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Massively parallel implementations of coupled-cluster methods for electron spin resonance spectra. I. Isotropic hyperfine coupling tensors in large radicals

Coupled cluster (CC) methods provide highly accurate predictions of molecular properties, but their high computational cost has precluded their routine application to large systems. Fortunately, recent computational developments in the ACES III program by the Bartlett group [the OED/ERD atomic integral package, the super instruction processor, and the super instruction architecture language] permit overcoming that limitation by providing a framework for massively parallel CC implementations. In that scheme, we are further extending those parallel CC efforts to systematically predict the three main electron spin resonance (ESR) tensors (A-, g-, and D-tensors) to be reported in a series of papers. In this paper inaugurating that series, we report our new ACES III parallel capabilities that calculate isotropic hyperfine coupling constants in 38 neutral, cationic, and anionic radicals that include the {sup 11}B, {sup 17}O, {sup 9}Be, {sup 19}F, {sup 1}H, {sup 13}C, {sup 35}Cl, {sup 33}S,{sup 14}N, {sup 31}P, and {sup 67}Zn nuclei. Present parallel calculations are conducted at the Hartree-Fock (HF), second-order many-body perturbation theory [MBPT(2)], CC singles and doubles (CCSD), and CCSD with perturbative triples [CCSD(T)] levels using Roos augmented double- and triple-zeta atomic natural orbitals basis sets. HF results consistently overestimate isotropic hyperfine coupling constants. However, inclusion of electron correlation effects in the simplest way via MBPT(2) provides significant improvements in the predictions, but not without occasional failures. In contrast, CCSD results are consistently in very good agreement with experimental results. Inclusion of perturbative triples to CCSD via CCSD(T) leads to small improvements in the predictions, which might not compensate for the extra computational effort at a non-iterative N{sup 7}-scaling in CCSD(T). The importance of these accurate computations of isotropic hyperfine coupling constants to elucidate experimental ESR spectra, to interpret spin-density distributions, and to characterize and identify radical species is illustrated with our results from large organic radicals. Those include species relevant for organic chemistry, petroleum industry, and biochemistry, such as the cyclo-hexyl, 1-adamatyl, and Zn-porphycene anion radicals, inter alia.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE-Managed HLW and SNF Research: FY15 EBS and Thermal Analysis Work Package Status.

This report examines the technical elements necessary to evaluate EBS concepts and perform thermal analysis of DOE-Managed SNF and HLW in the disposal settings of primary interest – argillite, crystalline, salt, and deep borehole. As the disposal design concept is composed of waste inventory, geologic setting, and engineered concept of operation, the engineered barrier system (EBS) falls into the last component of engineered concept of operation. The waste inventory for DOE-Managed HLW and SNF is closely examined, with specific attention to the number of waste packages, the size of waste packages, and the thermal output per package. As expected, the DOE-Managed HLW and SNF inventory has a much smaller volume, and hence smaller number of canisters, as well a lower thermal output, relative to a waste inventory that would include commercial spent nuclear fuel (CSNF). A survey of available data and methods from previous studies of thermal analysis indicates that, in some cases, thermo-hydrologic modeling will be necessary to appropriately address the problem. This report also outlines scope for FY16 work -- a key challenge identified is developing a methodology to effectively and efficiently evaluate EBS performance in each disposal setting on the basis of thermal analyses results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A theoretical investigation of the hydrolysis of uranium hexafluoride: the initiation mechanism and vibrational spectroscopy

Depleted uranium hexafluoride (UF 6 ), a stockpiled byproduct of the nuclear fuel cycle, reacts readily with atmospheric humidity, but the mechanism is poorly understood. Here we compare several potential initiation steps at a consistent level of theory, generating underlying structures and vibrational modes using hybrid density functional theory (DFT) and computing relative energies of stationary points with double-hybrid (DH) DFT. A benchmark comparison is performed to assess the quality of DH-DFT data using reference energy differences obtained using a complete-basis-limit coupled-cluster (CC) composite method. The associated large-basis CC computations were enabled by a new general-purpose pseudopotential capability implemented as part of this work. Dispersion-corrected parameter-free DH-DFT methods, namely PBE0-DH-D3(BJ) and PBE-QIDH-D3(BJ), provided mean unsigned errors within chemical accuracy (1 kcal mol -1 ) for a set of barrier heights corresponding to the most energetically favorable initiation steps. The hydrolysis mechanism is found to proceed via intermolecular hydrogen transfer within van der Waals complexes involving UF 6 , UF 5 OH, and UOF 4 , in agreement with previous studies, followed by the formation of a previously unappreciated dihydroxide intermediate, UF 4 (OH) 2 . The dihydroxide is predicted to form under both kinetic and thermodynamic control, and, unlike the alternate pathway leading to the UO 2 F 2 monomer, its reaction energy is exothermic, in agreement with observation. Finally, harmonic and anharmonic vibrational simulations are performed to reinterpret literature infrared spectroscopy in light of this newly identified species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multivariate analysis: An essential for studying complex glasses

