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DOE OSTI2020

Probing non-standard neutrino interactions with supernova neutrinos at Hyper-K

Non-standard neutrino self interactions (NSSI) could be stronger than Fermi interactions. We investigate the ability to constrain these four-neutrino interactions by their effect on the flux of neutrinos originating from a galactic supernova. In the dense medium of a core collapse supernova, these new self interactions can have a significant impact on neutrino oscillations, leading to changes at the flavor evolution and spectra level. We use simulations of the neutrino flux from a 13 solar mass, core collapse supernova at 10 kpc away, and numerically propagate these neutrinos through the stellar medium taking into account vacuum/MSW oscillations, SM ν – ν scattering as well as ν – ν interactions that arise from NSSI. We pass the resulting neutrino flux to a simulation of the future Hyper-Kamiokande detector to see what constraints on NSSI parameters are possible when the next galactic supernova becomes visible. We find that these constraints depend strongly on the neutrino mass hierarchy and if the NSSI is flavor-violating or preserving. Sensitivity to NSSI in the normal hierarchy (NH) at Hyper-K is limited by the experiment’s ability to efficiently detect ν e , but deviations from no NSSI could be seen if the NSSI is particularly strong. In the inverted hierarchy (IH) scenario, Hyper-K can significantly improve constraints on flavor-violating NSSI down to O(10 –1 )G F .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Higher-order interaction effects among operating conditions and feedstocks shape reactor microbiomes and fatty acid production profiles

Arrested anaerobic digestion (AAD) offers a promising route for producing fatty acids (FAs) from organic residues, yet optimal conditions for selectively generating medium-chain fatty acids (MCFAs) remain poorly defined. Here, we systematically evaluated the main and interaction effects of pH (5, 7, 9), feedstock (food waste, manure), temperature (35 and 45 °C), and inoculum source on microbiome composition and FA production. Anaerobic digester sludge and a novel bison rumen inoculum were compared. Significant higher-order interactions among operating parameters governed FA profiles and microbiome structure. Butyric acid production was driven by a three-way interaction among pH, feedstock, and temperature (p < 0.001), with maximum concentrations achieved in food waste reactors at pH 5.0 and 35 °C (1.2 ± 0.1 g L −1 with sludge and 1.1 ± 0.3 g L −1 with rumen). MCFA production exhibited significant four-way interactions (p < 0.1 to p < 0.001). At 45 °C and pH 5.0, inoculum source tuned MCFA selectivity: sludge favored pentanoic acid (0.4 ± 0.1 g L −1 ), whereas rumen favored hexanoic and heptanoic acids (up to 0.4 ± 0.2 g L −1 ). Manure reactors produced < 0.2 g L −1 MCFAs under all conditions. Genera, including Megasphaera, Prevotella, and Lactobacillus, were associated with production of specific MCFAs. PICRUSt2-based pathway predictions were consistent with MCFA production patterns and suggested a potential role for lactic acid–driven chain elongation pathways. This study provides insights into how interacting operating conditions shape AAD microbiomes, their FA profiles, and advances the trajectory of research aimed at engineering robust and controllable microbiomes for waste valorization.

09 BIOMASS FUELS↗

DOE OSTI2021

Evaluating the benefits of kinetic Monte Carlo and microkinetic modeling for catalyst design studies in the presence of lateral interactions

Popular computational catalyst design strategies rely on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends. The main benefit of this approach is related to the inherent dimensionality reduction of the large material space to just a few catalyst descriptors. Conversely, it is well documented that a small set of descriptors is insufficient to capture the intricacies and complexities of a real catalytic system. The inclusion of coverage effects through lateral adsorbate-adsorbate interactions can narrow the gap between simplified descriptor predictions and real systems, but mean-field MKMs cannot properly account for local coverage effects. This shortcoming of the mean-field approximation can be rectified by switching to a lattice-based kinetic Monte Carlo (kMC) method using cluster expansion representation of adsorbate–adsorbate lateral interactions. Using the prototypical CO oxidation reaction as an example, we critically evaluate the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. Here, the mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, the MKM approach does provide a better entry point for computational catalyst design.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗

