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The Physics of Hard Spheres Experiment on MSL-1: Required Measurements and Instrument Performance

The Physics of HArd Spheres Experiment (PHaSE), one of NASA Lewis Research Center's first major light scattering experiments for microgravity research on complex fluids, flew on board the Space Shuttle's Microgravity Science Laboratory (MSL-1) in 1997. Using colloidal systems of various concentrations of micron-sized plastic spheres in a refractive index-matching fluid as test samples, illuminated by laser light during and after crystallization, investigations were conducted to measure the nucleation and growth rate of colloidal crystals as well as the structure, rheology, and dynamics of the equilibrium crystal. Together, these measurements support an enhanced understanding of the nature of the liquid-to-solid transition. Achievement of the science objectives required an accurate experimental determination of eight fundamental properties for the hard sphere colloidal samples. The instrument design met almost all of the original measurement requirements, but with compromise on the number of samples on which data were taken. The instrument performs 2-D Bragg and low angle scattering from 0.4 deg. to 60 deg., dynamic and single-channel static scattering from 10 deg. to 170 deg., rheology using fiber optics, and white light imaging of the sample. As a result, PHaSE provided a timely microgravity demonstration of critical light scattering measurement techniques and hardware concepts, while generating data already showing promise of interesting new scientific findings in the field of condensed matter physics.

Doherty, Michael P.↗

Octafluoropropane Concentration Dynamics on Board the International Space Station

Since activating the International Space Station s (IS9 Service Module in November 2000, archival air quality samples have shown highly variable concentrations of octafluoropropane in the cabin. This variability has been directly linked to leakage from air conditioning systems on board the Service Module, Zvezda. While octafluoro- propane is not highly toxic, it presents a significant chal- lenge to the trace contaminant control systems. A discussion of octafluoropropane concentration dynamics is presented and the ability of on board trace contami- nant control systems to effectively remove octafluoropro- pane from the cabin atmosphere is assessed. Consideration is given to operational and logistics issues that may arise from octafluoropropane and other halo- carbon challenges to the contamination control systems as well as the potential for effecting cabin air quality.

Perry, J. L.↗

Fluid System Stability Analysis Techniques

Fluid systems, or networks, consist of multiple components that work together to achieve some desired thermofluid state. For any generic application, this fluid state can be a combination of the fluid pressure, flow rate, enthalpy, or species concentration. Fluid system components, such as pumps and valves, are often governed by nonlinear differential equations, resulting in complex component-to-component interactions. System-level fluid network stability occurs when the flow through the system can maintain a steady-state solution in the presence of small perturbations, which depends on these component interactions. System instability, however, can go undetected until issues arise during integrated system testing. This presentation explores a method for system designers to think of the fluid network as an assembly of components, each with their own thermofluid surfaces of partial stability, called nullclines. The intersections of all nullclines yields system-level solutions, called equilibrium points. When designers define operating points, they are tuning system parameters so that these equilibrium points move to the desired location in the thermofluid state plane. However, linearization theory shows us that the dynamic behavior around these points can be unstable. The local stability of these equilibrium points can be assessed analytically with eigen-analysis, or numerically by propagating state-plane samples to construct a phase portrait. Investigating a phase portrait can help designers gain a qualitative understanding of a system’s dynamic performance. This understanding can then help inform requirement definitions, component selection, and operational procedures. This presentation includes an example of the phase portrait technique on a system featuring a centrifugal pump and a back-pressure regulator (BPR). Numerical modeling of this system suggests that equilibrium points on the left-hand side of the pump curve are dynamically unstable.

