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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analytical model for the motion and interaction of two-dimensional active nematic defects

Here, we develop an approximate, analytical model for the velocity of defects in active nematics by combining recent results for the velocity of topological defects in nematic liquid crystals with the flow field generated from individual defects in active nematics. Importantly, our model takes into account the long-range interactions between defects that result from the flows they produce as well as the orientational coupling between defects inherent in nematics. Our work complements previous studies of active nematic defect motion by introducing a linear approximation that allows us to treat defect interactions as two-body interactions and incorporates the hydrodynamic screening length as a tuning parameter. We show that the model can analytically predict bound states between two +1/2 winding number defects, effective attraction between two –1/2 defects, and the scaling of a critical unbinding length between ±1/2 defects with activity. The model also gives predictions for the trajectories of defects, such as the scattering of +1/2 defects by –1/2 defects at a critical impact parameter that depends on activity. In the presence of circular confinement, the model predicts a braiding motion for three +1/2 defects that was recently seen in experiments, as well as stable and ergodic trajectories for four or more defects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Formation of open ruthenium branched structures with highly exposed active sites for oxygen evolution reaction electrocatalysis

The formation of exposed active sites that have high activity and stability for oxygen evolution reaction (OER) catalysis is a significant opportunity for improving water electrolysers. Low-index facets surface Ru can achieve both high activity and stability for OER. Here, we present a new catalyst design where low-index faceted Ru branches are grown off the corners of Pt nanocubes, forming open Ru branched nanoparticles. This open branched structure, exposing low-index facets on its length-tunable branch, enables a high electrochemically active surface area (ECSA), achieving high activity and stability for OER. This design strategy and synthetic control provide a principle for achieving high-performance OER nanocatalysts.

Xiao, Sa [The University of New South Wales, Sydne↗
DOE OSTI2020

Time reversal symmetry breaking and odd viscosity in active fluids: Green–Kubo and NEMD results

Active fluids, which are driven at the microscale by non-conservative forces, are known to exhibit novel transport phenomena due to the breaking of time reversal symmetry. Recently, Epstein and Mandadapu [arXiv:1907.10041 (2019)] obtained Green-Kubo relations for the full set of viscous coefficients governing isotropic chiral active fluids, including the so-called odd viscosity, invoking Onsager's regression hypothesis for the decay of fluctuations in active non-equilibrium steady states. In this Communication, we test these Green-Kubo relations using molecular dynamics simulations of a canonical model system consisting of actively torqued dumbbells. We find the resulting odd and shear viscosity values from the Green-Kubo relations to be in good agreement with values measured independently through non-equilibrium molecular dynamics flow simulations. This provides a test of the Green-Kubo relations and lends support to the application of the Onsager regression hypothesis in relation to viscous behaviors of active matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The role of collective elasticity on activated structural relaxation, yielding, and steady state flow in hard sphere fluids and colloidal suspensions under strong deformation

In this work, we theoretically study the effect of external deformation on activated structural relaxation and aspects of the nonlinear mechanical response of glassy hard sphere fluids in the context of elastically collective nonlinear Langevin equation theory. This microscopic force-based approach describes activated relaxation as a coupled local–nonlocal event involving caging and longer range collective elasticity, with the latter becoming more important and ultimately dominant with increasing packing fraction under equilibrium conditions. The central new question we address is how this physical picture of activated relaxation, and the relative importance of local caging vs collective elasticity physics, depends on external deformation. Theoretical predictions are presented for deformation-induced enhancement of mobility, the onset of relaxation speed up at remarkably low values of stress, strain, or shear rate, apparent power law thinning of the steady state structural relaxation time and viscosity, a non-vanishing activation barrier in the shear thinning regime, an apparent Herschel–Bulkley form of the rate dependence of the steady state shear stress, exponential growth of different measures of a dynamic yield or flow stress with the packing fraction, and reduced fragility and dynamic heterogeneity under deformation. The results are contrasted with experiments and simulations, and qualitative or better agreement is found. An overarching conclusion is that deformation strongly reduces the importance of longer range collective elastic effects relative to the local caging aspect for most, but not all, physical questions, with deformation-dependent fragility and dynamic heterogeneity phenomena being qualitatively sensitive to collective elasticity. Overall, nonlinear rheology is predicted to be a more local problem than quiescent structural relaxation, albeit with deformation-modified activated processes still important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluating the stability and activity of dilute Cu-based alloys for electrochemical CO 2 reduction

