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At least 91 records · Page 5

Time-series dissolved oxygen, other bigeochemically-relevant analytes, and pressure gradients associated with the manuscript “Dissolved oxygen sensor in an automated hyporheic sampling system reveals biogeochemical dynamics”

This dataset contains time-series data from a vertical profile within the bed and banks of the Columbia river near Richland, WA. Water was sampled through 3 small tubes embedded in the sediment at 50,100, and 200 cm below the sediment-water interface. The goal of this study was to observe the correlations between hydraulic drivers and biogeochemical responses. The results of this study are published in the manuscript “Dissolved oxygen sensor in an automated hyporheic sampling system reveals biogeochemical dynamics”. The file types included in the data package are all time-series spreadsheet data, including hydraulic head gradients, physical parameters (temperature, pressure, SpC (specific conductivity)), and biogeochemical parameters (dissolved oxygen, pH, NO3 (nitrate) and ORP (oxidation-reduction potential)).

54 ENVIRONMENTAL SCIENCES↗

Foldamer architectures of triazine-based sequence-defined polymers investigated with molecular dynamics simulations and enhanced sampling methods

Triazine-based sequence-defined polymers have recently been developed that are biomimetic and robust (Grate \latin{et al.} Angewandte Chemie 2016). In molecular dynamics (MD) simulations, the triazine polymers were shown to form linear nanorod foldamers through hydrogen bonding and $\pi$-$\pi$ interactions. The nanorod foldamers have motifs resembling those of DNA, $\alpha$-helices, and $\beta$-sheets, and have potential to be useful building blocks for new macromolecules and materials. To understand the formation of nanorod foldamers, we investigate how linker structures in the middle of the triazine polymers lead to folding using MD simulations. We found that a variety of linkers can participate in folding, but that specific linker structures are more favorable than others, depending on the polymer length. Folding of hexamers into well-defined nanorod foldamers was most favorable with pentanediamine and \emph{ortho}-xylenediamine linkers in the center of the polymers. Foldamers with \emph{ortho}-xylenediamine linkers in the center were investigated for longer polymers, i.e., octamers and decamers, using two different enhanced sampling methods, since regular MD simulations had failed to show any folding for these longer polymers. In particular, the recently developed concurrent adaptive sampling (CAS) algorithm (Ahn \latin{et al.} J. Chem. Phys. 2017) and replica exchange molecular dynamics (REMD) were used. We found that the two enhanced sampling methods did lead to the observation of foldamers, and that REMD revealed new foldamer architectures where \emph{cis}-\emph{trans} isomerizations had occurred. Foldamer formation, diversity, and the strengths and limitations of simulation techniques are discussed. These findings provide new insights into the diversity of foldamer architectures for a new type of biomimetic synthetic polymer.

Foldamers, Nanorods, Free energy landscapes, Molec↗

The influence of sampling rate on the dynamics and control of aeronautical systems

It is shown in the design of aeronautical control systems that sampling rate variations give rise to migrations of the discrete eigenvalues for both the plant and the controllers. In general, these migrations tend to degrade simulation fidelity and the overall performance of Ultrareliable Fault Tolerant Control Systems (UFTCS). These systems consist of a redundant asynchronous network of microprocessors which use sensor information to generate the servo commands that drive actuators, thrust linkages, etc. A change in the sampling period of a single microprocessor will, in addition to causing an eigenvalue shift, alter the magnitude of the servo command issued by the controller. The influence of these changes and the effect of initial conditions and skew are considered.

Howard, J. C.↗

A stochastic covariance shrinkage approach to particle rejuvenation in the ensemble transform particle filter

Rejuvenation in particle filters is necessary to prevent the collapse of the weights when the number of particles is insufficient to properly sample the high-probability regions of the state space. Rejuvenation is often implemented in a heuristic manner by the addition of random noise that widens the support of the ensemble. This work aims at improving canonical rejuvenation methodology by the introduction of additional prior information obtained from climatological samples; the dynamical particles used for importance sampling are augmented with samples obtained from stochastic covariance shrinkage. A localized variant of the proposed method is developed. Numerical experiments with the Lorenz '63 model show that modified filters significantly improve the analyses for low dynamical ensemble sizes. Furthermore, localization experiments with the Lorenz '96 model show that the proposed methodology is extendable to larger systems.