Understanding the impact of individual compositional components on the devitrification of complex multicomponent glasses, for example, 10–50+ oxides, typically requires numerous studies to examine each component's impact. Here we apply exploratory data analysis (EDA) to a heterogeneous data set of silicate glasses to determine the cations’ individual and interacting effects on the crystallization of nepheline (nominally NaAlSiO 4 ). Our data consisted of 795 simulated high-level nuclear waste glasses composed of, on average, 50 oxide components. We determine the interactions in the heterogeneous data that cause deviations from the behavior found in simplified composition studies. Using both univariate and bivariate EDA techniques, we demonstrate the importance of including calculated structural glass parameters on nepheline's devitrification, including field strength, cation-to-anion radius ratio, and single-bond strength. Here, we also show that studies with simplified glass compositions may fall short in generating knowledge directly transferrable to complex glass compositions. The method used in this study has the potential to inform experimental design for simplified compositions (~6+ oxides) that can generate knowledge directly transferrable to complex, multivariable compositions. The observations reported here have broad implications for any study attempting to map the physical properties of a complex glass containing numerous cations.

36 MATERIALS SCIENCE↗

Local patient dose diagnostic reference levels in pediatric interventional cardiology in Chile using age bands and patient weight values

Purpose: To present the results of a patient dose evaluation program in pediatric cardiology and propose local diagnostic reference levels (DRLs) for different types of procedure and age range, in addition to suggesting approaches to correlate patient dose values with patient weight. This study was the first conducted in Latin America for pediatric interventional cardiology under the auspices of the International Atomic Energy Agency. Methods: Over three years, the following data regarding demographic and patient dose values were collected: age, gender, weight, height, number of cine series, total number of cine frames, fluoroscopy time (FT), and two dosimetric quantities, dose-area product (DAP) and cumulative dose (CD), at the patient entrance reference point. The third quartile values for FT, DAP, CD, number of cine series, and the DAP/body weight ratio were proposed as the set of quantities to use as local DRLs. Results: Five hundred and seventeen patients were divided into four age groups. Sample sizes by age group were 120 for <1 yr; 213 for 1 to <5 yr; 82 for 5 to <10 yr; and 102 for 10 to <16 yr. The third quartile values obtained for DAP by diagnostic and therapeutic procedures and age range were 1.17 and 1.11 Gy cm{sup 2} for <1 yr; 1.74 and 1.90 Gy cm{sup 2} for 1 to <5 yr; 2.83 and 3.22 Gy cm{sup 2} for 5 to <10 yr; and 7.34 and 8.68 Gy cm{sup 2} for 10 to <16 yr, respectively. The third quartile value obtained for the DAP/body weight ratio for the full sample of procedures was 0.17 (Gy cm{sup 2}/kg) for diagnostic and therapeutic procedures. Conclusions: The data presented in this paper are an initial attempt at establishing local DRLs in pediatric interventional cardiology, from a large sample of procedures for the standard age bands used in Europe, complemented with the values of the ratio between DAP and patient weight. This permits a rough estimate of DRLs for different patient weights and the refining of these values for the age bands when there may be large differences in child size. These DRLs were obtained at the largest pediatric hospital in Chile, with an active optimization program, and could be used by other hospitals in the Latin America region to compare their current patient dose values and determine whether corrective action is appropriate.