DOE OSTI2021

12 C(e,e'pN) measurements of short range correlations in the tensor-to-scalar interaction transition region

High-momentum configurations of nucleon pairs at short-distance are probed using measurements of the $^{12}$C$(e,e'p)$ and $^{12}$C$(e,e'pN)$ reactions (where $N$ is either $n$ or $p$), at high-$Q^2$ and $x_B>1.1$. The data span a missing-momentum range of 300--1000 MeV/c and are predominantly sensitive to the transition region of the strong nuclear interaction from a Tensor to Scalar interaction. The data are well reproduced by theoretical calculations using the Generalized Contact Formalism with both chiral and phenomenological nucleon-nucleon ($NN$) interaction models. This agreement suggests that the measured high missing-momentum protons up to $1000$ MeV/c predominantly belong to short-ranged correlated (SRC) pairs. The measured $^{12}$C$(e,e'pN)$ / $^{12}$C$(e,e'p)$ and $^{12}$C$(e,e'pp)$ / $^{12}$C$(e,e'pn)$ cross-section ratios are consistent with a decrease in the fraction of proton-neutron SRC pairs and increase in the fraction of proton-proton SRC pairs with increasing missing momentum. This confirms the transition from an isospin-dependent tensor $NN$ interaction at $\sim 400$ MeV/c to an isospin-independent scalar interaction at high-momentum around $\sim 800$ MeV/c as predicted by theoretical calculation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Synergetic Effects of Soil Organic Matter Components During Interactions with Minerals

Mineral-associated soil organic matter (SOM) is critical for stabilizing organic carbon and mitigating climate change. However, mineral-SOM interactions at the molecular scale, particularly synergetic adsorption through organic-organic interaction on the mineral surface known as organic multilayering, remain poorly understood. This study investigates the impact of organic multilayering on mineral-SOM interactions, by integrating macroscale experiments and molecular-scale simulations that assess the individual and sequential adsorption of major SOM compounds – lauric acid (lipid), pentaglycine (amino acid), trehalose (carbohydrate), and lignin onto soil minerals. Ferrihydrite, Al-hydroxide, and calcite are exposed to SOM compounds to determine adsorption affinities and binding energies. Results show that lauric acid has 20-40 times higher K d than pentaglycine, following the order K d (ferrihydrite) > K d (Al-hydroxide) >> K d (calcite). Molecular-scale simulations confirm that lauric acid has a higher binding energy (30.8 kcal/mol) on ferrihydrite than pentaglycine (6.0 kcal/mol), attributed to lipid hydrophobicity. The lower binding energy of pentaglycine results from its hydrophilic amide groups, facilitating partitioning into water. Sequential experiments examine how the first layer of lipid or amino acid affects the adsorption of carbohydrate/lignin, which show little or no individual adsorption affinities. Macroscale results reveal that lipid and amino acid adsorption induce ferrihydrite particle repulsion increasing reactive surface area and enhancing carbohydrate/lignin adsorption independently and synergistically through organic multilayering. Molecular-scale results reveal that amino acid adsorbed on ferrihydrite interacts more readily with lignin macroaggregates (preformed in solution) than with individual lignin units, indicating organic multilayering via H-bonding. Further, these findings reveal the molecular mechanisms of SOM-mineral interactions, crucial for enhancing soil carbon stabilization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

First-Principles Study of Interaction between Molecules and Lewis Acid Zeolites Manipulated by Injection of Energized Charge Carriers

Metal dopants in Lewis acid zeolites can be applied to manipulate the interaction between the active sites and molecular reactants. However, only a few elements can be introduced into the zeolite framework to generate strong Lewis acid sites. In this study, we propose an alternative approach to tune the interaction between zeolite and molecules by introducing energized charge carriers that are photoexcited in a complex of plasmonic metal and zeolites. Here, through density functional theory (DFT) calculations, we show that although the energized electrons do not impact the adsorption of ammonia, which is used as a probe molecule, on Zr- and Si-BEA, ammonia’s heat of adsorption can be reduced up to 60% on Sn-BEA and 20% on Ti-BEA, respectively, because of the localized population of the electrons at the Sn and Ti center. This most pronounced effect in Sn-BEA is attributed to the Sn-induced midgap states and the strong electronegativity of Sn atoms. In contrast, the energized holes can strengthen the interaction between zeolites and ammonia by at least 10%. Particularly, if an energized hole is present in the system, the heat of adsorption of ammonia within Si-BEA can increase 3-fold, shifting from weak to moderate interaction. We find that, similar to closed sites, the effect of energized charge carriers can also be extended to open sites of Lewis acid zeolites. Our study provides fundamental insights for unlocking the potentials of integrating plasmonic metals with zeolites and brings an additional degree of control to tune the interfacial interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Improved Treatment of 1–4 Interactions in Force Fields for Molecular Dynamics Simulations

