiple accessible rearrangement vectors, each with its own E act . However, atoms with lower E act (or higher rearrangement rates) generally explored fewer possible rearrangement vectors, as the low E act path is explored far more than others. We discuss how our results influence future modeling efforts to predict the rearrangement vector of a hopping atom.