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At least 1,135 records · Page 63

Implementation of a Dose-based Compliance System for WCS - 19178

Waste Control Specialists LLC (WCS) operates a low-level radioactive waste (LLRW) disposal facility in Andrews, Texas. The site includes a compact waste facility (CWF) that began receiving waste in 2012, a federal waste facility (FWF) that started receiving waste in 2013, as well as a Resource Conservation and Recovery Act (RCRA) landfill and a byproduct facility. The current site license uses a complex system of concentration-based investigation levels and action levels (ILs and ALs) coupled with analytical decision levels (ADLs) that, when exceeded, require specific steps to be taken. These concentration-based ILs and ALs are media specific (i.e. air, soil, water), radionuclide specific, location specific, and disposal facility specific. This results in thousands of individual ILs, ALs, and ADLs that need to be managed and evaluated routinely in order to demonstrate compliance. Further, under the current system, each exceedance of an IL and AL can trigger comparisons to numerous additional isotopic ILs per sample, which is cumbersome, error prone, and costly. This paper describes implementation of a dose-based compliance system that has been developed to replace the existing system. The dose-based compliance system is implemented in RACER{sup C}, a cloud-based software developed by Risk Assessment Corporation (RAC). This system maintains all the analytical results related to the sampling and analysis conducted as part of the Radiological Environmental Monitoring Program (REMP) together with the geo-spatial data allowing instantaneous trending and analysis of the data. Further, the system contains the information needed to compare the analytical results to the new media-specific screening levels that have been developed, and the parameters and routines to compute doses using prescribed exposure scenarios and dose coefficients for compliance evaluation. Once measurement data are entered into RACER, the routines for continuous screening of air, soil, groundwater, and dosimeter data are triggered, and any sample result failing the screening step or exceeding the dose IL/AL is identified and flagged automatically for further review or action, as appropriate. Because RACER is cloud-based, the data, screening, and dose calculations can be accessed remotely at any time, providing a timely and efficient method for identifying any possible releases from the site to the environment as well as determining the potential dose consequences associated with a release. Furthermore, the system is accessible by the regulator providing transparency and ensuring they remain fully informed in an efficient manner. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Long-Term Stewardship Optimization for a Decommissioned Nuclear Reactor - 19579

The decommissioned Hallam Nuclear Power Facility (Hallam), located in Lancaster County, Nebraska, approximately 19 miles south of Lincoln, was developed as a prototype to investigate the technical and economic feasibility of a sodium-cooled, graphite-moderated nuclear reactor. As part of its Power Demonstration Program, the US Atomic Energy Commission (US AEC), a predecessor agency of the US Department of Energy (US DOE), operated the Hallam reactor from 1962 to 1964. The radiological surveillance of the Hallam site was established when the operating agreement between AEC and the Nebraska Public Power District was terminated. The US DOE Chicago Operations Office and the Nebraska Department of Health (NDH) agreed to install a shallow groundwater monitoring system as part of the environmental surveillance program. Surveillance at the site was scheduled to end in fiscal year 2005, with no further activities planned after that. At that time, the plan was to transition the site to the Nebraska Public Power District with future use of the facility to remain restricted. US DOE has title to and responsibility for the entombed radioactive materials. A surveillance and monitoring program was initiated in 1970 by NDH and was funded by US AEC. It included the analysis of samples from deep production wells (groundwater from the regional aquifer at depths greater than 55 meters [180 feet]) at the Sheldon Station. NDH was concerned in 1990 about the possibility of shallow groundwater coming in contact with the buried radiological materials along the buried walls of the reactor. Subsequently, DOE and NDH agreed to further characterize hydrologic conditions and establish a monitoring program in the shallow, perched groundwater zones. The current monitoring program focuses on the shallow, perched groundwater. Today, decades since facility decommissioning, site inspections and groundwater monitoring continue at this Cold War-era legacy site. The US DOE Office of Legacy Management (LM) monitors groundwater as a best management practice in response to a request from the Nebraska Department of Health and Human Services (DHHS). In 2006, LM recommended discontinuing groundwater monitoring because analytical results since 1970 demonstrated there had been no impact to shallow, perched groundwater and no current or anticipated unacceptable risk to human health and the environment. The State of Nebraska did not concur with the recommendation to stop monitoring but did agree to a reduction in sampling and analysis from once a year to once every 2 years--a schedule that began in 2008. An updated assessment of the groundwater monitoring effort was issued in 2016. The entire body of water-quality data continues to demonstrate that there have been no negative impacts to the shallow, perched groundwater from radioactive materials entombed at the site 46 years ago. LM, with concurrence from Nebraska DHHS, changed the sampling frequency, effective in 2018, as follows: once every 5 years from 2021 to 2041 and once every 10 years from 2041 to 2071. In summary, LM remains committed to its primary mission to protect human health and the environment at each of its 92 legacy sites. With results from groundwater sampling events demonstrating compliance for 48 years, the Hallam site was able to set an LM benchmark to optimize long-term stewardship and define an end-state strategy for other decommissioned reactor facilities across the DOE complex. Continued collaboration with local communities, stakeholder, and regulators often leads to outcomes of sound protectiveness without compromise to safety or compliance, as demonstrated by the optimization of the long-term stewardship at the Hallam site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