Cu-based catalysts currently offer the most promising route to actively and selectively produce value-added chemicals via electrochemical reduction of CO 2 (eCO 2 R); yet further improvements are required for their wide-scale deployment in carbon mitigation efforts. Here, we systematically investigate a family of dilute Cu-based alloys to explore their viability as active and selective catalysts for eCO 2 R through a combined theoretical–experimental approach. Using a quantum–classical modeling approach that accounts for dynamic solvation effects, we assess the stability and activity of model single-atom catalysts under eCO 2 R conditions. Our calculations identify that the presence of eCO2R intermediates, such as CO*, H*, and OH*, may dynamically influence the local catalyst surface composition. Additionally, we identify through binding energy descriptors of the CO*, CHO*, and OCCO* dimer intermediates that certain elements, such as group 13 elements (B, Al, and Ga), enhance the selectivity of C 2+ species relative to pure Cu by facilitating CO dimerization. The theoretical work is corroborated by preliminary testing of eCO 2 R activity and selectivity of candidate dilute Cu-based alloy catalyst films prepared by electron beam evaporation in a zero-gap gas diffusion electrode-based reactor. Of all studied alloys, dilute CuAl was found to be the most active and selective toward C 2+ products like ethylene, consistent with the theoretical predictions. Finally, we attribute the improved performance of dilute CuAl alloys to more favorable dimerization reaction energetics of bound CO species relative to that on pure Cu. In a broader context, the results presented here demonstrate the power of our simulation framework in terms of rational catalyst design.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Active meta-learning for predicting and selecting perovskite crystallization experiments

Autonomous experimentation systems use algorithms and data from prior experiments to select and perform new experiments in order to meet a specified objective. In most experimental chemistry situations, there is a limited set of prior historical data available, and acquiring new data may be expensive and time consuming, which places constraints on machine learning methods. Active learning methods prioritize new experiment selection by using machine learning model uncertainty and predicted outcomes. Meta-learning methods attempt to construct models that can learn quickly with a limited set of data for a new task. Here in this paper, we applied the model-agnostic meta-learning (MAML) model and the Probabilistic LATent model for Incorporating Priors and Uncertainty in few-Shot learning (PLATIPUS) approach, which extends MAML to active learning, to the problem of halide perovskite growth by inverse temperature crystallization. Using a dataset of 1870 reactions conducted using 19 different organoammonium lead iodide systems, we determined the optimal strategies for incorporating historical data into active and meta-learning models to predict reaction compositions that result in crystals. We then evaluated the best three algorithms (PLATIPUS and active-learning k-nearest neighbor and decision tree algorithms) with four new chemical systems in experimental laboratory tests. With a fixed budget of 20 experiments, PLATIPUS makes superior predictions of reaction outcomes compared to other active-learning algorithms and a random baseline.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Operation of Cs–Sb–O activated GaAs in a high voltage DC electron gun at high average current

Negative Electron Affinity (NEA) activated GaAs photocathodes are the most popular option for generating a high current (>1 mA) spin-polarized electron beam. Despite its popularity, a short operational lifetime is the main drawback of this material. Recent works have shown that the lifetime can be improved by using a robust Cs–Sb–O NEA layer with minimal adverse effects. In this work, we operate GaAs photocathodes with this new activation method in a high voltage environment to extract a high current. We demonstrate that improved chemical resistance of Cs–Sb–O activated GaAs photocathodes allowed them to survive a day-long transport process from a separate vacuum system using a vacuum suitcase. During beam running, we observed spectral dependence on lifetime improvement. In particular, we saw a 45% increase in the lifetime at 780 nm on average for Cs–Sb–O activated GaAs compared to Cs–O activated GaAs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Dissolution of Mg-enriched defects in implanted GaN and increased p-type dopant activation