Traditional force fields commonly use a combination of bonded torsional terms and empirically scaled nonbonded interactions to capture 1-4 energies and forces of atoms separated by three bonds in a molecule. While this approach can yield accurate torsional energy barriers, it often leads to inaccurate forces and erroneous geometries and creates an interdependence between dihedral terms and nonbonded interactions, complicating parametrization and reducing transferability. Here, in this paper, we demonstrate that 1-4 interactions can be accurately modeled using only bonded coupling terms, eliminating the need for arbitrarily scaled nonbonded interactions altogether. Furthermore, by leveraging the automated parametrization capabilities of the Q-Force toolkit, we efficiently determine the necessary coupling terms without the need for manual adjustment. Our approach is first validated on a range of small molecule systems, encompassing both flexible and rigid structures, and shows a significant improvement in force field accuracy, obtaining subkcal/mol mean absolute error for every molecule tested. We further extend the bonded-only model for 1-4 interactions to Amber ff14sb, CHARMM36, and OPLS-AA force fields to reproduce ab initio gas and implicit solvent ϕ,ψ surfaces of alanine dipeptide.

Abdullah, Aalim S. [University of California, Berk↗

DOE OSTI2026

Assessing the Limitations of Self-Interaction-Corrected Functionals for Describing the Hydrated Electron

Simulating the hydrated electron using density functional theory is challenging due to the prevalence of self-interaction error in standard functionals. Hybrid functionals like PBEh(40) can reasonably describe the chemistry of an excess electron in water and partially mitigate self-interaction error by incorporating exact Hartree–Fock exchange, but they are computationally expensive making them impractical for large-scale and long-time ab initio molecular dynamics simulations. Explicit self-interaction correction schemes that are applied on an orbital-by-orbital basis offer a potential alternative when the correction is limited to the singly occupied molecular orbital obtained with a generalized gradient approximation functional. Here, we examine whether the Perdew–Zunger self-interaction correction scheme applied to the revPBE functional can provide a computationally efficient and physically sensible alternative to PBEh(40) for the hydrated electron. We find that functionals incorporating a self-interaction correction scheme should be viewed with caution when applied to the hydrated electron and its reactivity. Furthermore, we show that it is critical to consider extensive sampling and diverse chemical environments when validating their performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Probing orientation-specific charge-dipole interactions between hexafluoroisopropanol and halides: A joint photoelectron spectroscopy and theoretical study

The interactions between hexafluoroisopropanol (HFIP) and halogen anions X? (F?, Cl?, Br?, and I?) have been investigated by negative ion photoelectron spectroscopy (NIPES) and ab initio calculations. The measured NIPE spectrum of each [HFIP·X]? (X = Cl, Br, and I) complex shows the identical pattern to the corresponding X? by shifting to the high electron binding energy side, indicative of formation of [HFIP···X?] structure, in which X? interacts with HFIP via charge-dipole interactions. However, the spectrum of [HFIP·F]? appears completely different from that of F?, and is more similar to the spectrum of the deprotonated HFIP anion (HFIP?H?). The geometry and electron density calculations indicate that a neutral HF molecule is formed upon HFIP interacting with F? via proton transfer, rendering a stable structure of [HFIP?H···HF]?. Two conformers of [HFIP?H·HF]? with HFIP being in synperiplanar and antiperiplanar configurations, respectively, are observed, providing direct experimental evidences to show the distinctly different and orientation-specific interactions between HFIP and halide anions.

Wang, Lei↗

DOE OSTI2021

Behavior of Water Near Multimodal Chromatography Ligands and Its Consequences for Modulating Protein–Ligand Interactions

Multimodal chromatography is a powerful approach for purifying proteins that uses ligands containing multiple modes of interaction. Recent studies have shown that selectivity in multimodal chromatographic separations is a function of the ligand structure and geometry. Here, we performed molecular dynamics simulations to explore how the ligand structure and geometry affect ligand–water interactions and how these differences in solution affect the nature of protein–ligand interactions. Our investigation focused on three chromatography ligands: Capto MMC, Nuvia cPrime, and Prototype 4, a structural variant of Nuvia cPrime. First, the solvation characteristics of each ligand were quantified via three metrics: average water density, fluctuations, and residence time. We then explored how solvation was perturbed when the ligand was bound to the protein surface and found that the probability of the phenyl ring dewetting followed the order: Capto MMC > Prototype 4 > Nuvia cPrime. To explore how these differences in dewetting affect protein–ligand interactions, we calculated the probability of each ligand binding to different types of residues on the protein surface and found that the probability of binding to a hydrophobic residue followed the same order as the dewetting behavior. This study illustrates the role that wetting and dewetting play in modulating protein–ligand interactions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Modeling Interactions within and between Peptide Amphiphile Supramolecular Filaments