THCM Coupled Model for Hydrate-Bearing Sediments: Data Analysis and Design of New Field Experiments (Marine and Permafrost Settings)

Gas hydrates are solid compounds made of water molecules clustered around low molecular weight gas molecules such as methane, hydrogen, and carbon dioxide. Methane hydrates form under pressure (P) and temperature (T) conditions that are common in sub-permafrost layers and in deep marine sediments. Stability conditions constrain the occurrence of gas hydrates to submarine sediments and permafrost regions. The amount of technically recoverable methane trapped in gas hydrate may exceed 104tcf. Gas hydrates are a potential energy resource, can contribute to climate change, and can cause large-scale seafloor instabilities. In addition, hydrate formation can be used for CO2 sequestration (also through CO2-CH4 replacement), and efficient geological storage seals. The experimental study of hydrate bearing sediments has been hindered by the very low solubility of methane in water (lab testing), and inherent sampling difficulties associated with depressurization and thermal changes during core extraction. This situation has prompted more decisive developments in numerical modeling in order to advance the current understanding of hydrate bearing sediments, and to investigate/optimize production strategies and implications. The goals of this research has been to addresses the complex thermo-hydro-chemo-mechanical THCM coupled phenomena in hydrate-bearing sediments, using a truly coupled numerical model that incorporates sound and proven constitutive relations, satisfies fundamental conservation principles. Analytical solutions aimed at verifying the proposed code have been proposed as well. These tools will allow to better analyze available data and to further enhance the current understanding of hydrate bearing sediments in view of future field experiments and the development of production technology.

58 GEOSCIENCES↗

In situ grain fracture mechanics during uniaxial compaction of granular solids

Grain fracture and crushing are known to influence the macroscopic mechanical behavior of granular materials and be influenced by factors such as grain composition, morphology, and microstructure. In this paper, we investigate grain fracture and crushing by combining synchrotron x-ray computed tomography and three-dimensional x-ray diffraction to study two granular samples undergoing uniaxial compaction. Our measurements provide details of grain kinematics, contacts, average intra-granular stresses, inter-particle forces, and intra-grain crystal and fracture plane orientations. Our analyses elucidate the complex nature of fracture and crushing, showing that: (1) the average stress states of grains prior to fracture vary widely in their relation to global and local trends; (2) fractured grains experience inter-particle forces and stored energies that are statistically higher than intact grains prior to fracture; (3) fracture plane orientations are primarily controlled by average intra-granular stress and contact fabric rather than the orientation of the crystal lattice; (4) the creation of new surfaces during fracture accounts for a very small portion of the energy dissipated during compaction; (5) mixing brittle and ductile grain materials alters the grain-scale fracture response. The results highlight an application of combined x-ray measurements for non-destructive in situ analysis of granular solids and provide details about grain fracture that have important implications for theory and modeling.

