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At least 649 records · Page 36

Short-Term Inhibition and Long-Term Enhancement of Irreversible Trace Metal Binding to Goethite in Multi-Metal Systems

Iron (oxyhydr)oxide minerals are important sorbents of trace metals in aquatic environments. Adsorption–desorption hysteresis has been documented for trace metals after aging, suggesting that they become incorporated over time. We previously found that ion size controls the extent of irreversible metal binding of single metals to goethite. In this study, we evaluate how the presence of multiple metals influences irreversible binding. Mixed Ni–Zn and Ni–Cd solutions were aged with goethite at pH 7 for 2 days, 30 days, and 60 days, after which isotope exchange experiments were performed to assess the lability of the adsorbed metal pools. After 2 days of aging, Ni and Cd in mixed-metal systems were more labile than in single-metal systems, indicating that competitive adsorption may partially block irreversible binding on short time scales. After 60 days, all three metals had larger irreversibly bound fractions than in single-metal systems. X-ray absorption near-edge structure (XANES) spectroscopy indicates that irreversibly bound fractions correlate with incorporation into goethite. This study demonstrates that pools of coadsorbed metals are bioaccessible on a time scale of minutes. Cooperative effects promote the structural sequestration of even large trace metals, causing reactive transport models to likely overpredict metal mobility. Long-term metal entrapment processes hinder micronutrient availability, impact contaminant sequestration and critical mineral recovery, and yield complex pathways through which metal solubilization may be enhanced or hindered during redox cycling.

58 GEOSCIENCES↗

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential vaccine target with high sequence conservation across diverse strains. However, despite the potency of NHR-targeting peptides and clinical efficacy of the NHR-targeting entry inhibitor enfuvirtide, no potently neutralizing NHR-directed monoclonal antibodies (mAbs) nor antisera have been identified or elicited to date. The lack of potent NHR-binding mAbs both dampens enthusiasm for vaccine development efforts at this target and presents a barrier to performing passive immunization experiments with NHR-targeting antibodies. To address this challenge, we previously developed an improved variant of the NHR-directed mAb D5, called D5_AR, which is capable of neutralizing diverse tier-2 viruses. Building on that work, here we present the 2.7Å-crystal structure of D5_AR bound to NHR mimetic peptide IQN17. We then utilize protein language models and supervised machine learning to generate small (n < 100) libraries of D5_AR variants that are subsequently screened for improved neutralization potency. We identify a variant with 5-fold improved neutralization potency, D5_FI, which is the most potent NHR-directed monoclonal antibody characterized to date and exhibits broad neutralization of tier-2 and −3 pseudoviruses as well as replicating R5 and X4 challenge strains. Additionally, our work highlights the ability of protein language models to efficiently identify improved mAb variants from relatively small libraries.

Biopolymers↗

Uncertainties in Density and Simulation Parameters for Radiographic Reconstructions Using Machine Learning

We will develop new and improved methods that will enable a fuller and more extensive use of experimental data, such as from radiographic imaging, towards better characterizing and reducing uncertainties in predictive modeling of weapons performance. We will achieve this by leveraging recent developments in the areas of computational imaging, statistical and machine learning, and reduced order modeling. Key new aspects of our approach include (a) a coupling of deep learning based density reconstruction with fast hydrodynamics simulators that will permit the development of certain guarantees on extrapolatability and bounds on certain other hydrodynamics-related para- metric uncertainties and (b) a dual approach towards better characterizing uncertainties in density reconstruction using deep learning based surrogates to accelerate Bayesian reconstructions on the one hand and using variational inference and Bayesian machine learning on the other hand.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE Plasma Science Center - Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems (Final Report DE-SC0001939)

Low temperature plasmas (LTPs) are the plasmas of electron-volt (eV) physics and eV technologies. LTPs have characteristic electron temperatures of a few eV and fractional ionizations that are typically small. Since LTPs have electron temperatures commensurate with the threshold energies of excited states in neutral atoms and molecules, power transfer from electrons to these atoms and molecules efficiently produces activated species (e.g., radicals, excited states, photons). Acceleration of ions in the sheaths of LTPs to energies of tens to hundreds of eV enable activation of surface modifying processes – sputtering, etching, deposition. With such properties, LTPs are often and beneficially used in technological devices, ranging from etching and deposition in microelectronics and solar cell fabrication, to hardening of surgical instruments. LTPs harbor fundamental science issues that are intellectually challenging and rewarding. At the same time, there are enormous societal benefits that are enabled by LTPs. The entire present-day and future information technology infrastructure owes its very existence to LTPs. Renewable energy sources, such as solar cell arrays, could not be economically produced in the absence of deposition and etching by LTPs. In acknowledgment of the importance of LTPs, the DOE Office of Fusion Energy Sciences supported the Plasma Science Center for Predictive Control of Plasma Kinetics: Multi-Phase and Bounded Systems from August 2009 to July 2021, consisting of an initial 5-year grant, 3 funded extensions and 2 no-cost extensions. This is the final report of the Center in which the productivity of the Center is discussed in terms of publications, impact and personnel. High-lights of the research performed in the Center are provided.