Annealing Mg-implanted homoepitaxial GaN at temperatures above 1400 °C eliminates the formation of inversion domains and leads to improved dopant activation efficiency. Extended defects, in the form of inversion domains, contain electrically inactive Mg after post-implantation annealing at temperatures as high as 1300 °C (one GPa N 2 overpressure), which results in a low dopant activation efficiency. Triple-axis x-ray data reveal that implant-induced strain is fully relieved after annealing at 1300 °C for 10 min, indicating that strain-inducing point defects formed during implantation have reconfigured and inversion domains are formed. However, annealing at temperatures of 1400–1500 °C (one GPa N 2 overpressure) eliminates the presence of the inversion domains. While residual defects, such as dislocation loops, still exist after annealing at and above 1400 °C, chemical analysis at multiple dislocation loops shows no sign of Mg segregation. Meanwhile, an overall decreasing trend in the dislocation loop density is observed after annealing at the higher temperatures and longer times. Additionally, once inversion domains are formed and the samples are cooled to room temperature, they are shown to dissolve with subsequent annealing above 1400 °C. While such defects have been observed before, the important finding that such defects can be dissolved with a short, higher temperature step is key. Earlier work [Breckenridge et al., J. Appl. Phys. Lett. 118, 022101 (2021)] addressing electrical measurements of these types of samples showed that annealing at 1400 °C leads to a dopant activation efficiency that is an order of magnitude higher than that observed at 1300 °C. In conclusion, this work complements earlier work by identifying the inversion domains, which incorporate Mg, and points to the benefits, in terms of defect density and p-type dopant activation, of using higher temperature (>1400 °C) annealing cycles to activate Mg in GaN, even if the Mg-containing inversion domains had been formed during lower temperature annealing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Novel deuterium–tritium (DT) neutron activation diagnostics for increased neutron yield operations at Sandia’s Z-facility (invited)

As inertial confinement fusion experiments at Sandia National Laboratories’ Z-facility begin using deuterium–tritium (DT) fuels, the expected DT-neutron yields are expected to increase many orders of magnitude. This brings about the need for diagnostics that have a significantly higher dynamic range of operation and ability to obtain yields where there will be significant radiation holds. Using the current activation diagnostic infrastructure at the Z-facility, a pair of activation diagnostics are being developed. Here, the first is fluorine activation, which will be used in a similar manner to current copper activation diagnostics that are fielded in a rabbit for quick removal from the experiments without opening the vacuum experiment containment. The second is a prompt DT-neutron detector that exploits the activation of oxygen with similar operation characteristics as the current Be-probes fielded at Z. We will discuss the design of this pair of instruments, along with calibration work performed at Sandia’s Ion Beam Laboratory in support of the development and anticipated instrument performance.

Mangan, Michael Antony↗
DOE OSTI2026

Active space selection with self-healing diffusion Monte Carlo algorithms for periodic solids

Multideterminant Diffusion Monte Carlo (DMC) displays improved accuracy over single determinant DMC. Self-Healing Diffusion Monte Carlo (SHDMC) is a DMC based method that iteratively improves a multideterminant trial wavefunction. Although configuration interaction or complete active space (CAS) methods are very accurate and computationally feasible for many systems, they are not optimal for application to solids. SHDMC is accurate and designed for application to solids, so developing SHDMC based active space selection algorithms is a worthy endeavor. Here, we present and compare active space selection algorithms that are designed for use in conjunction with SHDMC, without relying on external approaches. For benchmarking, we calculated the ground state energy of a small unit cell of graphene and compared the results with a complete basis set extrapolated selected CI and a reference SHDMC trajectory. We found that systematically expanding the active space using an “auto-branching” algorithm optimally balances accuracy with computational practicality. To the best of our knowledge, this is the first work that demonstrates completely self-contained DMC-based active space selection algorithms that do not depend on external methods for determinant selection.

Spanedda, Nicole [ORNL]↗
DOE OSTI2022

Geological activity shapes the microbiome in deep-subsurface aquifers by advection

Subsurface environments host diverse microorganisms in fluid-filled fractures; however, little is known about how geological and hydrological processes shape the subterranean biosphere. Here, we sampled three flowing boreholes weekly for 10 mo in a 1478-m-deep fractured rock aquifer to study the role of fracture activity (defined as seismically or aseismically induced fracture aperture change) and advection on fluid-associated microbial community composition. We found that despite a largely stable deep-subsurface fluid microbiome, drastic community-level shifts occurred after events signifying physical changes in the permeable fracture network. The community-level shifts include the emergence of microbial families from undetected to over 50% relative abundance, as well as the replacement of the community in one borehole by the earlier community from a different borehole. Null-model analysis indicates that the observed spatial and temporal community turnover was primarily driven by stochastic processes (as opposed to deterministic processes). We, therefore, conclude that the observed community-level shifts resulted from the physical transport of distinct microbial communities from other fracture(s) that outpaced environmental selection. Given that geological activity is a major cause of fracture activity and that geological activity is ubiquitous across space and time on Earth, our findings suggest that advection induced by geological activity is a general mechanism shaping the microbial biogeography and diversity in deep-subsurface habitats across the globe.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structural mechanism of allosteric activation of TRPML1 by PI(3,5)P 2 and rapamycin