54 ENVIRONMENTAL SCIENCES↗

Deployment of salt sample extraction system at an engineering-scale electrorefiner

The goal of the salt sampling program at Argonne is to develop and deploy automated molten salt sampling approaches for interfacing relevant unit operations with salt analysis to improve the timeliness of sampling-based accountancy measurements. Two technologies under development in support of this goal are a vacuum sampling loop module and a high-throughput pneumatic sample generator module. Compared to traditional point sampling approaches (i.e., dip probes), the vacuum sampling loop facilitates the collection of a larger cross-section of the bulk salt in order to collect more representative samples. The vacuum sampling approach also eliminates the risk of dross contamination of samples and avoids the use of moving parts in the salt. The pneumatic sample generator module is used to facilitate high-throughput sample analysis to improve the measurement precision of any given analytical technique by averaging out random sampling and measurement errors. In FY21, two methods for integrating these two modules were tested including direct fluidic coupling and coupling using a solid salt transfer mechanism. Solid salt transfer was ultimately selected over fluidic coupling, primarily to enable the transport of samples over longer distances to support automated at-line integration with high-precision techniques (such as microcalorimetry) that cannot withstand the conditions near an electrorefining process. To facilitate rapid solid salt coupling, new mechanisms were developed for rapidly charging and discharging salt sample tubes at the vacuum sampling loop and pneumatic sample generator modules, respectively. While the charging mechanism will be deployed in FY22, the discharge mechanism was tested in FY21 and is described here. The solid salt tube transfer method was deployed at one of Argonne’s engineering-scale electrorefiners to implement at-line high-throughput pneumatic micro-sample generation capabilities. The approach was used to generate precise uranium- and lanthanide-bearing electrorefiner micro-samples with the specific dimensions requested by researchers at Los Alamos National Laboratory for use in testing their novel microcalorimeter x-ray techniques. The solid salt transfer mechanism proved not only to be an effective means of integrating the precision sample generator with vacuum sampling, but also improved the performance of the sampler generator. To discharge salt from the sample tubes at the sampler generator, tube segments were inserted directly into the sample generator’s Helmholtz chamber and pressure pulse actuations were used to generate precision molten salt samples directly from the tube segments. The direct insertion of sample tubes into the sample generator enabled rapid loading of the salt and prevented salt from contacting most of the interior surfaces of the sample generator, which eliminated cross-contamination between runs. The vacuum sampling-loop tube charging mechanism will support high-throughput tube sampling operations by employing a dynamic vacuum filling process to fill short charge tubes that are configured to be rapidly connected and disconnected from the loop. The dynamic vacuum sampling operation will be automated, and sample tube handling can be executed with simple overhead actuation. Because the modular sampling approach described here eliminates the need for new high-radiation sample handling capabilities, salt-wetted seals, salt-wetted moving parts, and heated transfer lines outside the electrorefiner, it will address most of the remaining technical challenges for the at-line deployment of high-precision analytical techniques which will enable significant reductions in the time delay for sampling-based high-precision accountancy measurements.