36 MATERIALS SCIENCE↗

Generation of the TSL for Zirconium Hydrides from Ab Initio Methods

Zirconium hydride (ZrHx) is a moderator material used in TRIGA and other reactors that may exist in multiple phases with varying stoichiometry, which include the δ phase and the ϵ phase. Current ENDF/B-VIII.0 ZrHx thermal scattering law (TSL) evaluations do not distinguish between phases. These sub-libraries were generated with the LEAPR module of NJOY using historic phonon spectra derived from a central force model and assume incoherent elastic scattering for both bound hydrogen and zirconium, which neglects the effects of crystal structures important for scattering from zirconium bound in ZrHx. In this work, the TSLs for hydrogen and zirconium bound in δ-ZrHx and ϵ-ZrH2 were generated from phonon spectra derived from modern ab initio lattice dynamics methods and ab initio molecular dynamics. Subsequently, TSLs for hydrogen and zirconium in ZrHx and ZrH2 were generated using the Full Law Analysis Scattering System Hub (FLASSH) code. The built-in generalized coherent elastic routine was used to generate the previously neglected elastic contribution from zirconium for this material. The present TSLs provide both a re-evaluation of the current ZrH sub-libraries and expansion of the set of TSLs available for the examination of neutrons in systems with zirconium hydride, permitting explicit treatment of δ and ϵ phases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Exploring nuclear exotica at the limits

The study of nuclear limits has been performed and new physical mechanisms and exotic shapes allowing the extension of nuclear landscape beyond the commonly accepted boundaries have been established. The transition from ellipsoidal to toroidal shapes plays an essential role in potential extension of nuclear landscape to hyperheavy nuclei. Moreover, rotational excitations leading to the birth of particle (proton or neutron) bound rotational bands provide a mechanism for an extension of nuclear landscape beyond spin zero proton and neutron drip lines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving Conversion of Captured CO 2 on Mixed-Oxide Dual-Function Materials by Low-Concentration Metal Promotion

Reactive carbon capture (RCC) is a promising nascent approach to harness the untapped resource of waste CO 2 to produce fuels and platform chemicals. However, process economics relies on the design of dual-function materials (DFMs) that exhibit maximal conversion of captured CO 2 and high selectivity toward valuable carbon products (e.g., CO). Herein, we report the use of low-concentration (ca. 0.5 wt %) metal promotors (Pt and Au) to improve the conversion of captured CO 2 on a Zn-Al mixed-oxide DFM by >30%, while also more than doubling per-cycle CO yield due to enhanced retention of captured CO 2 and H 2 activation. In situ DRIFTS of bound CO 2 on the DFMs showed distinctions in surface carbonate formation for the Pt- and Au-modified materials that were correlated with product evolution during the reactive desorption step of RCC. Particularly, Pt afforded superior H 2 activation but formed irreversibly-bound bicarbonates, compromising overall productivity, while the Na/Au/ZA DFM predominantly adsorbed CO 2 on Na sites, resulting in polydentate carbonates that are retained until higher temperatures before conversion to CO. In conclusion, these results indicate that adding a low concentration of oxidation-resistant noble metals, especially Au, is an effective strategy for improving key performance metrics of Zn-Al mixed-oxide DFMs to further advance the development of scalable RCC technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrocatalytic synthesis of heterocycles from biomass-derived furfuryl alcohols

It is very attractive yet underexplored to synthesize heterocyclic moieties pertaining to biologically active molecules from biomass-based starting compounds. Herein, we report an electrocatalytic Achmatowicz reaction for the synthesis of hydropyranones from furfuryl alcohols, which can be readily produced from biomass-derived and industrially available furfural. Taking advantage of photo-induced polymerization of a bipyridyl ligand, we demonstrate the facile preparation of a heterogenized nickel electrocatalyst, which effectively drives the Achmatowicz reaction electrochemically. A suite of characterization techniques and density functional theory computations were performed to aid the understanding of the reaction mechanism. It is rationalized that the unsaturated coordination sphere of nickel sites in our electrocatalyst plays an important role at low applied potential, not only allowing the intimate interaction between the nickel center and furfuryl alcohol but also enabling the transfer of hydroxide from nickel to the bound furfuryl alcohol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Separation of overlapping sources in bioacoustic mixtures

Source separation is an important step to study signals that are not easy or possible to record individually. Common methods such as deep clustering, however, cannot be applied to signals of an unknown number of sources and/or signals that overlap in time and/or frequency—a common problem in bioacoustic recordings. This work presents an approach, using a supervised learning framework, to parse individual sources from a spectrogram of a mixture that contains a variable number of overlapping sources. This method isolates individual sources in the time-frequency domain using only one function but in two separate steps, one for the detection of the number of sources and corresponding bounding boxes, and a second step for the segmentation in which masks of individual sounds are extracted. This approach handles the full separation of overlapping sources in both time and frequency using deep neural networks in an applicable manner to other tasks such as bird audio detection. This paper presents method and reports on its performance to parse individual bat signals from recordings containing hundreds of overlapping bat echolocation signals. This method can be extended to other bioacoustic recordings with a variable number of sources and signals that overlap in time and/or frequency.

