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At least 253 records · Page 14

Machine Learning‐Augmented Molecular Dynamics Simulations (MD) Reveal Insights Into the Disconnect Between Affinity and Activation of ZTP Riboswitch Ligands

Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Chemistry↗

Using tabulated NLTE data for Hohlraum simulations

Non-local thermodyamic equilibrium (NLTE) atomic kinetics is necessary in inertial confinement fusion Hohlraum simulations for adequately modeling high-Z walls and dopants but is computationally very expensive. We present here an approach for tabulating NLTE material data in an economical manner. Material properties for an arbitrary radiation field are provided through tabulated data for a limited set of radiation fields plus derivatives with respect to components of those radiation fields. We have implemented this method in a radiation-hydrodynamics code and compare Hohlraum simulations done with inline NLTE calculations with those done with tables constructed from the same atomic data. The results demonstrate that NLTE tables can replace inline calculations in Hohlraum simulations without a significant loss of accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effects of sodium and calcium chloride ionic stresses on model yeast membranes revealed by molecular dynamics simulation

As efforts to move a renewable economy grow, it will be necessary to make use of microbial conversion strategies for the production of novel materials or the upgrading of waste to high-value products. One critical technical challenge currently limiting waste upgrading remains the difficulty in obtaining single-pot conversion techniques where physical, chemical, and biological conversion are performed in a single step. To overcome this challenge, a detailed understanding of how different stresses impact microbial membrane stability will be necessary. In this work, using all-atom molecular dynamics simulations, we examine the impacts of moderate concentrations of NaCl and CaCl 2 on a model yeast plasma membrane. Weak, though statistically significant, changes in membrane morphology and dynamics functions are observed that are consistent with swelling and stiffening. Additionally, an examination of the ion-lipid contacts and the behavior of water at the water-membrane interface suggests that the impacts of these common salts may, in part, be mediated through changes to water-membrane hydrogen-bonding and hydration water dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Macroscale properties and atomic-scale mechanisms of ash removal in low-temperature hydrothermal carbonization

Biogenic ash is a significant impediment to the utilization of agricultural residues in biofuel production. Such challenge can be addressed by various treatments, as demonstrated in this study on the experimental and computational mechanisms involved in the hydrothermal treatment (HT) of wheat straw. A combination of classical (all-atom) molecular dynamics simulations of cellulose carrying silica and calcium species, along with first principles quantum chemical calculations, indicates the dissociation of inorganics from the cellulose with increased HT temperature. Here, this observation is confirmed by experimental evidence of effective ash removal by HT, showing at least 50% removal of sulfur, chlorine, potassium, and calcium, and 12.5% of silica, leading to a reduced total ash content (from 6.7% to 4.2%).Changes in structural features upon HT, such as surface cellular structure and porosity, were revealed, accompanied by an increased specific surface area (from 1.17 to 6.34 m 2 /g). Our simulations suggest that silica binds tightly to the hydrophobic face of cellulose at room temperature, but HT significantly reduces the binding free energy of association with both hydrophobic and hydrophilic surfaces. Most significantly, ash removal leads to an increased calorific value, rising from approximately 16 MJ/kg to about 19 MJ/kg, along with improved thermal behavior. The improved integration combustion index parameter S indicates that the combustion properties improve with ash removal efficiency. The proposed atomic-level mechanism for the observed removal of inorganics during mild HT underscores the potential of such treatment in producing energy-dense wheat straw, a widely available agricultural residue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emergent Ergodicity at the Transition between Many-Body Localized Phases

Strongly disordered systems in the many-body localized (MBL) phase can exhibit ground state order in highly excited eigenstates. The interplay between localization, symmetry, and topology has led to the characterization of a broad landscape of MBL phases ranging from spin glasses and time crystals to symmetry protected topological phases. Understanding the nature of phase transitions between these different forms of eigenstate order remains an essential open question. In this work, we conjecture that no direct transition between distinct MBL orders can occur in one dimension; rather, an ergodic phase always intervenes. Motivated by recent advances in Rydberg-atom-based quantum simulation, we propose an experimental protocol where the intervening ergodic phase can be diagnosed via the dynamics of local observables.