Fluid System↗

Fluid System Stability Analysis Techniques

Fluid systems, or networks, consist of multiple components that work together to achieve some desired thermofluid state. For any generic application, this fluid state can be a combination of the fluid pressure, flow rate, enthalpy, or species concentration. Fluid system components, such as pumps and valves, are often governed by nonlinear differential equations, resulting in complex component-to-component interactions. System-level fluid network stability occurs when the flow through the system can maintain a steady-state solution in the presence of small perturbations, which depends on these component interactions. System instability, however, can go undetected until issues arise during integrated system testing. This presentation explores a method for system designers to think of the fluid network as an assembly of components, each with their own thermofluid surfaces of partial stability, called nullclines. The intersections of all nullclines yields system-level solutions, called equilibrium points. When designers define operating points, they are tuning system parameters so that these equilibrium points move to the desired location in the thermofluid state plane. However, linearization theory shows us that the dynamic behavior around these points can be unstable. The local stability of these equilibrium points can be assessed analytically with eigen-analysis, or numerically by propagating state-plane samples to construct a phase portrait. Investigating a phase portrait can help designers gain a qualitative understanding of a system’s dynamic performance. This understanding can then help inform requirement definitions, component selection, and operational procedures. This presentation includes an example of the phase portrait technique on a system featuring a centrifugal pump and a back-pressure regulator (BPR). Numerical modeling of this system suggests that equilibrium points on the left-hand side of the pump curve are dynamically unstable.

Fluid System↗

High definition large area mapping of geological samples using a Maia detector array in the Nuclear Microprobe

A Maia detector array has been utilized and installed on the CSIRO-MARC Nuclear Microprobe. Maia uses an annular array of 384 silicon detectors to provide a solid-angle of 1.3 sr to improve the collection of X-rays induced by Particle Induced X-ray Emission (PIXE) using a micron focussed MeV proton beam. It features event-by-event data acquisition with dead-time correction and pileup rejection and a total count-rate capacity above 10 M/s, versatile stage and beam scanning modes (coupled to the DAQ-36 system described previously) to cater for a variety of sample configuration and experimental needs, precise measurement of transit time and integration of beam fluence per pixel, and spectral deconvolution of event data in real-time using the Dynamic Analysis method to provide element images during data collection. In this work we demonstrate the system on thin sections made from geological samples extracted from active seafloor hydrothermal vents in the PACMANUS hydrothermal field in Papua New Guinea.

36 MATERIALS SCIENCE↗

Data Requirements for Application of Risk-Based Dynamic Contingency Analysis to Evaluate Hurricane Impact to Electrical Infrastructure in Puerto Rico

This paper presents a risk-based dynamic contingency analysis framework that was used to evaluate the hurricane impact to electrical infrastructure in Puerto Rico. PNNL developed a scalable risk-based framework for identifying high-voltage transmission resilience improvements by classifying and prioritizing high-risk power grid contingencies (system failures) under hurricane impact. The risk-based framework is founded on grid outage definitions with their associated probabilities of occurrence from hurricane events, in combination with an impact assessment derived from detailed dynamic cascading failure analysis. This paper focuses on a discussion around data requirements for transmission resilience planning for hurricane events, derived from the development of the risk-based framework and its application to Puerto Rico. This paper launches an important first step in encouraging the engineering community and power system industry to move towards establishing resilience planning as a routine practice. Since actual results for Puerto Rico contain sensitive information, sample simulation results will be used to illustrate the data requirements and risk-based dynamic cascading framework on the Puerto Rico power grid, as well as demonstrate the potential for such a simulation framework. The paper includes a discussion on the lessons learned, importance and need for improved datasets that are not usually considered in traditional power system planning. The paper will also elaborate on how the scalable simulation framework and datasets might be expanded to larger footprints and leveraged for modelling other types of natural disasters.