42 ENGINEERING↗

Computational Power of Random Quantum Circuits in Arbitrary Geometries

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025

DeCross, M.↗

Development of Methods for In-line Monitoring of Yield Stress During the Transfer of Radioactive Waste - 20435

Radioactive waste slurries at the Savannah River Site (SRS) and Hanford often behave as non-Newtonian fluids with a yield stress. The yield stress increases the size of equipment needed to transport or mix these slurries and can increase the risk of process upsets. This property is often measured by collection of samples and transportation to a laboratory, which can increase the risk of personnel exposure and even change the rheology. In addition, slurry rheology has been observed to change with time. Real-time in-line monitoring (RTIM) of rheological properties of slurries can have substantial benefits to critical processes which are currently in operation or will be part of future plans in Department of Energy (DOE) complex processes. The need for an appropriate RTIM technology that can potentially minimize or eliminate numerous sampling operations was recently identified. This research at Florida International University focuses on addressing the need for a reliable RTIM technology at US Department of Energy sites. The objective of this work is to investigate and develop appropriate and reliable technologies that can perform accurate and easy measurements of yield stress with minimal changes to the flow conditions at US Department of Energy sites. Use of ultrasound in longitudinal and shear modes was considered as a method for monitoring of yield stress variations with no disturbance to the flow. Measurement of shear wave velocity (in shear mode) and monitoring of sound velocity variations with start of flow from rest (longitudinal mode) are the underlying principles. Measurement of pressure loss and liquid rise (due to static differential pressure) during flow of slurries were two other methods that were considered and investigated. In addition, analysis of stability depth of a penetrometer in slurry medium (penetrometer method) revealed a potential suitability. This paper presents efforts associated with investigation of different methods mentioned earlier for kaolin-water mixtures at different concentrations. Theoretical analysis showed that all methods under investigation were capable of monitoring yield stress in a desirable range of 0 to 70 pascal. A bench scale test setup was constructed for investigation of pressure loss and liquid rise methods. Simulants at different concentrations were created for initial testing campaigns. For ultrasonic testing, effects of yield stress on sound propagation speed in longitudinal and shear modes were investigated for simulants placed inside PVC pipes. Parameters such as simulant concentration and pipe diameter were varied to find optimal values. It was found that spacing (or medium thickness) of 1/8 inch or less was necessary to observe echoes with sufficient strength. In addition, a significant effect of yield stress on sound propagation velocity was observed. For the liquid rise method, kaolin-water simulant at 1.17 specific gravity was pumped through a 1/4 inch pipe and liquid height was measured in a vertical riser branching off a three-way connection. Static gauge pressure was varied within [0.3 to 1.1] psi range by increase of pumping pressure and flow. Results showed consistent yield stress data within 10% deviation from values reported by a rheometer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

SNaPP: Simplified Nanoproteomics Platform for Reproducible Global Proteomic Analysis of Nanogram Protein Quantities

Global proteomic analyses are now widely applied across biological research to study changes in an organism(s) proteome correlated with a perturbation, phenotype and/or time series of interest.[1-3] Further, it has been broadly established that efficient and reproducible sample preparation workflows are crucial to successful quantitative proteome comparisons, especially when applying label free methods.[4-8] However, clinical samples are often severely limited in quantity and can preclude the application of more robust bulk sample processing workflows due to e.g. contamination, carry-over, or sample losses.[9] This has limited the effective application of global proteomics for many sample types of great interest, e.g. LCM dissected tissues, FACS sorted cells, circulating tumor cells (CTC), and early embryos. In a typical proteomics experiment, bulk homogenization is applied to generate sufficient protein for processing (> 10 µg protein), and can blend the proteomes of many different cell types and disparate tissue regions. The resulting “average” proteome, can effectively render unobservable proteome changes of interest, and preclude important applications. Global proteomic analyses of complex protein samples in nanogram quantities require a fastidious approach to achieve in-depth protein coverage and quantitative reproducibility.