1-dimensional spin chains↗

Robust and ultrafast state preparation by ramping artificial gauge potentials

Abstract The implementation of static artificial magnetic fields in ultracold atomic systems has become a powerful tool, e.g. for simulating quantum-Hall physics with charge-neutral atoms. Taking an interacting bosonic flux ladder as a minimal model, we investigate protocols for adiabatic state preparation via magnetic flux ramps. Considering the fact that it is actually the artificial vector potential (in the form of Peierls phases) that can be experimentally engineered in optical lattices, rather than the magnetic field, we find that the time required for adiabatic state preparation dramatically depends on which pattern of Peierls phases is used. This can be understood intuitively by noting that different patterns of time-dependent Peierls phases that all give rise to the same magnetic field ramp, generally lead to different artificial electric fields during the ramp. As an intriguing result, we find that an optimal choice allows for preparing the ground state almost instantaneously in the non-interacting system, which can be related to the concept of counterdiabatic driving. Remarkably, we find extremely short preparation times also in the strongly-interacting regime. Our findings open new possibilities for robust state preparation in atomic quantum simulators.

Wang, Botao (ORCID:0000000282202452)↗

Isolated copper single sites for high-performance electroreduction of carbon monoxide to multicarbon products

Electrochemical carbon monoxide reduction is a promising strategy for the production of value-added multicarbon compounds, albeit yielding diverse products with low selectivities and Faradaic efficiencies. Here, copper single atoms anchored to Ti 3 C 2 T x MXene nanosheets are firstly demonstrated as effective and robust catalysts for electrochemical carbon monoxide reduction, achieving an ultrahigh selectivity of 98% for the formation of multicarbon products. Particularly, it exhibits a high Faradaic efficiency of 71% towards ethylene at -0.7 V versus the reversible hydrogen electrode, superior to the previously reported copper-based catalysts. Besides, it shows a stable activity during the 68-h electrolysis. Theoretical simulations reveal that atomically dispersed Cu–O 3 sites favor the C–C coupling of carbon monoxide molecules to generate the key *CO-CHO species, and then induce the decreased free energy barrier of the potential-determining step, thus accounting for the high activity and selectivity of copper single atoms for carbon monoxide reduction.

36 MATERIALS SCIENCE↗

Sequential Infiltration Synthesis of Cadmium Sulfide Discrete Atom Clusters

Abstract Exposure of soft material templates to alternating volatile chemical precursors can produce inorganic deposition within the permeable template (e.g. a polymer thin film) in a process akin to atomic layer deposition (ALD). While such sequential infiltration synthesis (SIS) processes have now been demonstrated for many metal oxides, we report an SIS process for a transition metal sulfide – CdS. Gas phase dimethyl cadmium and hydrogen sulfide precursors infiltrated into poly(4‐vinylpyridine) thin films result in the 3D‐nucleation of clusters consistent with a cubane‐type Cd 4 S 4 core that are variably terminated with methyl, thiol and hydroxy capping ligands. First principles models and simulation of few‐atom Cd‐based clusters are consistent with electronic and vibrational spectroscopy and grazing‐incidence total X‐ray scattering measurements of 3D‐cluster‐arrays synthesized at 80 °C. The direct synthesis of few‐atom transition metal sulfide clusters within polymer thin films will provide a versatile new route to precision architectures for light‐absorbing materials including solar energy harvesting and conversion applications.

Jayaweera, Nuwanthaka P. [Material Science Divisio↗

Origin of Selective Production of Hydrogen Peroxide by Electrochemical Oxygen Reduction

Oxygen reduction reaction (ORR) is one of the most important electrochemical reactions. Starting from a common reaction intermediate *–O–OH, the ORR splits into two pathways, either producing hydrogen peroxide (H 2 O 2 ) by breaking the *–O bond or leading to water formation by breaking the O–OH bond. However, it is puzzling why many catalysts, despite the strong thermodynamic preference for the O–OH breaking, exhibit high selectivity for hydrogen peroxide. Moreover, the selectivity is dependent on the potential and pH, which remain not understood. Here, for this work, we develop an advanced first-principles model for effective calculation of the electrochemical reaction kinetics at the solid–water interface, which were not accessible by conventional models. Using this model to study representative catalysts for H 2 O 2 production, we find that breaking the O–OH bond can have a higher energy barrier than breaking *–O, due to the rigidity of the O–OH bond. Importantly, we reveal that the selectivity dependence on potential and pH is rooted into the proton affinity to the former/later O in *–O–OH. For single cobalt atom catalyst, decreasing potential promotes proton adsorption to the former O, thereby increasing the H 2 O 2 selectivity. In contrast, for the carbon catalyst, the proton prefers the latter O, resulting in a lower H 2 O 2 selectivity in acid condition. These findings explain the experiments and highlight the kinetic origins of the selectivity. Our work improves the understanding of ORR by uncovering the proton affinity as a new factor and provides a new model to effectively simulate the atomic-level kinetics of heterogeneous electrochemistry.