DCAT, Puerto Rico, hurricane, Power System Stabili↗

Dynamics of Single Chains of Suspended Ferrofluid Particles

We present an experimental study of the dynamics of isolated chains made of super-paramagnetic particles under the influence of a magnetic field. The motivation of this work is to understand if the chain fluctuations exist and, if it does, how does the fluctuation affect chain aggregation. We find that single chains strongly fluctuate and that the characteristic frequency of their fluctuations is inversely proportional to the magnetic field strength. The higher the field the lower the characteristic frequency of the chain fluctuations. In the high magnetic field limit, chains behave like rigid rods without any internal motions. In this work, we used ferrofluid particles suspended in water. These particles do not have any intrinsic magnetization. Once a magnetic field is applied, a dipole moment is induced in each particle, proportional to the magnetic field. A dipolar magnetic interaction then occurs between particles. If dipole-dipole magnetic energy is higher than the thermal energy, the result is a structure change inside the dipolar fluid. The ratio of these two energies is expressed by a coupling constant lambda as: lambda = (pi(a(exp 3))(chi(exp 2))(mu(sub 0))(H(sub 0))(exp 2))/18kT Where a is the particle radius, mu(sub 0) is the vacuum magnetic permeability, H(sub 0) the applied magnetic field, k the Boltzmann constant and T the absolute temperature. If lambda > 1, magnetic particles form chains along the field direction. The lateral coalescence of several chains may form bigger aggregates especially if the particle volume fraction is high. While many studies and applications deal with the rheological properties and the structural changes of these dipolar fluids, this work focuses on the understanding of the chain dynamics. In order to probe the chain dynamics, we used dynamic light scattering (DLS) in self-beating mode as our experimental technique. The experimental geometry is such that the scattering plane is perpendicular to the magnetic field. Therefore, only motions in this plane are probed. A very dilute sample of a ferrofluid emulsion with a particle volume fraction of 10(exp -5) is used in this experiment. We chose such a low volume fraction to avoid multiple light scattering as well as lateral chain-chain aggregation. DLS measures the dynamic structure factor S(q,t) of the sample (q is the scattering wave vector, t is the time). In the absence of the magnetic field, identical particles of ferrofluid droplets are randomly distributed and S(q,t) reduces to exp(-q(exp 2)2D(sub 0)t). D(sub 0)=(kT/(6(pi)(eta)(a)) is the diffusion coefficient of Brownian particles (where Xi = (6(pi)(eta)(a)) is the Stokes frictional coefficient of a spherical particle in a fluid of viscosity eta). If interactions or polydispersity can not be ignored, an effective diffusion coefficient is introduced. Formally, D(sub eff) is defined as: D(sub eff) = - q(exp -2) partial derivative of (ln(S(q,t)) with respect to time, as t goes to 0. D(sub eff) reduces to D(sub 0) if no interactions and only a few particles size are present. Therefore, we can use DLS to measure particle size. The particle radius was found to be a=0.23 mu m with 7% of polydispersity. In this case, if we vary the scattering angle theta (and so q) we do not have any change in the measured diffusion coefficient: it is q-independent. When a magnetic field is applied, particles aggregate into chains if lambda > 1. We first studied the kinetics of the chain formation when lambda = 406. At a fixed scattering angle, we measured diffusion coefficient D(sub eff) as a function of time. Experimentally, we find that D(sub eff) decreases monotonously with time. Physically, this means that chains are becoming longer and longer. Since we are only sensitive to motions in the scattering plane and since chains have their main axis perpendicular to this plane, the measured diffusion coefficient is the trans-verse diffusion coefficient. We can relate D(sub eff) to the mean number of particles per chain N(t) at a given time and to the diffusion coefficient of an isolated particle D(sub 0) as D(sub eff)=f(N(t))D(sub 0). Since f(N) is known from other recent work, N can be expressed as a function of the time. We found a square root dependency: N(t) proportional to the square root of t. As expected for very low volume fraction, this behavior is characteristic of a diffusion-limited aggregation as suggested by several authors and by our previous work. In this study, we focus on the dependence of the effective diffusion coefficient on the scattering angle and the magnetic field strength. After the magnetic field is applied (lambda = 406) for a long time, typically 6 hours, kinetics of chain formation becomes very slow. Chain size does not vary much over the next hour period. Thus, we can perform different interesting experiments. First, at a fixed magnetic field, we measure the effective diffusion coefficient as a function of the scattering angle (from 5 to 130 deg). Our results show that the measured diffusion coefficient increases linearly with the scattering angle: D(sub eff) proportional to q. If we do the same experiment for different lambda values, D(sub eff) depends on lambda as D(sub eff) proportional to lambda(exp -1/2). We also find for different lambda values that the same asymptotic D(sub eff) value is obtained when q approaches zero. The angle dependency of D(sub eff) suggests that an additional motion exists besides chain drifting. Chain size is constant during experiment, which was verified by measuring the same diffusion coefficient at the beginning and at the end of the angle switching. If chains are rigid, D(sub eff) is independent of q. Therefore, we found that D(sub eff) not only measures the motion of the entire chain but also its internal fluctuations. These internal motions are the fluctuations of the particles in the chain. To understand the q dependency of D(sub eff), let us look at the probing length used. In our study, the characteristic length scale probed is l=2pi/q which is in the range of 0.9<l/a<20. When l is much larger than the particle radius (l/a going to infinity) we are mainly sensitive to the center of mass diffusion of the chain. D(sub eff) is then the diffusion of the entire chain and depends only on N but not on q and lambda. The value D(sub eff) allows us to obtain the number of particles per chain N. In the opposite limit (i.e. l/a < 1), we are sensitive to motions on the size of individual particles. The main contributions to the measured diffusion coefficient come from internal motions of the chains (i.e. particles' fluctuations inside the chain). We investigated also the effect of the chain size on D(sub eff). For the same value of the magnetic interaction lambda and different chain sizes, we found that the slope of D(sub eff) versus q decreases when N increases as a power law D(sub eff) proportional to N(exp -0.7). This is an important behavior because this means that the longer the chain the slower its internal fluctuations besides the whole chain motion.