60 APPLIED LIFE SCIENCES↗

Soil and Water Chemistry and Trace Metal Extractability and Speciation in Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Dataset revised on October 15, 2021. This revision adds sulfur and iron X-ray absorption near-edge structure spectra for the wetland soils and stream sediments from the field areas. It also renames the sample locations in a way that is more intuitive to readers of the companion paper that is under review. Finally, the data filenames and organization have been updated in their labeling to parallel the data sources in the associated paper. The abstract text and methods were also revised to reflect the data that was added to the dataset.Trace metals are essential for microbially-mediated biogeochemical processes occurring in anoxic wetland soils and stream bed sediments, such as denitrification, methanogenesis, and mercury methylation. Low availability of these elements may potentially inhibit key components of anaerobic carbon and nitrogen cycling and contaminant transformation. The solid-phase speciation of trace metals likely plays an important role in controlling their bioavailability. Metal speciation is well studied in contaminated soils and sediments as well as those naturally elevated in trace metals. However, less is known regarding the chemical forms of trace metals in systems having concentrations similar to geological background levels, the very settings where metal limitations may be most prevalent. We have investigated trace metal concentrations, extractability, and solid-phase speciation in three freshwater subsurface aquatic systems: marsh wetland soils, riparian wetland soils, and the sediments of a streambed.Data are provided for marsh wetland soils at Argonne National Laboratory, riparian wetland soils in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments from East Fork Poplar Creek near Oak Ridge National Laboratory. Soil and sediment elemental abundances, mineralogy, and extractable nutrients as well as dissolved major elements, anions, trace metals, and nutrients in the overlying surface waters are provided. In addition, the results of sequential chemical extraction for the trace metals cobalt, nickel, copper, and zinc from the soils and sediment are reported as well as X-ray absorption near-edge structure (XANES) spectra in these materials are reported. To aid interpretation of these data, XANES spectra of sulfur in the soils and sediments as well as both XANES and extended X-ray absorption fine structure (EXAFS) spectra of iron in these materials are reported. The data package also includes the XANES spectra of reference standards and a potential interferent in the measurements. All data are provided in text-based CSV format with header sections indicating the data contained in each file and the corresponding units. Note that "u" is used in place of Greek lower case mu to indicate the micro prefix on units.

54 ENVIRONMENTAL SCIENCES↗

Personalized, disease-stage specific, rapid identification of immunosuppression in sepsis

Introduction Data overlapping of different biological conditions prevents personalized medical decision-making. For example, when the neutrophil percentages of surviving septic patients overlap with those of non-survivors, no individualized assessment is possible. To ameliorate this problem, an immunological method was explored in the context of sepsis. Methods Blood leukocyte counts and relative percentages as well as the serum concentration of several proteins were investigated with 4072 longitudinal samples collected from 331 hospitalized patients classified as septic (n=286), non-septic (n=43), or not assigned (n=2). Two methodological approaches were evaluated: (i) a reductionist alternative, which analyzed variables in isolation; and (ii) a non-reductionist version, which examined interactions among six (leukocyte-, bacterial-, temporal-, personalized-, population-, and outcome-related) dimensions. Results The reductionist approach did not distinguish outcomes: the leukocyte and serum protein data of survivors and non-survivors overlapped. In contrast, the non-reductionist alternative differentiated several data groups, of which at least one was only composed of survivors (a finding observable since hospitalization day 1). Hence, the non-reductionist approach promoted personalized medical practices: every patient classified within a subset associated with 100% survival subset was likely to survive. The non-reductionist method also revealed five inflammatory or disease-related stages (provisionally named ‘early inflammation, early immunocompetence, intermediary immuno-suppression, late immuno-suppression, or other’). Mortality data validated these labels: both ‘suppression’ subsets revealed 100% mortality, the ‘immunocompetence’ group exhibited 100% survival, while the remaining sets reported two-digit mortality percentages. While the ‘intermediary’ suppression expressed an impaired monocyte-related function, the ‘late’ suppression displayed renal-related dysfunctions, as indicated by high concentrations of urea and creatinine. Discussion The data-driven differentiation of five data groups may foster early and non-overlapping biomedical decision-making, both upon admission and throughout their hospitalization. This approach could evaluate therapies, at personalized level, earlier. To ascertain repeatability and investigate the dynamics of the ‘other’ group, additional studies are recommended.