automation↗

Measuring the Error in Approximating the Sub-Level Set Topology of Sampled Scalar Data

This paper studies here the influence of the definition of neighborhoods and methods used for creating point connectivity on topological analysis of scalar functions. It is assumed that a scalar function is known only at a finite set of points with associated function values. In order to utilize topological approaches to analyze the scalar-valued point set, it is necessary to choose point neighborhoods and, usually, point connectivity to meaningfully determine critical-point behavior for the point set. Two distances are used to measure the difference in topology when different point neighborhoods and means to define connectivity are used: (i) the bottleneck distance for persistence diagrams and (ii) the distance between merge trees. Usually, these distances define how different scalar functions are with respect to their topology. These measures, when properly adapted to point sets coupled with a definition of neighborhood and connectivity, make it possible to understand how topological characteristics depend on connectivity. Noise is another aspect considered. Five types of neighborhoods and connectivity are discussed: (i) the Delaunay triangulation; (ii) the relative neighborhood graph; (iii) the Gabriel graph; (iv) the k-nearest-neighbor (KNN) neighborhood; and (v) the Vietoris–Rips complex. It is discussed in detail how topological characterizations depend on the chosen connectivity.

97 MATHEMATICS AND COMPUTING↗

Intrepid MCMC: Metropolis-Hastings with exploration

In engineering examples, one often encounters the need to sample from unnormalized distributions with complex shapes that may also be implicitly defined through a physical or numerical simulation model, making it computationally expensive to evaluate the associated density function. For such cases, MCMC has proven to be an invaluable tool. Random-walk Metropolis Methods (also known as Metropolis-Hastings (MH)), in particular, are highly popular for their simplicity, flexibility, and ease of implementation. However, most MH algorithms suffer from significant limitations when attempting to sample from distributions with multiple modes (particularly disconnected ones). Here, in this paper, we present Intrepid MCMC - a novel MH scheme that utilizes a simple coordinate transformation to significantly improve the mode-finding ability and convergence rate to the target distribution of random-walk Markov chains while retaining most of the simplicity of the vanilla MH paradigm. Through multiple examples, we showcase the improvement in the performance of Intrepid MCMC over vanilla MH for a wide variety of target distribution shapes. We also provide an analysis of the mixing behavior of the Intrepid Markov chain, as well as the efficiency of our algorithm for increasing dimensions. A thorough discussion is presented on the practical implementation of the Intrepid MCMC algorithm. Finally, its utility is highlighted through a Bayesian parameter inference problem for a two-degree-of-freedom oscillator under free vibration.