Transient receptor potential mucolipin 1 (TRPML1) is a Ca 2+ -permeable, nonselective cation channel ubiquitously expressed in the endolysosomes of mammalian cells and its loss-of-function mutations are the direct cause of type IV mucolipidosis (MLIV), an autosomal recessive lysosomal storage disease. TRPML1 is a ligand-gated channel that can be activated by phosphatidylinositol 3,5-bisphosphate [PI(3,5)P 2 ] as well as some synthetic small-molecule agonists. Recently, rapamycin has also been shown to directly bind and activate TRPML1. Interestingly, both PI(3,5)P 2 and rapamycin have low efficacy in channel activation individually but together they work cooperatively and activate the channel with high potency. To reveal the structural basis underlying the synergistic activation of TRPML1 by PI(3,5)P 2 and rapamycin, we determined the high-resolution cryoelectron microscopy (cryo-EM) structures of the mouse TRPML1 channel in various states, including apo closed, PI(3,5)P 2 -bound closed, and PI(3,5)P 2 /temsirolimus (a rapamycin analog)-bound open states. These structures, combined with electrophysiology, elucidate the molecular details of ligand binding and provide structural insight into how the TRPML1 channel integrates two distantly bound ligand stimuli and facilitates channel opening.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Reassessing the claimed cytokinin-substituting activity of dehydrodiconiferyl alcohol glucoside

Dehydrodiconiferyl alcohol glucoside (DCG) is a phenylpropanoid-derived plant metabolite with reported cytokinin-substituting and cell-division-promoting activity. Despite its claimed activity, DCG did not trigger morphological changes in Arabidopsis seedlings nor did it alter transcriptional shifts in cell division and cytokinin-responsive genes. In reinvestigating the bioactivity of DCG in its original setting, the previously described stimulation of tobacco callus formation could not be confirmed. No evidence was found that DCG is actually taken up by plant cells, which could explain the absence of any observable activity in the performed experiments. The DCG content in plant tissue increased when feeding explants with the DCG aglycone dehydrodiconiferyl alcohol, which is readily taken up and converted to DCG by plant cells. Despite the increased DCG content, no activity for this metabolite could be demonstrated. Furthermore, our results therefore demand a reevaluation of the often-quoted cytokinin-substituting and cell-division-promoting activity that has previously been attributed to this metabolite.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A first principles analysis of potential-dependent structural evolution of active sites in Fe-N-C catalysts

Fe-N-C (iron–nitrogen–carbon) electrocatalysts have emerged as potential alternatives to precious metal-based materials for the oxygen reduction reaction (ORR). However, the structure of these materials under electrochemical conditions is not well understood, and their poor stability in acidic environments poses a formidable challenge for successful adoption in commercial fuel cells. To provide molecular-level insights into these complex phenomena, we combine periodic density functional theory (DFT) calculations, exhaustive treatment of coadsorption effects for ORR reaction intermediates, including O and OH, and comprehensive analysis of solvation stabilization effects to construct voltage-dependent ab initio thermodynamic phase diagrams that describe the in situ structure of the active sites. These structures are further linked to activity and stability descriptors that can be compared with experimental parameters such as the half-wave potential for ORR and the onset potential for carbon corrosion and CO 2 evolution. The results indicate that pyridinic Fe sites at zigzag carbon edges, as well as other edge sites, exhibit high activity for ORR compared to sites in the bulk. However, edges neighboring the active sites are prone to instability via overoxidation and consequent site loss. The results suggest that it could be beneficial to synthesize Fe-N-C catalysts with small sizes and large perimeter edge lengths to enhance ORR activity, while voltage fluctuations should be limited during fuel cell operation to prevent carbon corrosion of overoxidized edges.

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

Network of epistatic interactions in an enzyme active site revealed by large-scale deep mutational scanning

Cooperative interactions between amino acids are critical for protein function. A genetic reflection of cooperativity is epistasis, which is when a change in the amino acid at one position changes the sequence requirements at another position. To assess epistasis within an enzyme active site, we utilized CTX-M β-lactamase as a model system. CTX-M hydrolyzes β-lactam antibiotics to provide antibiotic resistance, allowing a simple functional selection for rapid sorting of modified enzymes. We created all pairwise mutations across 17 active site positions in the β-lactamase enzyme and quantitated the function of variants against two β-lactam antibiotics using next-generation sequencing. Context-dependent sequence requirements were determined by comparing the antibiotic resistance function of double mutations across the CTX-M active site to their predicted function based on the constituent single mutations, revealing both positive epistasis (synergistic interactions) and negative epistasis (antagonistic interactions) between amino acid substitutions. The resulting trends demonstrate that positive epistasis is present throughout the active site, that epistasis between residues is mediated through substrate interactions, and that residues more tolerant to substitutions serve as generic compensators which are responsible for many cases of positive epistasis. Additionally, we show that a key catalytic residue (Glu166) is amenable to compensatory mutations, and we characterize one such double mutant (E166Y/N170G) that acts by an altered catalytic mechanism. These findings shed light on the unique biochemical factors that drive epistasis within an enzyme active site and will inform enzyme engineering efforts by bridging the gap between amino acid sequence and catalytic function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Active doping controls the mode of failure in dense colloidal gels