Immunology↗

Investigating Low Temperature Properties of Rubber Seals - 13020

To achieve the required tightness levels of containers for low and intermediate level radioactive wastes rubbers are widely applied as main sealing materials. The save encapsulation of the radioactive container contents has to be guaranteed according to legislation and appropriate guidelines for long storage periods as well as down to temperatures of -40 deg. C during transportation. Therefore the understanding of failure mechanisms that lead to leakage at low temperatures is of high importance. It is known that the material properties of rubbers are strongly influenced by temperature. At low temperatures this is caused by the rubber-glass transition (abbr. glass transition). During continuous cooling the material changes from rubber-like entropy-elastic to stiff energy-elastic behaviour, that allows nearly no strain or retraction. Therefore, rubbers are normally used above their glass transition but the minimum working temperature limit is not defined precisely, what can cause problems during application. The temperature range where full functionality is possible is strongly dependent on the application conditions and the material. For this investigation mainly ethylene propylene diene (EPDM) and fluorocarbon rubbers (FKM) were selected as they are often used for radioactive waste containers. Differential Scanning Calorimetry (DSC) and Dynamic Mechanical Analysis (DMA) are typically used for the determination of the temperature range of the glass transition process. The standardized compression set measurement according to ISO 815 is common for investigation of rubber sealing materials as the test simulates the seal behaviour after release. To reduce the test time of the standard tests a faster technique giving the same information was developed. Additionally, the breakdown temperature of the sealing function of complete O-ring seals is measured in a component test setup to compare it with the results of the other tests. The experimental setup is capable of measuring the leakage rate at low temperatures by the pressure rise method. A model was developed that allows calculating the minimum working temperature limit of a seal by combining the results of the applied methods. (authors)

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Concentrations of arsenic and lead in residential garden soil from four Johannesburg neighborhoods

The 2017 Lancet Commission on Pollution and Health identified soil as an important, daily route of public exposure to a variety of pollutants. Lead and arsenic are two potential soil contaminants associated with serious health effects including reductions in intelligence, behavioral effects and aggressive or violent behavior (lead), as well as skin changes, cancer of the skin, bladder, liver and lungs and developmental delays (arsenic). In this study soil samples were collected, using US EPA methods, from gardens in four Johannesburg neighborhoods, and analyzed for lead and arsenic content using a portable X-ray fluorescence spectrometer. The results showed widely varied concentrations of arsenic and lead in soil collected across the four neighborhoods. Concentrations of lead (range: 0.1–2141.0 mg/kg; mean: 241.7 mg/kg (SD 282.8); median 158.1 mg/kg) exceeding local and international reference levels were found in an inner city suburb, while raised arsenic concentrations (range: 0.1–65.3 mg/kg; mean: 18.3 mg/kg (SD 11.7); median: 19.1) were found in the gardens of a suburb located very close to a mine tailings facility. This study confirms the potential for high levels of exposure to toxic metals in residential gardens in an urban African setting. There is a pressing need for scaled up attention to the public health implications of exposure to soil pollution in developing countries.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The diversity of aluminum-based drinking water treatment residuals for use in environmental remediation

Drinking water treatment residuals (DWTRs) are complex mixtures of organic and inorganic phases generally disposed of as waste materials. However, their strong sorptive properties could be further exploited to immobilize contaminants. To characterize these materials, we applied a range of analytical techniques to a set of aluminum-based DWTRs. Here we determined surface areas, elemental compositions using CHNS analysis and X-ray fluorescence (XRF), performed thermogravimetric analyses paired with mass spectrometry (TGA-MS), and used synchrotron-based methods: X-ray diffraction (XRD) and X-ray absorption spectroscopy (XAS). Elemental analyses and specific surface area measurements – that vary between 7.23 ± 0.03 and 197.6 ± 0.9 m 2 g –1 – indicate that non-coagulant additives must play an important role in controlling sorption. High resolution powder XRD reveals the presence of only a few crystalline minerals mostly derived from source waters or additives. Fe was detected by XRF in all samples, whereas Mn was present in significant levels in samples with potassium permanganate as additive. The chemical speciation of these elements was characterized by performing spectral decompositions of XAS spectra. The spectral features of Fe are consistent with iron(III) oxides/hydroxides and structural iron in clays. On the other hand, Mn is predominantly present under its reduced form, Mn(II).

54 ENVIRONMENTAL SCIENCES↗

Conservative algorithms for non-Maxwellian plasma kinetics

Here, we present a numerical model and a set of conservative algorithms for Non-Maxwellian plasma kinetics with inelastic collisions. These algorithms self-consistently solve for the time evolution of an isotropic electron energy distribution function interacting with an atomic state distribution function of an arbitrary number of levels through collisional excitation, deexcitation, as well as ionization and recombination. Electron-electron collisions, responsible for thermalization of the electron distribution, are also included in the model. The proposed algorithms guarantee mass/charge and energy conservation in a single step, and is applied to the case of non-uniform gridding of the energy axis in the phase space of the electron distribution function. Numerical test cases are shown to demonstrate the accuracy of the method and its conservation properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Systematic approach for simultaneously correcting the band-gap and p - d separation errors of common cation III-V or II-VI binaries in density functional theory calculations within a local density approximation

