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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
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DOE OSTI2022

First near-threshold measurements of the 13 C($α, n$ 1 ) 16 O reaction for low-background-environment characterization

The modeling of background sources in large volume detection systems requires accurate nuclear cross sections for a variety of reactions. Among the most important are (α,n) on light nuclei, where α particles, up to ≈9 MeV, are produced from the decay of actinides present in trace amounts in detection and structural material. In order to model the neutron energy spectra and production of other secondary particles, the partial cross sections are needed. Yet very little experimental data exists for these partial cross sections because past measurements, hampered by the experimental challenges of neutron detection, have focused mostly on total reaction cross section measurements. Here, in this paper, the partial cross section of the 13 C(α,n 1 ) 16 O reaction is reported for the first time. The measurements were made near the reaction threshold using a high energy resolution helium spectrometer. The measurements show a rapidly increasing cross section, which quickly becomes a significant fraction of the total reaction cross section. Measurements are compared with previous theory estimates and differences of more than an order of magnitude are found. A comparison is made with new total cross section measurements and the current level of consistency is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Comparison of human poly-N-acetyl-lactosamine synthase structure with GT-A fold glycosyltransferases supports a modular assembly of catalytic subsites

Poly-N-acetyl-lactosamine (poly-LacNAc) structures are composed of repeating [-Galβ(1,4)-GlcNAcβ(1,3)-]n glycan extensions. They are found on both N- and O-glycoproteins and glycolipids and play an important role in development, immune function, and human disease. The majority of mammalian poly-LacNAc is synthesized by the alternating iterative action of β1,3-N-acetylglucosaminyltransferase 2 (B3GNT2) and β1,4-galactosyltransferases. B3GNT2 is in the largest mammalian glycosyltransferase family, GT31, but little is known about the structure, substrate recognition, or catalysis by family members. Here we report the structures of human B3GNT2 in complex with UDP:Mg 2+ and in complex with both UDP:Mg 2+ and a glycan acceptor, lacto-N-neotetraose. The B3GNT2 structure conserves the GT-A fold and the DxD motif that coordinates a Mg 2+ ion for binding the UDP-GlcNAc sugar donor. The acceptor complex shows interactions with only the terminal Galβ(1,4)-GlcNAcβ(1,3)- disaccharide unit, which likely explains the specificity for both N- and O-glycan acceptors. Modeling of the UDP-GlcNAc donor supports a direct displacement inverting catalytic mechanism. Comparative structural analysis indicates that nucleotide sugar donors for GT-A fold glycosyltransferases bind in similar positions and conformations without conserving interacting residues, even for enzymes that use the same donor substrate. In contrast, the B3GNT2 acceptor binding site is consistent with prior models suggesting that the evolution of acceptor specificity involves loops inserted into the stable GT-A fold. These observations support the hypothesis that GT-A fold glycosyltransferases employ coevolving donor, acceptor, and catalytic subsite modules as templates to achieve the complex diversity of glycan linkages in biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Copper availability governs nitrous oxide accumulation in wetland soils and stream sediments

Denitrification is microbially-mediated through enzymes containing metal cofactors. Laboratory studies of pure cultures have highlighted that the availability of Cu, required for the multicopper enzyme nitrous oxide reductase, can limit N2O reduction. However, in natural aquatic systems, such as wetlands and hyporheic zones in stream beds, the role of Cu in controlling denitrification remains incompletely understood. In this study, we collected soils and sediments from three natural environments -- riparian wetlands, marsh wetlands, and a stream -- to investigate their nitrogen species transformation activity at background Cu levels and different supplemented Cu loadings. All of the systems contained solid-phase associated Cu below or around geological levels (40 - 280 nmol g-1) and exhibited low dissolved Cu (3-50 nM), which made them appropriate sites for evaluating the effect of limited Cu availability on denitrification. In laboratory incubation experiments, high concentrations of N2O accumulated in all microcosms lacking Cu amendment except for one stream sediment sample. With Cu added to provide dissolved concentrations at trace levels (10-300 nM), reduction rate of N2O to N 2 in the wetland soils and stream sediments was enhanced. A kinetic model could account for the trends in nitrogen species by combining the reactions for microbial reduction of NO 3 - to NO 2 -/N 2 O/N 2 and abiotic reduction of NO 2 - to N 2 . The model revealed that the rate of N 2 O to N 2 conversion increased significantly in the presence of Cu. For riparian wetland soils and stream sediments, the kinetic model also suggested that overall denitrification is driven by abiotic reduction of NO2- in the presence of inorganic electron donors. This study demonstrated that natural aquatic systems containing Cu at concentrations less than or equal to crustal abundances may display incomplete reduction of N 2 O to N 2 that would cause N 2 O accumulation and release to the atmosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Nitrification is a minor source of nitrous oxide (N 2 O) in an agricultural landscape and declines with increasing management intensity