Izadi, Mohammad Rasool↗

A theoretical/computational framework to measure SiO2 and MgO viscosity at high pressure

The convection of the mantle of Earth and super-Earths is important for many terrestrial phenomena, from plate tectonics to outgassing. Rheological properties, such as viscosity, regulate the transport of thermal energy and mass. However, the viscosity of mantle-relevant materials, such as MgO, at relevant pressures (>120 GPa) are not well constrained. The objective of this work was to develop a computational platform to simulate novel experiments aiming to measure the viscosity of MgO at high pressures. Experiments performed by our collaborators at Johns Hopkins University and Lawrence Livermore National Laboratory use the OMEGA EP laser facility to shock a corrugated MgO interface to 170 GPa, with resulting velocity evolution governed by the viscous Richtmyer-Meshkov instability. We used an in-house hydrocode to simulate this process and thus provide a bound on viscosity by comparing our simulations results to these experiments, as well as to examine the physical processes at play. We simulated the experiments with different values of MgO viscosity (from inviscid to 10,000 Pa∙s) while taking into account the unsteady laser pulse, the material's equation of state, and the rate-dependent constitutive relation for MgO, and the materials' equations of state. Our results suggest that MgO at these conditions has a viscosity within an order of magnitude of 5000 Pa∙s.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

First-principles investigation of cerium and neodymium diffusion in BCC chromium and vanadium via vacancy-mediated transport

Lanthanide transport plays a crucial role in the performance and longevity of metallic nuclear fuels. This study examines the diffusion behavior of Ce and Nd—two major fission products—in body-centered cubic (BCC) Cr and V, which are potential liner or coating materials for mitigating fuel-cladding chemical interactions (FCCI). Using density functional theory (DFT) calculations and self-consistent mean-field (SCMF) analysis, the vacancy-mediated diffusion coefficients are evaluated. Our findings reveal that Ce and Nd act as oversized solutes and are strongly bound to vacancies in BCC Cr and V, with diffusivities in Cr significantly lower than in V and in hexagonal closed-packed (HCP) Zr, as investigated in our previous work. The activation energies for Ce and Nd diffusion are 3.39 and 3.32 eV, respectively, in BCC Cr, and 2.56 and 2.33 eV, respectively, in BCC V. Analysis of vacancy drag and partial diffusion coefficient ratios indicates a strong tendency for lanthanide enrichment at vacancy sinks in BCC Cr, and to a lesser extent in BCC V, with this effect persisting up to the melting point in Cr and remaining substantial for Nd in V at high temperatures. Under irradiation, the increase in vacancy concentration is expected to enhance lanthanide transport, potentially accelerating interactions at liner-cladding interfaces. Although BCC Cr exhibits relatively low lanthanide diffusivities under equilibrium conditions, the expected segregation tendencies under irradiation suggest that Zr liners may be a more favorable option. Further investigations using rate theory, cluster dynamics, and phase-field modeling are required to quantitatively assess the performance of these materials in reactor environments.

36 - MATERIALS SCIENCE↗

The FABLE silicon detector array for comprehensive studies of fusion and breakup dynamics

The Fusion and Breakup of Light Elements (FABLE) array, comprised of ΔE-E telescopes of neutron-transmutation doped (NTD) Double-Sided Silicon Strip Detectors (DSSDs), has been developed and commissioned for future experiments at the Facility for Rare Isotope Beams (FRIB). FABLE was designed to perform measurements of complete and incomplete fusion cross sections, to help address the interplay between breakup and clustering in outcomes of reactions with exotic nuclides. Here, the FABLE array has been commissioned in a comprehensive study at the ReAccelerator facility ReA6 of the Facility for Rare Isotope Beams (FRIB), investigating the dynamics in the weakly-bound proton rich 7 Be reaction on 208 Pb targets.