08 HYDROGEN↗

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗

Scale Invariance of Hot Spot Formation in TATB High Explosives

Shock-induced detonation of insensitive high explosives based on 1,3,5-triamino-2,4,6-trinitrobenzene starts with formation of hot spots at microstructural defects but has eluded atomistic modeling treatment at micron length scales. To this end, we performed multimicron scale all-atom molecular dynamics (MD) simulations of hot spots that form during the collapse of cylindrical pores with diameters between 10 and 300 nm. Our MD simulations show that hot spots formed at pores larger than 20 nm exhibit temperature fields with scale-invariant features for sizes up to at least 300 nm. Through a continuum-based grain-scale modeling framework, we span and extend beyond the size scales currently accessible to MD and find that hot spot scale invariance is a general feature that arises when the mechanical strength is insensitive to strain rate. Finally, our results demonstrate the applicability of all-atom MD to simulate the complicated dynamical evolution of micron-sized systems and bolster confidence in insights from MD simulations of materials that exhibit strength with negligible rate dependence over the relevant intervals.

36 MATERIALS SCIENCE↗

Imaging atomic-scale chemistry from fused multi-modal electron microscopy

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic-resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark-field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

36 MATERIALS SCIENCE↗

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH 2 -capped block of six hydrophobic N-((4-bromophenyl)ethyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. Furthermore, this work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

Femtosecond two-photon-resonant parametric four-wave mixing detection of atomic hydrogen

Here, we demonstrate an ultrafast parametric four-wave mixing method for the collisional-quenching-free detection of atomic hydrogen. Two photons of 243 nm light resonantly excite the n = 1 to n = 2 transition of atomic hydrogen, and a third probe photon scatters from the electronic coherence to generate the parametric emission of a degenerate signal photon. Laser-induced photofragmentation fluorescence from water, also excited with the same 243 nm pulses, is used as a convenient method to visualize beam overlap in space and time. The femtosecond time resolution enables the suppression of unwanted nonresonant contributions to the signal and separation from resonant mixing in water molecules because of the significantly different coherence lifetimes. A folded BOXCARS phase-matching configuration yields a spatially isolated, laser-like, signal beam, amenable to measurements in highly luminous backgrounds. Measurements in an H 2 /CH 4 /air flame demonstrate quantitative agreement with simulated H-atom concentration profiles. A coherence decay time constant of 42 ps is recorded in the atmospheric pressure flame.

Kliewer, Christopher Jesse [Sandia National Labora↗

Exemption of lattice collapse in Ni–MnO 2 birnessite regulated by the structural water mobility

Lattice collapse and associated mechanical fracture frequently occur in Li-intercalated metal oxide cathodes at the deep charge state upon Li-ion removal, governed by chemical compositions and the resulting electron density of the oxygen atoms. However, similar lattice collapse for metal oxide electrodes in aqueous storage and its mitigation have not been well studied. In this work, we reported the lattice collapse of MnO 2 layered birnessite during the aqueous de-sodiation process at high voltage due to the structural water motion, as evidenced by in situ XRD. Unlike non-aqueous Li-intercalated electrodes, Ni-dopants mitigated the lattice collapse of birnessite at deep charge states. Moreover, density functional theory (DFT) calculations showed that Ni doping induces charge depletion of lattice oxygen due to its higher electronegativity than Mn. This charge reduction, in turn, yields a significant decrease in electrostatic repulsion between the oxygens belonging to lattice and structural water. Classical molecular dynamics simulations based on atomic charges obtained from DFT elucidate that Ni-doping facilitates immobilization of structural water in (Ni)MnO 2 and prevents lattice collapse upon Na-ion removal. (Ni)MnO 2 exempted from lattice collapse shows an improved storage capacity relative to MnO 2 while maintaining similar cycling stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular-level design of alternative media for energy-saving pilot-scale fibrillation of nanocellulose