42 ENGINEERING↗

Quantification of in-contact probe-sample electrostatic forces with dynamic atomic force microscopy

Here, atomic force microscopy (AFM) methods utilizing resonant mechanical vibrations of cantilevers in contact with a sample surface have shown sensitivities as high as few picometers for detecting surface displacements. Such a high sensitivity is harnessed in several AFM imaging modes. Here, we demonstrate a cantilever-resonance-based method to quantify electrostatic forces on a probe in the probe-sample junction in the presence of a surface potential or when a bias voltage is applied to the AFM probe. We find that the electrostatic forces acting on the probe tip apex can produce signals equivalent to a few pm of surface displacement. In combination with modeling, the measurements of the force were used to access the strength of the electrical field at the probe tip apex in contact with a sample. We find an evidence that the electric field strength in the junction can reach ca. 1 V nm –1 at a bias voltage of a few volts and is limited by non-ideality of the tip-sample contact. This field is sufficiently strong to significantly influence material states and kinetic processes through charge injection, Maxwell stress, shifts of phase equilibria, and reduction of energy barriers for activated processes. Besides, the results provide a baseline for accounting for the effects of local electrostatic forces in electromechanical AFM measurements as well as offer additional means to probe ionic mobility and field-induced phenomena in solids.

36 MATERIALS SCIENCE↗

Use of continuous sample translation to reduce radiation damage for XPCS studies of protein diffusion

An experimental setup to measure X-ray photon correlation spectroscopy during continuous sample translation is presented and its effectiveness as a means to avoid sample damage in dynamics studies of protein diffusion is evaluated. X-ray damage from focused coherent synchrotron radiation remains below tolerable levels as long as the sample is translated through the beam sufficiently quickly. Here it is shown that it is possible to separate sample dynamics from the effects associated with the transit of the sample through the beam. By varying the sample translation rate, the damage threshold level, D thresh = 1.8 kGy, for when beam damage begins to modify the dynamics under the conditions used, is also determined. Signal-to-noise ratios, R sn ≥ 20, are obtained down to the shortest delay times of 20 µs. The applicability of this method of data collection to the next generation of multi-bend achromat synchrotron sources is discussed and it is shown that sub-microsecond dynamics should be obtainable on protein samples.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

60 APPLIED LIFE SCIENCES↗

Computational Fluid Dynamics Modeling to Facilitate Qualification of Stack Sampling Probe Location

Computational fluid dynamics (CFD) modeling was used to help evaluate modifications to a radiological effluent stack and assist with establishing a stack sampling location that met the mixing criteria for qualification. Requirements for stack sampling location are listed in the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-2021 standard. Modeling was performed to help develop a suitable design for increasing building ventilation for the radiological effluent stack. The ANSI/HPS N13.1-2021 criteria for the air monitoring probe location are that the coefficient of variation of velocity uniformity, gaseous tracer uniformity, and particulate tracer uniformity must be less than or equal to 20%. Furthermore, no point in the sampling location may have a gaseous tracer concentration that varies from the mean concentration by more than 30%. Additionally, the flow angle at the sampling location must not be more than 20 degrees. The ANSI/HPS N13.1-2021 standard allows for models (physical or computational) to be employed to perform the full suite of qualification tests, followed by a more limited set of verification tests on the actual stack to qualify the stack sampling location. Here, a series of computational model simulations were employed to evaluate the stack qualification criteria. Significant time and re-source savings are achieved using CFD modeling. CFD modeling demonstrated that the stack meets the criteria at the sample probe location. Verification tests were performed on the modified stack to measure the velocity uniformity and flow angle at the stack sampling location, and results demonstrated that the CFD model results may be used to support the qualification of the stack sampling location.

Air Monitoring↗

Chaotic neural dynamics facilitate probabilistic computations through sampling

Cortical neurons exhibit highly variable responses over trials and time. Theoretical works posit that this variability arises potentially from chaotic network dynamics of recurrently connected neurons. Here, we demonstrate that chaotic neural dynamics, formed through synaptic learning, allow networks to perform sensory cue integration in a sampling-based implementation. We show that the emergent chaotic dynamics provide neural substrates for generating samples not only of a static variable but also of a dynamical trajectory, where generic recurrent networks acquire these abilities with a biologically plausible learning rule through trial and error. Furthermore, the networks generalize their experience in the stimulus-evoked samples to the inference without partial or all sensory information, which suggests a computational role of spontaneous activity as a representation of the priors as well as a tractable biological computation for marginal distributions. These findings suggest that chaotic neural dynamics may serve for the brain function as a Bayesian generative model.