Many peptides are able to self-assemble into one-dimensional (1D) nanostructures, such as cylindrical fibers or ribbons of variable widths, but the relationship between the morphology of 1D objects and their molecular structure is not well understood. Here, we use coarse-grained molecular dynamics (CG-MD) simulations to study the nanostructures formed by self-assembly of different peptide amphiphiles (PAs). The results show that ribbons are hierarchical superstructures formed by laterally assembled cylindrical fibers. Simulations starting from bilayer structures demonstrate the formation of filaments, whereas other simulations starting from filaments indicate varying degrees of interaction among them depending on chemical structure. These interactions are verified by observations using atomic force microscopy of the various systems. The interfilament interactions are predicted to be strongest in supramolecular assemblies that display hydrophilic groups on their surfaces, while those with hydrophobic ones are predicted to interact more weakly as confirmed by viscosity measurements. The simulations also suggest that peptide amphiphiles with hydrophobic termini bend to reduce their interfacial energy with water, which may explain why these systems do not collapse into superstructures of bundled filaments. The simulations suggest that future experiments will need to address mechanistic questions about the self-assembly of these systems into hierarchical structures, namely, the preformation of interactive filaments vs equilibration of large assemblies into superstructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Factors Influencing Preferential Anion Interactions during Solvation of Multivalent Cations in Ethereal Solvents

Most multivalent secondary batteries have employed electrolytes composed of cyclic ether solvents such as tetrahydrofuran or linear glycol ether solvents (glymes) such as 1,2-dimethoxyethane (G1). A robust understanding of multivalent cation solvation tendencies in these classes of solvents provides insight into corresponding structure–property relationships which, in turn, promotes the design and discovery of improved electrolytes. In this work, our goal is to systematically address how electrolyte constituent properties, namely, ether solvent structure and dication size, direct the solvation interactions of divalent electrolytes and their resultant properties. This study utilizes pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy in conjunction with Raman spectroscopy and ionic conductivity measurements to elucidate the preferential interactions between multivalent cations, anions, and solvent molecules along with their correlated ion dynamics. These investigations incorporate two representative divalent cations (Ca 2+ and Zn 2+ ) as well as two ethereal solvent representatives from both the cyclic ether and glyme structural classes. The results reveal that anions coordinate more readily with divalent cations in cyclic ethers than in glymes. Furthermore, the coordination of the anions with Ca 2+ , i.e., contact-ion pair (CIP) formation is more pronounced than with Zn 2+ in a glyme solvent of limited chain length (G1), providing insight into cation size effects that are important for translating solvation behavior across various multivalent electrolytes. Importantly, we find that specific anion coordination is more strongly controlled by solvent structure than by salt concentration in the practical range of 0.1–0.5 M. However, simply reducing these inner-sphere inter-ionic interactions by changing solvent structure does not necessarily de-correlate ionic motion. Instead, concentration-dependent changes in molar ionic conductivity suggest that second-shell interactions, i.e., solvent separated ion pairs (SSIPs), are prevalent in these electrolytes and that the solution dielectric constant, which is increased by the presence of dipolar ion pairs, is critical for controlling these interactions. These findings thus provide a basis for understanding the physical chemistry of multivalent battery electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Modulating Interactions between Molten Polystyrene and Porous Solids Using Atomic Layer Deposition

Understanding and modulating the interactions between molten polymers and porous solids is important for numerous processes and phenomena including catalytic conversion of polymers and fabrication of nanocomposites and nanostructured materials. Although changing the surface composition of pores would enable modulation of interactions between polymer and nanoporous solids, it is challenging to achieve such a control without inducing significant changes to the size and structure of nanopores. In this work, we demonstrate that the interactions between molten polystyrene (PS) and disordered packings of SiO 2 nanoparticles (NPs) can be modulated by changing the surface composition of the NPs using atomic layer deposition (ALD). A disordered packing of silica NPs is modified with varying surface coverages of TiO 2 , WO 3 and CaCO 3 , with coverages estimated by the mass gain and the refractive index change of NP packings. Based on the time required to fully infiltrate these ALD-modified NP packings via capillarity, the contact angles for PS on different surfaces prepared via ALD are determined. The contact angle gradually changes from that of pure SiO 2 to that of the fully covered surfaces. The contact angles for PS on SiO 2 , TiO 2 , WO 3 and CaCO 3 are found to be 20°, 62°, 70° and 10°, respectively. Interestingly, the contact angles and interfacial energies between PS and the ALD-modified surfaces do not correlate strongly with the water contact angle of these surfaces; thus, caution must be exercised in predicting how a polymer would wet or interact with porous solids solely based on their hydrophilicity. Furthermore, the method presented in this work can be extended to study the interactions between a wide range of polymers and surfaces in porous media, which will have important implications for designing new catalytic materials for polymer upcycling reactions as well as novel NP-polymer composite films and membranes with enhanced mechanical and transport properties.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Tuning Transport via Interaction Strength in Cationic Conjugated Polyelectrolytes