We propose a systematic approach that can empirically correct three major errors typically found in a density functional theory (DFT) calculation within the local density approximation (LDA) simultaneously for a set of common cation binary semiconductors, such as III-V compounds, (Ga or In)X with X = N,P,As,Sb, and II-VI compounds, (Zn or Cd)X, with X = O,S,Se,Te. By correcting (1) the binary band gaps at high-symmetry points , L, X, (2) the separation of p-and d-orbital-derived valence bands, and (3) conduction band effective masses to experimental values and doing so simultaneously for common cation binaries, the resulting DFT-LDA-based quasi-first-principles method can be used to predict the electronic structure of complex materials involving multiple binaries with comparable accuracy but much less computational cost than a GW level theory. This approach provides an efficient way to evaluate the electronic structures and other material properties of complex systems, much needed for material discovery and design.

Wang, Jianwei↗

Hourly gap-filled meteorological data from PIE LTER measurements (2004-2023) used as drivers to run ELM PFLOTRAN simulations

This dataset contains continuous gap-filled precipitation, solar radiation, photosynthetically active radiation (PAR), air temperature, relative humidity, wind speed, and barometric pressure data recorded primarily at the Marshview Farm weather station within the Plum Island Long Term Ecosystems Research (PIE LTER) in Newbury Massachusetts (MA) from 2004 to 2023. We compiled the data set from published annual data packages in 15min resolution available on DataOne. Gaps were filled using different statistical techniques or available observations from the vicinity, e.g. the US-PLo and the US-PHM Ameriflux sites, also located within the PIE LTER. Flags are included in this dataset to indicate the origin of each data point. Metadata files ELMPFLOTRAN_met_dd.csv and ELMPFLOTRAN_met_flmd.csv contain more information on site locations, gap filling protocols, data variables, flags, and QA/QC methods. The data set was used in the spin up and simulations of a land surface model coupled to a biogeochemical reaction network (ELM PFLOTRAN) assessing impacts of hydrology and salinity input on methane fluxes in 2022 and 2023 (Sulman et al., 2024).

54 ENVIRONMENTAL SCIENCES↗

Blockchain Enabled Intelligence of Federated Systems (BELIEFS): An attack-tolerant trustable distributed intelligence paradigm

In this article, a Blockchain Enabled Intelligence of Federated Systems (BELIEFS) is proposed to conduct cooperative control for the multi-regional large-scale power system with a multi-agents system (MAS). By establishing a two levels blockchain, each regional AI agent can simultaneously manage intra-regional controllers and cooperate with other AI agents. Under the consensus mechanism, the agents, which respectively conducted distributed deep reinforcement learning (DDRL) algorithm in multi-regions, can have the tolerant capability of malicious attacks in their training process. The demonstration of the proposed approach is within a multi-regional large-scale interconnected power system. Under the mode of "centralized dispatching and hierarchical management", this article aims to definite a mathematical model to deal with the control problem of the power systems. With the comparison experiments, the effectiveness and efficiency of our proposed method in the training process are verified. In addition, malicious attacks are set on the main chain and shard chains to verify the attack-tolerant capability. We expect that such approach and results can suggest a new paradigm of attack-tolerant trustable distributed AI deployment.

97 MATHEMATICS AND COMPUTING↗

Phosphate amendments for chemical immobilization of uranium in contaminated soil

Uranium (U) contamination is a major environmental problem associated with the mining and processing of nuclear materials for both weapons and power production. When possible, in situ soil remediation techniques are preferable for reducing the risk associated with diffuse low-level U contamination. Uranium is known to form sparingly soluble phosphate compounds that persist in the environment. Therefore, batch experiments were performed to evaluate the efficacy of three phosphate amendments, hydroxyapatite (HA), sodium phytate (IP6) and sodium tripolyphosphate (TPP), to immobilize U in contaminated sediments. The amendments were added at equivalent phosphorus (P) concentrations and then equilibrated under a range of test conditions, with changes in soluble U and Ptotal monitored at pre-set time intervals. Only HA was effective at reducing the soluble U soil fraction when compared to the control, with IP6 and TPP increasing the soluble U soil fraction. After equilibration, changes in contaminant partitioning in the amended sediments were evaluated using operational extraction methods. Sequential extraction results for HA generally indicated a transfer of U from labile to more recalcitrant phases, while the results for IP6 and TPP were more ambiguous.