Mechanical properties of disordered materials are governed by their underlying free energy landscape. In contrast to external fields, embedding a small fraction of active particles within a disordered material generates nonequilibrium internal fields, which can help to circumvent kinetic barriers and modulate the free energy landscape. In this work, we investigate through computer simulations how the activity of active particles alters the mechanical response of deeply annealed polydisperse colloidal gels. We show that the “swim force” generated by the embedded active particles is responsible for determining the mode of mechanical failure, i.e., brittle vs. ductile. We find, and theoretically justify, that at a critical swim force the mechanical properties of the gel decrease abruptly, signaling a change in the mode of mechanical failure. The weakening of the elastic modulus above the critical swim force results from the change in gel porosity and distribution of attractive forces among gel particles, while below the critical swim force, the ductility enhancement is caused by an increase of gel structural disorder. Above the critical swim force, the gel develops a pronounced heterogeneous structure characterized by multiple pore spaces, and the mechanical response is controlled by dynamical heterogeneities. We contrast these results with those of a simulated monodisperse gel that exhibits a nonmonotonic trend of ductility modulation with increasing swim force, revealing a complex interplay between the gel energy landscape and embedded activity.

Zhou, Tingtao (ORCID:000000021766719X)↗
DOE OSTI2025

Weighted active space protocol for multireference machine-learned potentials

Multireference methods such as multiconfiguration pair-density functional theory accurately capture electronic correlation in systems with strong multiconfigurational character, but their cost precludes direct use in molecular dynamics. Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach. However, the sensitivity of multireference calculations to the choice of the active space complicates the consistent evaluation of energies and gradients across structurally diverse nuclear configurations. To overcome this limitation, we introduce the weighted active space protocol (WASP), a systematic approach to assign a consistent active space for a given system across uncorrelated configurations. By integrating WASP with MLPs and enhanced sampling techniques, we propose a data-efficient active learning cycle that enables the training of an MLP on multireference data. We demonstrated the approach on the TiC + -catalyzed C–H activation of methane, a reaction that poses challenges for Kohn–Sham density functional theory due to its significant multireference character. This framework enables accurate and efficient modeling of catalytic dynamics, establishing a paradigm for simulating complex reactive processes beyond the limits of conventional electronic-structure methods.

enhanced sampling↗
DOE OSTI2022

Investigation of Ni catalyst activation during plasma-assisted methane oxidation

Atmospheric pressure plasma has shown promise in improving thermally activated catalytic reactions through a process termed plasma-catalysis synergy. In this work, we investigated atmospheric pressure plasma jet (APPJ)-assisted CH 4 oxidation over a Ni/SiO 2 .Al 2 O 3 catalyst. Downstream gas-phase products from CH 4 conversion were quantified by Fourier transform infrared spectroscopy. The catalyst near-surface region was characterized by in-situ diffuse reflectance infrared Fourier transform spectroscopy. The catalyst was observed to be activated at elevated temperature (500 °C) if it was exposed to the APPJ operated at large plasma power. 'Catalyst activation' signifies that the purely thermal conversion of CH 4 using catalysts which had been pre-exposed to plasma became more intense and produced consistently CO product, even if the plasma was extinguished. Without the application of the APPJ to the Ni catalyst surface this was not observed at 500 °C. The study of different exposure conditions of the activated catalyst indicates that the reduction of the catalyst by the APPJ is likely the cause of the catalyst activation. We also observed a systematic shift of the vibrational frequency of adsorbed CO on Ni catalyst when plasma operating conditions and catalyst temperatures were varied and discussed possible explanations for the observed changes. Furthermore, this work provides insights into the plasma-catalyst interaction, especially catalyst modification in the plasma catalysis process, and potentially demonstrates the possibility of utilizing the surface CO as a local probe to understand the plasma-catalyst interaction and shed light on the complexity of plasma catalysis.

methane oxidation↗