Tuning polymer-ion interaction strength is critical for balancing ion solvation and transport in solid polymer electrolytes for battery applications. In mixed Li + /electron conducting systems for improved battery binders, the design space is further complicated by seemingly opposing design rules for electron and ion conducting polymers. Conjugated polymers functionalized with cationic side chains have demonstrated high ionic conductivity, lithium transport, and electronic conductivity by combining long-range polymer ordering with diffuse ion interactions. Herein, we demonstrate a family of mixed conducting polythiophenes functionalized with a range of cationic side chains, namely imidazolium, trimethylammonium, and ammonium groups. The strength of ionic interactions and structure of the side chains govern lithium-selective transport, resulting in high Li + conductivity (~10 –4 S/cm at 80 °C) and electronic conductivity. The more diffuse imidazolium ion affords labile ionic interactions, resulting in higher lithium transference than the other cations studied. Electronic conductivity is also higher in the imidazolium system, stemming from the ability of the planar side chains to stack while also accommodating the bulky TFSI – counterions. Finally, these results demonstrate the importance of interaction strength in ion transport while also indicating that the physical structure of the side chain has an impact on electronic conduction. The imidazolium group strikes a balance, achieving superior properties across all metrics.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Chromatographic and Spectroscopic Study of the Interaction between Polysulfides and Copper Sulfides

To mitigate the “polysulfide shuttle” in lithium–sulfur batteries, different hosting materials that can interact with the polysulfide species physically or chemically have been widely investigated. Copper sulfides as one type of material are believed to have strong chemical interactions with the polysulfide species to consequently influence the performances of Li–S batteries. In this work, high-performance liquid chromatography (HPLC), electrospray ionization mass spectrometry (ESI/MS), scanning electron microscopy with energy-dispersive X-ray spectrometry (SEM-EDS), and inductively coupled plasma optical emission spectroscopy (ICP-OES) were used to systematically investigate the interactions between ether-based polysulfide solutions and copper sulfides (as well as silver sulfide). Furthermore, based on chromatographic and spectroscopic results, the interactions between polysulfides and Cu 2 S can be classified into two types of reactions: one is the redox reaction with the formation of CuS, while another is the complexation reaction with the formation of soluble LiCuS n (n ≥ 4). Contrarily, Ag 2 S (and CuS) shows no interactions with polysulfides. Accordingly, the cycling behaviors of Li–S batteries with copper sulfides as hosting materials or with copper as additives were explained reasonably.

25 ENERGY STORAGE↗

DOE OSTI2024

Dynamic Implications of Noncovalent Interactions in Amphiphilic Single-Chain Polymer Nanoparticles

Single-chain polymer nanoparticles (SCNPs) combine the chemical diversity of synthetic polymers with the intricate structure of biopolymers, generating versatile biomimetic materials. The mobility of polymer chain segments at length scales similar to secondary structural elements in proteins is critical to SCNP structure and thus function. However, the influence of noncovalent interactions used to form SCNPs (e.g., hydrogen-bonding and biomimetic secondary-like structure) on these conformational dynamics is challenging to quantitatively assess. To isolate the effects of noncovalent interactions on SCNP structure and conformational dynamics, we synthesized a series of amphiphilic copolymers containing dimethylacrylamide and monomers capable of forming these different interactions: (1) di(phenylalanine) acrylamide that forms intramolecular β-sheet-like cross-links, (2) phenylalanine acrylamide that forms hydrogen-bonds but lacks a defined local structure, and (3) benzyl acrylamide that has the lowest propensity for hydrogen-bonding. Each SCNP formed folded structures comparable to those of intrinsically disordered proteins, as observed by size exclusion chromatography and small angle neutron scattering. The dynamics of these polymers, as characterized by a combination of dynamic light scattering and neutron spin echo spectroscopy, was well described using the Zimm with internal friction (ZIF) model, highlighting the role of each noncovalent interaction to additively restrict the internal relaxations of SCNPs. These results demonstrate the utility of local scale interactions to control SCNP polymer dynamics, guiding the design of functional biomimetic materials with refined binding sites and tunable kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