Uranyl↗

Quantum-Chemically Informed Machine Learning: Prediction of Energies of Organic Molecules with 10 to 14 Non-hydrogen Atoms

High-fidelity quantum-chemical calculations can provide accurate predictions of molecular energies, but their high computational costs limit their utility, especially for larger molecules. We have shown in previous work that machine learning models trained on high-level quantum-chemical calculations (G4MP2) for organic molecules with one to nine non-hydrogen atoms can provide accurate predictions for other molecules of comparable size at much lower costs. Here we demonstrate that such models can also be used to effectively predict energies of molecules larger than those in the training set. To implement this strategy, we first established a set of 191 molecules with 10–14 non-hydrogen atoms having reliable experimental enthalpies of formation. We then assessed the accuracy of computed G4MP2 enthalpies of formation for these 191 molecules. The error in the G4MP2 results was somewhat larger than that for smaller molecules, and the reason for this increase is discussed. Two density functional methods, B3LYP and ωB97X-D, were also used on this set of molecules, with ωB97X-D found to perform better than B3LYP at predicting energies. The G4MP2 energies for the 191 molecules were then predicted using these two functionals with two machine learning methods, the FCHL-Δ and SchNet-Δ models, with the learning done on calculated energies of the one to nine non-hydrogen atom molecules. The better-performing model, FCHL-Δ, gave atomization energies of the 191 organic molecules with 10–14 non-hydrogen atoms within 0.4 kcal/mol of their G4MP2 energies. Thus, this work demonstrates that quantum-chemically informed machine learning can be used to successfully predict the energies of large organic molecules whose size is beyond that in the training set.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Groundwater and Intruder Radionuclide Screening

Solid Waste Management (SWM) operates the E-Area Low-Level Waste Facility (ELLWF) where low level on-site and off-site solid waste streams are buried. The facility has been in operation since late 1994 and is currently projected to remain in operation until 2065. This facility can accommodate a broad range of waste forms resulting from the six different types of disposal unit options (i.e., varying degrees of engineered barriers → trenches to concrete vaults). This facility is currently operating under a Performance Assessment (PA) issued back in 2008, along with several subsequent supporting Special Analyses (SA). The Savannah River National Laboratory (SRNL) developed the prior PAs and SAs and has been tasked to update the facility’s PA. For operating the E-Area facility, a Waste Inventory Tracking System (e.g., WITS) is actively employed by waste generators where every radionuclide entering the facility (to be buried in one of its many disposal units) must be either directly or indirectly accounted for. Since there is a large number of radionuclides in existence (>3,000), the International Commission on Radiological Protection (ICRP-107) has provided guidance on the subset of radionuclides requiring further assessment in landfills such as the E-Area LLWF. The ICRP-107 publication provides critical radiological information on 1,252 radionuclides of 97 elements. This database is the critical starting point for developing a consistent inventory limit system. The explicit measurement and tracking of all radionuclides are not necessary when process knowledge, burial history, and radiological aspects are factored into conservative groundwater and intruder screening processes. Across the DOE complex these screening processes have been historically performed using the methodology suggested by the National Council on Radiation Protection and Measurements (NCRP) as presented in their original report (NCRP 1984) and then refined in a later report (NCRP 1996). In the recommended screening models employed within this report the traditional NCRP models are updated to better handle progeny and better reflect the known characteristics of E-Area. This improved screening process is referred to as the “NCRP-like” method. Various upgrades to the traditional NCRP methodology have been used by others (e.g., NRC funded effort by Kennedy and Strenge 1992). The more detailed models by Kennedy and Strenge (1992) were considered in this effort and are compared to the results from the more traditional NCRP-like models. The groundwater and inadvertent intruder screening analyses presented in this report start with this 1,252 radionuclide list and reduces it down to more manageable lists that are applicable to the various disposal unit types contained within E-Area. In order to reduce this starting list, some level of exposure risk must be considered acceptable. Historically, a dose (or concentration level) has been compared with a screening criterion set to 1% of a performance measure (e.g., a beta-gamma dose not to exceed the 4 mrem/yr beta-gamma performance measure x 0.01 = 0.04 mrem/yr). Thus, if a radionuclide produced a bounding or screening-level dose (or concentrations) less than the screening criterion, it could be safely removed from further consideration. Several tiers of screening and bounding level analyses have been considered in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