60 APPLIED LIFE SCIENCES↗

Rapid sampling of stochastic displacements in Brownian dynamics simulations

Here, we present a new method for sampling stochastic displacements in Brownian Dynamics (BD) simulations of colloidal scale particles. The method relies on a new formulation for Ewald summation of the Rotne-Prager-Yamakawa (RPY) tensor, which guarantees that the real-space and wave-space contributions to the tensor are independently symmetric and positive-definite for all possible particle configurations. Brownian displacements are drawn from a superposition of two independent samples: a wave-space (far-field or long-ranged) contribution, computed using techniques from fluctuating hydrodynamics and non-uniform fast Fourier transforms; and a real-space (near-field or short-ranged) correction, computed using a Krylov subspace method. The combined computational complexity of drawing these two independent samples scales linearly with the number of particles. The proposed method circumvents the super-linear scaling exhibited by all known iterative sampling methods applied directly to the RPY tensor that results from the power law growth of the condition number of tensor with the number of particles. For geometrically dense microstructures (fractal dimension equal three), the performance is independent of volume fraction, while for tenuous microstructures (fractal dimension less than three), such as gels and polymer solutions, the performance improves with decreasing volume fraction. This is in stark contrast with other related linear-scaling methods such as the force coupling method and the fluctuating immersed boundary method, for which performance degrades with decreasing volume fraction. Calculations for hard sphere dispersions and colloidal gels are illustrated and used to explore the role of microstructure on performance of the algorithm. In practice, the logarithmic part of the predicted scaling is not observed and the algorithm scales linearly for up to 4×10 6 particles, obtaining speed ups of over an order of magnitude over existing iterative methods, and making the cost of computing Brownian displacements comparable to the cost of computing deterministic displacements in BD simulations. Finally, a high-performance implementation employing non-uniform fast Fourier transforms implemented on graphics processing units and integrated with the software package HOOMD-blue is used for benchmarking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Level Understanding of the Free Energy Landscape in Early Stages of Metal-Organic Framework Nucleation

The assembly mechanism of hierarchical materials controlled by the choice of solvent and presence of spectator ions. In this paper, we use enhanced sampling molecular dynamics methods to investigate these effects on the configurational landscape of metal-linker interactions in the early stages of synthesis, using MIL-101(Cr) as a prototypical example. Microsecond-long well-tempered metadynamics (WTmetaD) uncover a complex free energy structural landscape, with distinct crystal (C) and non-crystal (NC) like configurations and their equilibrium population. In presence of ions (Na+, F-), we observe a complex effect on the crystallinity of secondary building units (SBUs), by encouraging/suppressing salt bridges between C configurations and consequently controlling the percentage of defects. Solvent effects are assessed by introducing N, N-dimethylformamide (DMF) instead of water, where SBU adducts are appreciably more stable and compact. These results shed light on how solvent nature and ionic strength impact the free energy of nucleation phenomena that ultimately control materials synthesis and defect formation. The work described in this publication was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences and performed at Pacific Northwest National Laboratory (PNNL). The authors acknowledge the use of the UCL Legion High Performance Computing Facility (Legion @ UCL) and associated support services in the completion of this work. This research used resources of the National Energy Research Scientific Computing Centre, a DOE Office of Science User Facility. Battelle operates PNNL for DOE under Contract DE-AC05-76RL01830.

