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Roy, Santanu

Publications and source records attributed to Roy, Santanu.

5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Hierarchical Ion Interactions in the Direct Air Capture of CO 2 at Air/Aqueous Interfaces

The direct air capture (DAC) of CO 2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly - ), an effective CO 2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly - and captured carbonaceous anions (HCO 3 - , CO 3 2 -, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Adsorption, Orientation, and Speciation of Amino Acids at Air–Aqueous Interfaces for the Direct Air Capture of CO 2

Amino acids make up a promising family of molecules capable of direct air capture (DAC) of CO 2 from the atmosphere. Under alkaline conditions, CO 2 reacts with the anionic form of an amino acid to produce carbamates and deactivated zwitterionic amino acids. The presence of the various species of amino acids and reactive intermediates can have a significant effect on DAC chemistry, the role of which is poorly understood. In this study, all-atom molecular dynamics (MD) based computational simulations and vibrational sum frequency generation (vSFG) spectroscopy studies were conducted to understand the role of competitive interactions at the air–aqueous interface in the context of DAC. We find that the presence of potassium bicarbonate ions, in combination with the anionic and zwitterionic forms of amino acids, induces concentration and charge gradients at the interface, generating a layered molecular arrangement that changes under pre- and post-DAC conditions. In parallel, an enhancement in the surface activity of both anionic and zwitterionic forms of amino acids is observed, which is attributed to enhanced interfacial stability and favorable intermolecular interactions between the adsorbed amino acids in their anionic and zwitterionic forms. The collective influence of these competitive interactions, along with the resulting interfacial heterogeneity, may in turn affect subsequent capture reactions and associated rates. Finally, these effects underscore the need to consider dynamic changes in interfacial chemical makeup to enhance DAC efficiency and to develop successful negative emission and storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole–dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. In conclusion, this study enables the ability to predict the structure–property relations for PAN and analogues with sustainable ab initio accuracy across scales.

36 MATERIALS SCIENCE↗