97 - MATHEMATICS AND COMPUTING↗

NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts

In this work, we present NENCI-2021, a benchmark database of ~8000 Non-Equilibirum Non-Covalent Interaction energies for a large and diverse selection of intermolecular complexes of biological and chemical relevance. To meet the growing demand for large and high-quality quantum mechanical data in the chemical sciences, NENCI-2021 starts with the 101 molecular dimers in the widely used S66 and S101 databases and extends the scope of these works by (i) including 40 cation–π and anion–π complexes, a fundamentally important class of non-covalent interactions that are found throughout nature and pose a substantial challenge to theory, and (ii) systematically sampling all 141 intermolecular potential energy surfaces (PESs) by simultaneously varying the intermolecular distance and intermolecular angle in each dimer. Designed with an emphasis on close contacts, the complexes in NENCI-2021 were generated by sampling seven intermolecular distances along each PES (ranging from 0.7× to 1.1× the equilibrium separation) and nine intermolecular angles per distance (five for each ion–π complex), yielding an extensive database of 7763 benchmark intermolecular interaction energies (E int ) obtained at the coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory. The E int values in NENCI-2021 span a total of 225.3 kcal/mol, ranging from -38.5 to +186.8 kcal/mol, with a mean (median) E int value of -1.06 kcal/mol (-2.39 kcal/mol). In addition, a wide range of intermolecular atom-pair distances are also present in NENCI-2021, where close intermolecular contacts involving atoms that are located within the so-called van der Waals envelope are prevalent—these interactions, in particular, pose an enormous challenge for molecular modeling and are observed in many important chemical and biological systems. A detailed symmetry-adapted perturbation theory (SAPT)- based energy decomposition analysis also confirms the diverse and comprehensive nature of the intermolecular binding motifs present in NENCI-2021, which now includes a significant number of primarily induction-bound dimers (e.g., cation–π complexes). NENCI-2021 thus spans all regions of the SAPT ternary diagram, thereby warranting a new four-category classification scheme that includes complexes primarily bound by electrostatics (3499), induction (700), dispersion (1372), or mixtures thereof (2192). A critical error analysis performed on a representative set of intermolecular complexes in NENCI-2021 demonstrates that the E int values provided herein have an average error of ±0.1 kcal/mol, even for complexes with strongly repulsive E int values, and maximum errors of ±0.2–0.3 kcal/mol (i.e., ~±1.0 kJ/mol) for the most challenging cases. For these reasons, we expect that NENCI-2021 will play an important role in the testing, training, and development of next-generation classical and polarizable force fields, density functional theory approximations, wavefunction theory methods, and machine learning based intra- and inter-molecular potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis

Abstract Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of atomic configurations. To address this challenge, we present Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that accounts for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt 3 Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combined with low symmetry of the alloy substrate produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to the Oxygen Reduction Reaction, where configurational complexity results from the presence of irregular crystal surfaces, high adsorbate coverages, and directionally-dependent adsorbate-adsorbate interactions. In both cases, the ACE-GCN model, trained on a fraction (~10%) of the total DFT-relaxed configurations, successfully describes trends in the relative stabilities of unrelaxed atomic configurations sampled from a large configurational space. This approach is expected to accelerate development of rigorous descriptions of catalyst surfaces under in-situ conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient loading of reduced data ensembles produced at ORNL SNS/HFIR neutron time-of-flight facilities

We present algorithmic improvements to the loading operations of certain reduced data ensembles produced from neutron scattering experiments at Oak Ridge National Laboratory (ORNL) facilities. Ensembles from multiple measurements are required to cover a wide range of the phase space of a sample material of interest. They are stored using the standard NeXus schema on individual HDF5 files. This makes it a scalability challenge, as the number of experiments stored increases in a single ensemble file. The present work follows up on our previous efforts on data management algorithms, to address identified input output (I/O) bottlenecks in Mantid, an open-source data analysis framework used across several neutron science facilities around the world. We reuse an in-memory binary-tree metadata index that resembles data access patterns, to provide a scalable search and extraction mechanism. In addition, several memory operations are refactored and optimized for the current common use cases, ranging most frequently from 10 to 180, and up to 360 separate measurement configurations. Results from this work show consistent speed ups in wall-clock time on the Mantid LoadMD routine, ranging from 19% to 23% on average, on ORNL production computing systems. The latter depends on the complexity of the targeted instrument-specific data and the system I/O and compute variability for the shared computational resources available to users of ORNL’s Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) instruments. Nevertheless, we continue to highlight the need for more research to address reduction challenges as experimental data volumes, user time and processing costs increase.