Cutillas, S.↗

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Environmental fate of radiocesium in biota inhabiting a contaminated ecosystem on the U.S. Department of Energy's Savannah River Site

Although biomagnification of radiocesium ( 137 Cs) has been reported in food webs, most previous research has been limited to select trophic linkages. Few studies have included a comprehensive survey of fauna associated with aquatic, semi-aquatic, and terrestrial habitats within a single study framework. The objectives of this study were to advance our understanding of the dynamics of 137 Cs accumulation within food webs by quantifying 137 Cs activity across a wide range of biota found within a contaminated canal, as well as test the hypothesis that life-stage and body size influence 137 Cs bioaccumulation in select herpetofauna. With extensive sampling across multiple taxa collected from a contaminated canal system and associated floodplain on the Savannah River Site, we assessed 137 Cs activity and stable nitrogen isotopes for both aquatic organisms that were restricted to the contaminated effluent canal, and semi-aquatic organisms able to move freely between the contaminated canal and the adjacent uncontaminated terrestrial habitat. We found 137 Cs activity to be highly variable among species, with evidence for and against biomagnification in semi-aquatic and aquatic organisms, respectively. Furthermore, 137 Cs activity decreased with life stage and body size in bullfrogs (Lithobates catesbeianus), despite post-metamorphic bullfrogs having a more carnivorous diet compared to tadpoles, while cottonmouths (Agkistrodon piscivorus) retained similar 137 Cs activity regardless of their age and size. While evidence of biomagnification has been observed in some contaminated systems, results of our study suggest the extent to which 137 Cs biomagnifies within food webs is context-dependent and likely influenced by a suite of biotic and abiotic factors. Further, our data indicate sampling of a broad suite of species and environmental attributes are needed to elucidate the fate and dynamics of anthropogenic pollutants within contaminated ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Revealing subterahertz atomic vibrations in quantum paraelectrics by surface-sensitive spintronic terahertz spectroscopy

Understanding surface collective dynamics in quantum materials is crucial for advancing quantum technologies. For example, surface phonon modes in quantum paraelectrics are thought to be essential in facilitating interfacial superconductivity. However, detecting these modes, especially below 1 terahertz, is challenging because of limited sampling volumes and the need for high spectroscopic resolution. Here, we report surface soft transverse optical (TO1) phonon dynamics in KTaO 3 and SrTiO 3 by surface-sensitive spintronic terahertz spectroscopy that can sense the collective modes only a few nanometers deep from the surface. In KTaO 3 , the TO1 mode softens and sharpens with decreasing temperature, leveling off at 0.7 terahertz. In contrast, this mode in SrTiO 3 broadens substantially below the quantum paraelectric crossover and coincides with the hardening of a sub–milli–electron volt phonon mode related to the antiferrodistortive transition. These observations that deviate from their bulk properties may have implications for interfacial superconductivity and ferroelectricity. The developed technique opens opportunities for sensing low-energy surface collective excitations.