The outstanding mechanical properties, light weight, and biodegradability of cellulose nanofibrils (CNFs) make them promising components of renewable and sustainable next-generation reinforced composite biomaterials and bioplastics. Manufacturing CNFs at a pilot scale requires disc-refining fibrillation of dilute cellulose fibers in aqueous pulp suspensions to shear the fibers apart into their nanodimensional forms, which is, however, an energy-intensive process. Here, in this study, we used atomistic molecular dynamics (MD) simulation to examine media that might facilitate the reduction of interactions between cellulose fibers, thereby reducing energy consumption in fibrillation. The most suitable medium found by the simulations was an aqueous solution with 0.007:0.012 wt.% NaOH:urea, and indeed this was found in pilot-scale experiments to reduce the fibrillation energy by ~21% on average relative to water alone. The NaOH:urea-mediated CNFs have similar crystallinity, morphology, and mechanical strength to those formed in water. The NaOH and urea act synergistically on CNFs to aid fibrillation but at different length scales. NaOH deprotonates hydroxyl groups leading to mesoscale electrostatic repulsion between fibrils, whereas urea forms hydrogen bonds with protonated hydroxyl groups thus disrupting interfibril hydrogen bonds. This suggests a general mechanism in which an aqueous medium that contains a strong base and a small organic molecule acting as a hydrogen-bond acceptor and/or donor may be effectively employed in materials processes where dispersion of deprotonable polymers is required. The study demonstrates how atomic-detail computer simulation can be integrated with pilot-scale experiments in the rational design of materials processes for the circular bioeconomy.

36 MATERIALS SCIENCE↗

Molecular dynamics studies of lattice defect effects on tritium diffusion in zirconium

Tritium diffusion in α-Zr containing point defects such as vacancies or self-interstitial atoms (SIAs) is simulated using molecular dynamics. Point defects rapidly aggregate to form extended defects, such as 3D nanoclusters and Frank loops. The geometry of extended defects is affected by the presence of tritium. At low temperature and in the absence of tritium, vacancies aggregate to form stacking fault pyramids. Addition of tritium at these temperatures promotes aggregation of vacancies to form 3D nanoclusters, within which the tritium concentration can be sufficiently high to suggest that these defects may serve as nucleation sites for hydride precipitation. Trapping of tritium in vacancy nanocluster reduces the calculated bulk diffusivity by an amount proportional to the vacancy concentration. At high temperature, vacancy clusters change shape to form planar basal dislocation loops, which bind tritium less strongly, leading to a sharp reduction in the fraction of trapped tritium and a corresponding increase in tritium diffusivity at high temperature. In contrast, SIAs increase tritium diffusion through α-Zr. Analysis of atomic trajectories shows that tritium does not interact directly with SIAs. In conclusion, diffusion enhancement is instead related to expansion of the lattice.

36 MATERIALS SCIENCE↗

Data-Driven Discovery of Linear Molecular Probes with Optimal Selective Affinity for PFAS in Water

Approaches to tackle the wide and growing variety of highly persistent per- and polyfluoroalkyl substances (PFAS) are of pressing global need because of their detrimental human health effects, such as cancer, birth defects, and hormone imbalance. Sensitive, selective, and easy-to-use real-time sensors to monitor and detect PFAS and sorbents to extract them are critical to meeting government-mandated environmental concentrations. In this work, we combine all-atom molecular dynamics simulations, enhanced sampling, deep representational learning, and Bayesian optimization to perform high-throughput virtual screening for highly sensitive and selective molecular probes. Our molecular design space consists of 3850 linear hydrocarbon chains with varying degrees of halogenation with and without amine- and phosphine-based headgroups. By employing a data-driven search process, we efficiently explore the molecular design space to optimize the sensitivity to perfluorooctanesulfonic acid (PFOS) as a prototypical PFAS analyte and selectivity relative to a sodium dodecyl sulfate (SDS) interferent. We calculate 504 Gibbs free energies of probe-analyte and probe-interferent interactions and identify probes with PFOS association free energies of up to (-ΔG PFOS ) = 9.8 ± 0.2 kJ/mol and selectivities relative to SDS of (-ΔΔG PFOS–SDS ) = 3.1 ± 1.5 kJ/mol. A C 11 Br 23 P(CH 3 ) 2 probe containing 11 backbone brominated carbons and a tertiary phosphine headgroup possesses the most sensitive binding constant to PFOS within the defined search space of K b PFOS = 177.4 ± 12.7, and a semibrominated probe C 5 H 11 C 7 Br 14 N(CH 3 ) 2 containing 12 backbone carbons and a tertiary amine headgroup possesses the highest selectivity relative to SDS of K b PFOS /K b SDS = 4.6 ± 1.7. A retrospective analysis of our data to extract interpretable design rules reveals that the sensitivity of linear hydrogenated probes increases by approximately 1 kJ/mol per C–C bond. The addition or removal of halogen atoms and amine or phosphine headgroups produces nonmonotonic changes in both sensitivity and selectivity with changes to the sensitivity of up to 2.5 kJ/mol. Finally, this work places empirical limitations on the performance of a wide range of linear probes for PFOS detection and offers a generic strategy for high-throughput computational screening to promote selective and sensitive binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