Godoy, William↗

Study of the specific features of single-crystal boron microstructure

A complex study of the structure of β-boron single crystal grown by the floating-zone method, with sizes significantly exceeding the analogs known in the literature, has been performed. The study includes X-ray diffraction analysis and X-ray diffractometry (measurement of pole figures and rocking curves), performed on both laboratory and synchrotron sources; atomic-resolution scanning transmission electron microscopy with spherical aberration correction; and energy-dispersive microanalysis. X-ray diffraction analysis using synchrotron radiation has been used to refine the β-boron structure and find impurity Si atoms. The relative variations in the unit-cell parameters a and c for the crystal bulk are found to be δa/a ≈ 0.4 and δc/c ≈ 0.1%. X-ray diffractometry has revealed that the single-crystal growth axis coincides with the [22̄013] crystallographic axis and makes an angle of 21.12° with the [0001] threefold axis. Electron microscopy data have confirmed that the sample under study is a β-boron crystal, which may contain 0.3–0.4 at % Si as an impurity. Planar defects (stacking faults and dislocations) are found. The results of additional measurements of the temperature dependence of the thermal conductivity of the crystal in the range of 50–300 K are indicative of its high structural quality.

36 MATERIALS SCIENCE↗

ANALYSIS OF SAFETY IMPACTS FROM EXTERNAL FLOODING USING THE RISK-INFORMED SAFETY MARGIN CHARACTERIZATION (RISMC) TOOLKIT

The existing fleet of U.S. nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This paper demonstrates how Idaho National Laboratory (INL) researchers use the RISMC Toolkit to investigate complex nuclear plant phenomena using RAVEN and RELAP-7. The analysis focused on a highly relevant topic currently facing some nuclear power plants – specifically flooding issues. This research and development looked at challenges to a hypothetical pressurized water reactor, including: (1) a potential loss of off-site power followed by the possible loss of all diesel generators (i.e., a station black-out event), (2) earthquake induced station-blackout, and (3) a potential earthquake induced tsunami flood. The analysis is performed by using a set of codes: a thermal-hydraulic code (RELAP-7), a flooding simulation tool (NEUTRINO) and a stochastic analysis tool (RAVEN) – these are currently under development at INL. Using RAVEN, we were able to perform multiple RELAP-7 simulation runs by changing specific parts of the model in order to reflect specific aspects of different scenarios, including both the failure and recovery of critical components. The simulation employed traditional statistical tools (such as Monte-Carlo sampling) and more advanced machine-learning based algorithms to perform uncertainty quantification in order to understand changes in system performance and limitations as a consequence of power uprate. Qualitative and quantitative results obtained gave a detailed picture of the issues associated with potential accident scenarios. These types of insights can provide useful material for decision makers to perform risk-informed margins management.

97 MATHEMATICS AND COMPUTING↗

A simple novel device for air sampling by electrokinetic capture

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.