Chu, Zhaodong↗

A model study of potential sampling errors due to data scatter around expendable bathythermograph transects in the tropical Pacific

A linear multiple vertical-mode model described by McPhaden et al. (1988) is used to examine potential errors due to data scatter around expendable bathythermograph (XBT) transects in the tropical Pacific. Two methods of sampling are compared. In the first, the model was sampled along approximately straight lines of grid points corresponding to the mean positions of XBT tracks in the eastern, central, and western Pacific; in the second, the model was sampled again at the dates and locations of actual XTB casts for 1979-1983. The model indicates that the data scattered zonally around XBT transects in general can lead to about 2 dyn cm error in dynamic height in composite sections of XBT data. Errors larger than 2 dyn cm occurred in regions where XBT sample spacing in the zonal direction was insufficient to resolve Rossby wave variations in the model.

Mcphaden, Michael J.↗

Isotope effects in liquid water via deep potential molecular dynamics

A comprehensive microscopic understanding of ambient liquid water is a major challenge for ab initio simulations as it simultaneously requires an accurate quantum mechanical description of the underlying potential energy surface (PES) as well as extensive sampling of configuration space. Due to the presence of light atoms (e.g. 𝐻 or 𝐷), nuclear quantum fluctuations lead to observable changes in the structural properties of liquid water (e.g. isotope effects), and therefore provide yet another challenge for ab initio approaches. In this work, we demonstrate that the combination of dispersion-inclusive hybrid density functional theory (DFT), the Feynman discretised path-integral (PI) approach, and machine learning (ML) constitutes a versatile ab initio based framework that enables extensive sampling of both thermal and nuclear quantum fluctuations on a quite accurate underlying PES. In particular, we employ the recently developed deep potential molecular dynamics (DPMD) model – a neural-network representation of the ab initio PES – in conjunction with a PI approach based on the generalised Langevin equation (PIGLET) to investigate how isotope effects influence the structural properties of ambient liquid 𝐻⁢2⁢𝑂 and 𝐷⁢2⁢𝑂. Through a detailed analysis of the interference differential cross sections as well as several radial and angular distribution functions, we demonstrate that this approach can furnish a semi-quantitative prediction of these subtle isotope effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of solvation on the electronic resonances in uracil

Interactions of low-energy electrons with the DNA and RNA nucleobases are known to form metastable states, known as electronic resonances. In this work, we study electron attachment to solvated uracil, an RNA nucleobase, using the orbital stabilization method at the Equation of Motion-Coupled Cluster for Electron Affinities with Singles and Doubles (EOM-EA-CCSD) level of theory with the Effective Fragment Potential (EFP) solvation method. We benchmarked the approach using multireference methods, as well as by comparing EFP and full quantum calculations. The impact of solvation on the first one particle (1p) shape resonance, formed by electron attachment to the π* LUMO orbital, as well as the first two particle one hole (2p1h) resonance, formed by electron attachment to neutral uracil's π–π* excited state, was investigated. We used molecular dynamics simulations for solvent configurations and applied charge stabilization technique-based biased sampling to procure configurations adequate to cover the entire range of the electron attachment energy distribution. The electron attachment energy in solution is found to be distributed over a wide range of energies, between 4.6 eV to 6.8 eV for the 2p1h resonance, and between −0.1 eV to 2 eV for the 1p resonance. The solvent effects were similar for the two resonances, indicating that the exact electron density of the state is not as important as the solvent configurations. Multireference calculations extended the findings showing that solvation effects are similar for the lowest four resonances, further indicating that the specific solute electron density is not as important, but rather the water configurations play the most important role in solvation effects. Lastly, by comparing bulk solvation to clusters of uracil with a few water molecules around it, we find that the impact of microsolvation is very different from that of bulk solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Detecting population-environmental interactions with mismatched time series data

Time series analysis is an essential method for decomposing the influences of density and exogenous factors such as weather and climate on population regulation. However, there has not been much work focused on understanding how well commonly collected data can reconstruct the effects of environmental factors on population dynamics. We show that, analogous to similar scale issues in spatial data analysis, coarsely sampled temporal data can fail to detect covariate effects when interactions occur on timescales that are fast relative to the survey period. We propose a method for modeling mismatched time series data that couples high-resolution environmental data to low-resolution abundance data. We illustrate our approach with simulations and by applying it to Florida's southern Snail kite population. Our simulation results show that our method can reliably detect linear environmental effects and that detecting nonlinear effects requires high-resolution covariate data even when the population turnover rate is slow. In the Snail kite analysis, our approach performed among the best in a suite of previously used environmental covariates explaining Snail kite dynamics and was able to detect a potential phenological shift in the environmental dependence of Snail kites. Our work provides a statistical framework for reliably detecting population–environment interactions from coarsely surveyed time series. An important implication of this work is that the low predictability of animal population growth by weather variables found in previous studies may be due, in part, to how these data are utilized as covariates.