Kollias, Loukas↗

Electrical conductivity of Sn at high pressure and temperature

To date, temperature and conductivity have many outstanding implications in extreme environments but are yet to be fully understood under high pressure and temperature dynamic conditions. Here, we introduce an approach to provide high quality electrical conductivity results under dynamic loading conditions. Emphasis is given to address the skin depth effect's influence in a dynamic loading experiment by using thin films. The thin film samples in this study were at least 100 times thinner than previous samples in dynamic electrical conductivity experiments, increasing the current density to its full potential across the sample's entire cross section. Consideration of the skin depth accounts for at minimum a 4× scaling factor to the final electrical conductivity result that has been neglected in previous dynamic electrical conductivity studies. We also obtained improved signal-to-noise ratio with custom diagnostics optimized for better electrical impedance matching. Furthermore, these considerations were applied to Sn to assess electrical conductivity at elevated pressure and temperature. The high signal-to-noise ratio with reduced skin depth influence results in Sn allowing observation of the conductivity changes related to solid-to-solid and solid-to-liquid phase transitions. Additionally, we calculate the Sn thermal conductivity using the Wiedemann-Franz law for our experiments and compare against thermal transport dependent temperature measurements from previous work.

36 MATERIALS SCIENCE↗

Development of a Data Acquisition System for Kinetic Inductance Detectors: Wide Dynamic Range and High Sampling Rate for Astronomical Observation

Microwave kinetic inductance detectors have a variety of potential applications in astronomical observations. We built a data acquisition system for kinetic inductance detectors combining a dedicated analog board and a commercially available digital board to meet the requirements of astronomical measurements, such as observation of the cosmic microwave background. This paper reports the status of the development of the data acquisition system. We have already achieved simultaneous readout through 120 channels using a direct down-conversion method to decode the signal. A variety of software has been developed and tested using the functionalities of the system and actual detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Neural network potentials with effective charge separation for non-equilibrium dynamics of ionic solids: a ZnO case study

Developing neural network potentials (NNPs) accurate under non-equilibrium dynamics is challenging, as such systems require extensive sampling beyond equilibrium phases. Here we construct high-fidelity NNPs for zinc oxide (ZnO), a polymorphic ionic solid, using density functional theory (DFT) reference data. To efficiently capture transitional configurations, we combine enhanced-sampling molecular dynamics with empirical potentials, data distillation, and pretraining on short-range atomic energies (A-Train), followed by transfer learning with DFT-relabeled datasets. This hierarchical approach improves transferability across polymorphs and stress states. We further introduce effective charge separation, treating long-range Coulombic terms analytically while short-range residual interactions are learned by the NNP. The optimal effective charges fall in the range 0.5–1.0 q e , consistent with dielectric-screened values derived from formal charges but distinct from Bader estimates. Motivated by this observation, we propose a simple data-driven protocol in which effective charges are optimized by comparing DFT reference energies with explicit Coulomb calculations, without additional NNP training. This strategy improves accuracy and transferability in DFT-level predictions of energies, forces, and stress. Together, these results provide a practical charge-selection framework for robust NNP development in ionic solids, enabling reliable simulation of polymorphic phase transformations and non-equilibrium dynamics.

Chemistry↗

Variational control forces for enhanced sampling of nonequilibrium molecular dynamics simulations

We introduce a variational algorithm to estimate the likelihood of a rare event within a nonequilibrium molecular dynamics simulation through the evaluation of an optimal control force. Optimization of a control force within a chosen basis is made possible by explicit forms for the gradients of a cost function in terms of the susceptibility of driven trajectories to changes in variational parameters. We consider probabilities of time-integrated dynamical observables as characterized by their large deviation functions and find that in many cases, the variational estimate is quantitatively accurate. Additionally, we provide expressions to exactly correct the variational estimate that can be evaluated directly. We benchmark this algorithm against the numerically exact solution of a model of a driven particle in a periodic potential, where the control force can be represented with a complete basis. Additionally, we then demonstrate the utility of the algorithm in a model of repulsive particles on a line, which undergo a dynamical phase transition, resulting in singular changes to the form of the optimal control force. In both systems, we find fast convergence and are able to evaluate large deviation functions with significant increases in statistical efficiency over alternative Monte Carlo approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