47 OTHER INSTRUMENTATION↗

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

2025 ASMS Investigation of the Collision-Induced Dissociation Mechanism of Protonated TODGA with IRIS

Title (20 words): Investigation of the Collision-Induced Dissociation Mechanism of Protonated TODGA with IRIS Introduction (120 words): One of the challenges facing wide-spread adoption of nuclear power is the development of efficient separation processes for used nuclear fuel. The molecules in separation processes are subjected to an extreme environment due to the high radiation fields from the used fuel and highly acidic media used for fuel dissolution, which results in significant molecular degradation, leading to reduced process efficiency. These degradation products must be identified and studied so mitigation strategies can be developed to maintain process efficiency. However, complex systems can have many degradation products, complicating identification. Untargeted analysis tools could be used to understand radiation chemistry in complex systems. However, this would necessitate improved understanding of the gas-phase fragmentation mechanisms of fuel cycle molecules like tetraoctyldiglycolamide (TODGA). Methods (120 words): The gas-phase fragmentation of protonated TODGA was investigated using collision-induced dissociation (CID), resonance ejection, and infrared ion spectroscopy (IRIS). CID and resonance ejection experiments were conducted using a Bruker Daltonics (Bremen, Gemany) SolariX XR fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer. IRIS spectra of protonated TODGA and its two CID fragmentation products were measured using a modified Bruker amaZon Speed ETD 3D quadrupole ion trap mass spectrometer coupled to the Free Electron Lasers for Infrared eXperiments (FELIX) free electron laser. Measured spectra were compared with density functional theory (DFT) calculations using the Gaussian 16, Revision C.02 software package with the ?B97X-D functional and def2-TZVPP basis sets. Candidate structures were generated using the CREST 3.0 conformational sampling software tool. Preliminary Data (300 words): Collision-induced dissociation of protonated TODGA ([C36H73N2O3]+, m/z=581.562) results two fragment ions, one at m/z=340.285 assigned as [C20H38NO3]+ and the other at m/z=312.290, assigned as [C19H38NO2]+. Based on the assigned formula and the structure of protonated TODGA, the fragment at m/z=340.285 is likely formed from elimination of neutral dioctylamine. Comparison of the IRIS spectrum of m/z=340.285 with DFT predictions suggests it contains a ring structure, and is assigned as N-octyl-N-(6-oxo-1,4-dioxan-2-ylidene)octan-1-aminium. Based on this structure and the structure of protonated TODGA, we hypothesize this fragment formed from elimination of neutral dioctylamine followed by a ring closure mechanism. Comparison of the IRIS spectrum of the fragment at m/z=312.290 with DFT predictions also indicated the presence of a ring structure, assigned as N-(1,3-dioxolan-4-ylidene)-N-octyloctan-1-aminium. This product could be formed from elimination of carbon monoxide from the ring of m/z=340.285 as a sequential fragmentation or formed directly from protonated TODGA via elimination of neutral N,N-dioctylformamide followed by a ring closure. Resonance ejection experiments where m/z=340 was continuously ejected from the IRC cell showed no decrease in intensity of m/z=312.290 across several collision energies, suggesting that the later, direct formation mechanism, dominates. The location of the ionizing proton in protonated TODGA is important for modeling the fragmentation mechanisms. DFT calculations suggested that the position of bands involving the coupled vibrations of the amide C—N and C=O bonds in TODGA are the most sensitive to proton location. Evaluation of the IRIS spectrum of protonated TODGA suggests that the ionizing proton is located between the two amid oxygens. This protonation location was calculated to lie approximately 30 kJ/mol lower in energy than the next lowest energy location, with the proton located solely on one of the amide oxygens. Novel aspect (20 words): Infrared ion spectroscopy combined with resonance ejection experiments and density functional theory to probe the collision-induced dissociation mechanism of tetraoctyldiglycolamide.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Determining the Effect of Catechins on SOD1 Conformation and Aggregation by Ion Mobility Mass Spectrometry Combined with Optical Spectroscopy

The aggregation of Cu,Zn-superoxide dismutase (SOD1) plays an important role in the etiology of amyotrophic lateral sclerosis (ALS). For the disruption of ALS progression, discovering new drugs or compounds that can prevent SOD1 aggregation is important. In this study, ESI-MS was used to investigate the interaction of catechins and SOD1. The noncovalent complex of catechins that interact with SOD1 was found and retained in the gas phase under native ESI-MS condition. The conformation changes of SOD1 after binding with catechins were also explored via traveling wave ion mobility (IM) spectrometry. Epigallocatechin gallate (EGCG) can stabilize SOD1 conformation against unfolding in three catechins. To further evaluate the efficacy of EGCG, we monitored the fluorescence changes of dimer E{sub 2},E{sub 2},-SOD1(apo-SOD1, E:empty) with and without ligands under denaturation conditions, and found that EGCG can inhibit apo-SOD1 aggregation. In addition, the circular dichroism spectra of the samples showed that EGCG can decrease the β-sheet content of SOD1, which can produce aggregates. These results indicated that orthogonal separation dimension in the gas-phase IM coupled with ESI-MS (ESI-IM-MS) can potentially provide insight into the interaction between SOD1 and small molecules. The advantage is that it dramatically decreases the analysis time. Meantime, optical spectroscopy techniques can be used to confirm ESI-IM-MS results. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