54 ENVIRONMENTAL SCIENCES↗

Non-monotonic temperature dependence of nanoscopic dynamics measured in living housefly larvae

We have studied nanoscopic dynamics on pico-to nano-second time scale in living housefly ( Musca domestica ) larvae using quasielastic neutron scattering. Model-independent data exhibit two distinct dynamic components measurable on the time scale probed in the experiment. The broad component is reminiscent of water dynamics, but somewhat slower, and must be associated with the scattering contribution from the hemolymph in larvae. The narrow (slow) component is similar in appearance to the dynamics measured previously in the living planarian flatworms. Unlike the monotonic temperature dependence for the hemolymph dynamics, the temperature dependence for the slow dynamic component shows an increase at 298 K, in the middle of the measured (on cooling down) range of 303.8 to 289.3 K. A similar increase at 298 K, in the middle of the measured (on warming up, and with different sample environment temperature control equipment used) range of 284.5–304.1 K, has been previously observed for the slow dynamic component in living planarian flatworms. Here, an increase in the measurable nanoscopic dynamics at a mid-range temperature of 298 K, decoupled from the hemolymph dynamics, is an unexpected phenomenon, apparently observable among organisms from different phyla, such as flatworms and arthropods.

59 BASIC BIOLOGICAL SCIENCES↗

Contaminant Leaching From Intact Saltstone Monoliths - 17517

At the Department of Energy's (DOE's) Savannah River Site (SRS) chemically reducing materials, such as blast furnace slag (BFS), are added to grout formulations mixed with low-level radioactive salt solution in order to enhance the attenuation of redox sensitive contaminants (e.g., technetium-99 (Tc-99)). The resulting cementitious material, known as saltstone, is deposited in a series of concrete vaults for permanent disposal at the Saltstone Disposal Facility (SDF). Under oxidizing conditions, Tc persists as an anion in the +7 oxidation state, i.e., pertechnetate (TcO{sub 4}{sup -}), with very limited retention generally associated with amphoteric soil oxides. However, Tc(VII) is subject to chemical reduction to the +4 oxidation state, which is less soluble and mobile in the environment. Thus, chemically reducing grouts provide both a physical (i.e., low saturated hydraulic conductivities (K{sub sat}) that limit H{sub 2}O turnover and O{sub 2} exposure) and chemical barrier (i.e., residual reductive capacity) to contaminant release. However, many of the previous experiments evaluating the ability of saltstone to chemically reduce and immobilize Tc have been conducted using ground saltstone materials as sorbents, a practice that is likely to reduce the moisture level in the material, enhance exposure to O{sub 2} and alter sorbent properties in an unpredictable manner. Therefore, the objective of the current study was to evaluate contaminant leaching from intact monoliths that better represent the initial physical and chemical state of saltstone within the SDF disposal units. For the current study, saltstone simulants were produced utilizing SRR prescribed formulations: initial batches were spiked with rhenium (Re) to serve as nonradioactive analog for Tc-99, and subsequent batches were spiked with Tc-99 for comparison. The relative concentrations of I, Re and Tc-99 in the salt-waste simulants were consistent with the average concentrations of I-129 and Tc-99 in the low-level feed waste. In addition, SRR retrieved intact monoliths from Saltstone Disposal Unit (SDU) Cell 2A in 2015 for testing. Contaminant mass transfer rates for Tc-99 and other contaminants from spiked saltstone simulants and actual SDF saltstone samples were assessed using EPA Method 1315, Mass Transfer Rates of Constituents in Monolithic or Compacted Granular Materials Using a Semi-Dynamic Tank Leaching Procedure. This method was recently adopted for evaluating contaminant leaching from intact monolithic materials. Given the importance of redox speciation in controlling the mobility of Tc-99, the EPA mass transfer tests for the spiked simulants were initially conducted using leachates in equilibrium with three different test atmospheres: (1) oxic, (2) anoxic, and (3) anoxic reducing. Nitrate (NO{sub 3}{sup -}) leaching was evaluated as a poorly retained waste constituent. The leaching behavior of cesium-137 (Cs-137), representing about 98% of the initial radioactivity of the saltstone, was also evaluated for the SDU-extracted samples. Results from Method 1315 were also compared to a novel Dynamic Leaching Method (DLM) in which a flexible-wall permeameter was used to achieve saturated leaching under an elevated hydraulic gradient in an effort to evaluate the persistence of reductive capacity and subsequent changes in contaminant partitioning within intact saltstone monoliths. The composition of the chemical leachates from both tests was thoroughly analyzed in an effort to identify potential solid phases controlling contaminant partitioning through geochemical modeling. For the EPA 1315 tests using spiked simulants, Re leaching rates (and other poorly sorbing contaminants like NO{sub 3}{sup -} and iodine), as indicated by high effective diffusivities (D{sub e}) and low leachability indices (i.e. LI = - log[D{sub e}]), were much higher than Tc-99, which was attributed to poor initial reduction and/or rapid oxidation of Re, indicating that Re is a poor chemical analog for evaluating Tc partitioning under reducing conditions. Technetium-99 leaching rates for the spiked saltstone samples also appeared to be sensitive to the estimated reduction capacity of the dry feed materials used in making grout, a characteristic that can vary between different BFS sources. Technetium-99 leaching rates for the intact saltstone samples in the EPA 1315 test were quite similar, with less variability between the three test samples. This may be indicative of the longer curing time before the SDF samples were tested (∼3 years). Somewhat surprisingly, the leaching rates for Cs-137 from the SDF samples were generally lower than the poorly sorbing contaminants, NO{sub 3}{sup -} and iodine. For the DLM tests, Re leaching from spiked saltstone was much higher than observed for Tc-99, with rates similar to that of non-reactive grout constituents, consistent with EPA 1315 leaching rates. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Learning dynamical systems from data: An introduction to physics-guided deep learning