Breakup↗

Investigation of coverage dependence of the stretching frequency of CO adsorbed on Pd surfaces at low coverage limits

The stretching frequency of the C—O bond is a sensitive probe of the local environment of a surface-bound CO molecule, including the adorption site and density, i.e. surface coverage. In this work, we extend our analysis beyond the frequency shift due to differences in adsorption configurations. Using density functional theory (DFT) calculations, we directly explore the correlations between surface coverage and the stretching frequency of adsorbed CO on Pd surfaces. Here we also perform constant pressure infrared reflection absorption measurements of CO on Pd(111) and use existing relations between pressure and coverage to derive coverage dependency. Both results are compared to previously reported experimental data. Our derived correlations of peak frequency and area with surface coverage can help interpret experimental IR spectra in real time and extract time-dependent concentration data from transient kinetic experiments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Newton versus the machine: solving the chaotic three-body problem using deep neural networks

ABSTRACT Since its formulation by Sir Isaac Newton, the problem of solving the equations of motion for three bodies under their own gravitational force has remained practically unsolved. Currently, the solution for a given initialization can only be found by performing laborious iterative calculations that have unpredictable and potentially infinite computational cost, due to the system’s chaotic nature. We show that an ensemble of converged solutions for the planar chaotic three-body problem obtained using an arbitrarily precise numerical integrator can be used to train a deep artificial neural network (ANN) that, over a bounded time interval, provides accurate solutions at a fixed computational cost and up to 100 million times faster than the numerical integrator. In addition, we demonstrate the importance of training an ANN using converged solutions from an arbitrary precise integrator, relative to solutions computed by a conventional fixed precision integrator, which can introduce errors in the training data, due to numerical round-off and time discretization, that are learned by the ANN. Our results provide evidence that, for computationally challenging regions of phase space, a trained ANN can replace existing numerical solvers, enabling fast and scalable simulations of many-body systems to shed light on outstanding phenomena such as the formation of black hole binary systems or the origin of the core collapse in dense star clusters.

Breen, Philip G.↗

Optimality and Noise Resilience of Critical Quantum Sensing

We compare critical quantum sensing to passive quantum strategies to perform frequency estimation, in the case of single-mode quadratic Hamiltonians. We show that, while in the unitary case both strategies achieve precision scaling quadratic with the number of photons, in the presence of dissipation this is true only for critical strategies. We also establish that working at the exceptional point or beyond threshold provides suboptimal performance. This critical enhancement is due to the emergence of a transient regime in the open critical dynamics, and is invariant to temperature changes. When considering both time and system size as resources, for both strategies the precision scales linearly with the product of the total time and the number of photons, in accordance with fundamental bounds. However, we show that critical protocols outperform optimal passive strategies if preparation and measurement times are not negligible. Our results are applicable to a broad variety of critical sensors whose phenomenology can be reduced to that of a single-mode quadratic Hamiltonian, including systems described by finite-component and fully connected models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Independent Technical Review of INL Aluminum-Clad Spent Nuclear Fuel (ASNF) Oxide Layer Radiolytic Gas Generation Resolution: Task 2

PNNL staff performed an independent technical review (ITR) of the aluminum-clad spent nuclear fuel (ASNF) program Task 2. The objective of Task 2 is to determine G-values for the radiolytic production of gaseous molecular hydrogen (H 2 ) from the aluminum oxyhydroxide layers present on ASNF cladding. The G-values need to be defensible, bounding, but not overly conservative. As part of the ITR, the team reviewed program documents, Task 2 work plans, and results to date. In addition, the team held three separate video conferences with the program research staff to ask clarifying questions and obtain additional detail. The PNNL ITR team concludes that if the program follows the methodology and rigor outlined in the test matrices, the program will develop G-values for a defensible technical basis of extended storage of ASNF. Recommendations for improvement are given.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phased Construction Completion Report for Decontamination Laundry Demolition at the Oak Ridge National Laboratory

This Phased Construction Completion Report (PCCR) documents completion of demolition, waste disposition, and slab stabilization activities of Building 2523 (Decontamination Laundry) for the Oak Ridge National Laboratory (ORNL). The Decontamination Laundry is located directly north of the intersection of White Oak Avenue and the 2519 Access Road. This demolition scope included the removal of the above-grade structures and facility components associated with Building 2523. This scope included the removal of Building 2523 (and all remaining contents inside), Trailer 2523A (and all remaining contents inside), an above-grade wastewater tank, and a wooden access porch connecting Buildings 2523 and Trailer 2523A. On the north side of Building 2523, above-grade portions of selected remaining foundations/stairs were removed from former Building 2517 to make room to stage waste containers. Building 2621 is west of the Laundry Building and Buildings 2547 and 2649 are to the east, while Building 2525 is to the north. Building 2523 is located within Bethel Valley Exposure Unit (EU) 3. The total area of the EU is approximately 39 acres. The area within EU 3 is bounded by First Street on the west, Central Avenue on the north, Third Street on the east and south. The slab of Building 2523 has been stabilized with a cap of flowable fill concrete and asphalt to contain residual radiological contamination and to provide surface suitable for vehicle parking. No below-grade demolition actions were performed during this task.

99 GENERAL AND MISCELLANEOUS↗