Modeling complex physical dynamics is a fundamental task in science and engineering. Traditional physics-based models are first-principled, explainable, and sample-efficient. However, they often rely on strong modeling assumptions and expensive numerical integration, requiring significant computational resources and domain expertise. While deep learning (DL) provides efficient alternatives for modeling complex dynamics, they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret. Physics-guided DL aims to integrate first-principled physical knowledge into data-driven methods. It has the best of both worlds and is well equipped to better solve scientific problems. Recently, this field has gained great progress and has drawn considerable interest across discipline Here, we introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems. We describe the learning pipeline and categorize state-of-the-art methods under this framework. We also offer our perspectives on the open challenges and emerging opportunities.

97 MATHEMATICS AND COMPUTING↗

Picosecond Dynamical Response to a Pressure-Induced Break of the Tertiary Structure Hydrogen Bonds in a Membrane Chromoprotein

In this work, we used elastic incoherent neutron scattering (EINS) to find out if structural changes accompanying local hydrogen bond rupture are also reflected in global dynamical response of the protein complex. Chromatophore membranes from LH2-only strains of the photosynthetic bacterium Rhodobacter sphaeroides, with spheroidenone or neurosporene as the major carotenoids, were subjected to high hydrostatic pressure at ambient temperature. Optical spectroscopy conducted at high pressure confirmed rupture of tertiary structure hydrogen bonds. In parallel, we used EINS to follow average motions of the hydrogen atoms in LH2, which reflect the flexibility of this complex. A decrease of the average atomic mean square displacements of hydrogen atoms was observed up to a pressure of 5 kbar in both carotenoid samples due to general stiffening of protein structures, while at higher pressures a slight increase of the displacements was detected in the neurosporene mutant LH2 sample only. These data reflect a correlation between the local pressure-induced breakage of H-bonds, observed in optical spectra, with the altered protein dynamics monitored by EINS. The slightly higher compressibility of the neurosporene mutant sample shows that even subtle alterations of carotenoids are manifested on a larger scale and emphasize a close connection between the local structure and global dynamics of this membrane protein complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