Abstract The long‐term contribution of nitrification to nitrous oxide (N 2 O) emissions from terrestrial ecosystems is poorly known and thus poorly constrained in biogeochemical models. Here, using Bayesian inference to couple 25 years of in situ N 2 O flux measurements with site‐specific Michaelis–Menten kinetics of nitrification‐derived N 2 O, we test the relative importance of nitrification‐derived N 2 O across six cropped and unmanaged ecosystems along a management intensity gradient in the U.S. Midwest. We found that the maximum potential contribution from nitrification to in situ N 2 O fluxes was 13%–17% in a conventionally fertilized annual cropping system, 27%–42% in a low‐input cover‐cropped annual cropping system, and 52%–63% in perennial systems including a late successional deciduous forest. Actual values are likely to be <10% of these values because of low N 2 O yields in cultured nitrifiers (typically 0.04%–8% of NH 3 oxidized) and competing sinks for available in situ. Most nitrification‐derived N 2 O was produced by ammonia‐oxidizing bacteria rather than archaea, who appeared responsible for no more than 30% of nitrification‐derived N 2 O production in all but one ecosystem. Although the proportion of nitrification‐derived N 2 O production was lowest in annual cropping systems, these ecosystems nevertheless produced more nitrification‐derived N 2 O (higher V max ) than perennial and successional ecosystems. We conclude that nitrification is minor relative to other sources of N 2 O in all ecosystems examined.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Global electroweak symmetric vacuum

Although the Higgs potential in the Standard Model (SM) contains only a simple electroweak symmetry breaking vacuum in the small field region, additional metastable or global vacua could exist in models beyond the SM. In this paper, we study one intriguing scenario with an additional electroweak symmetric vacuum that could be the global one. For the thermal universe ending at the current metastable vacuum, the electroweak symmetry should stay non-restored at high temperatures. We realize the scenario in a model with Higgs-portal couplings to SM singlet scalars with approximately global O(N) symmetries with a large N. For a large portion of model parameter space, both the quantum and thermal tunneling rates are suppressed such that our current metastable vacuum is long-lived enough. Our scenario predicts order-one changes for the Higgs self-couplings and a large contribution to the signal of the off-shell Higgs invisible decay. It can be partly probed at the LHC Run 3 and well tested at the high luminosity LHC. We also discuss the subcritical (anti-de Sitter) bubbles from the thermal tunneling that could have a large population and interesting cosmological implications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

First direct measurement of the 13 $\mathrm{N(α, ρ)}$ 16 $\mathrm{O}$ reaction relevant for core-collapse supernovae nucleosynthesis

We report that understanding the explosion mechanism of a core-collapse supernova (CCSN) is important to accurately model CCSN scenarios for different progenitor stars using model-observation comparisons. The uncertainties of various nuclear reaction rates relevant for CCSN scenarios strongly affect the accuracy of these stellar models. Out of these reactions, the 13 N(α, p) 16 O reaction has been found to affect various stages of a CCSN at varying temperatures. This work presents the first direct measurement of the 13 N(α, p) 16 O reaction performed using a 34.6 MeV beam of radioactive 13 N ions and the active-target detector MUSIC (MUlti-Sampling Ionization Chamber) at Argonne National Laboratory. The resulting total 13 N(α, p) 16 O reaction cross sections from this measurement in the center-of-mass energy range of 3.26 - 6.02 MeV are presented and compared with calculations using the Hauser-Feshbach formalism. Uncertainties in the reaction rate have been dramatically reduced at CCSN temperatures.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N<sub>2</sub>O emission using data from mesocosm experiments

Abstract. Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human activities. Existing approaches such as process-based (PB) models have well-known limitations due to insufficient representations of the processes or uncertainties of model parameters, and due to leverage recent advances in machine learning (ML) a new method is needed to unlock the “black box” to overcome its limitations such as low interpretability, out-of-sample failure and massive data demand. In this study, we developed a first-of-its-kind knowledge-guided machine learning model for agroecosystems (KGML-ag) by incorporating biogeophysical and chemical domain knowledge from an advanced PB model, ecosys, and tested it by comparing simulating daily N2O fluxes with real observed data from mesocosm experiments. The gated recurrent unit (GRU) was used as the basis to build the model structure. To optimize the model performance, we have investigated a range of ideas, including (1) using initial values of intermediate variables (IMVs) instead of time series as model input to reduce data demand; (2) building hierarchical structures to explicitly estimate IMVs for further N2O prediction; (3) using multi-task learning to balance the simultaneous training on multiple variables; and (4) pre-training with millions of synthetic data generated from ecosys and fine-tuning with mesocosm observations. Six other pure ML models were developed using the same mesocosm data to serve as the benchmark for the KGML-ag model. Results show that KGML-ag did an excellent job in reproducing the mesocosm N2O fluxes (overall r2=0.81, and RMSE=3.6 mgNm-2d-1 from cross validation). Importantly, KGML-ag always outperforms the PB model and ML models in predicting N2O fluxes, especially for complex temporal dynamics and emission peaks. Besides, KGML-ag goes beyond the pure ML models by providing more interpretable predictions as well as pinpointing desired new knowledge and data to further empower the current KGML-ag. We believe the KGML-ag development in this study will stimulate a new body of research on interpretable ML for biogeochemistry and other related geoscience processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A surface mechanism for O 3 production with N 2 addition in dielectric barrier discharges

Ozone, O 3 , is a strong oxidizing agent often used for water purification. O 3 is typically produced in dielectric barrier discharges (DBDs) by electron-impact dissociation of O 2 , followed by three-body association reactions between O and O 2 . Previous studies on O 3 formation in low-temperature plasma DBDs have shown that O 3 concentrations can drop to nearly zero after continued operation, termed the ozone-zero phenomenon (OZP). Including small (<4%) admixtures of N 2 can suppress this phenomenon and increase the O 3 production relative to using pure O 2 in spite of power deposition being diverted from O 2 to N 2 and the production of nitrogen oxides, N x O y . The OZP is hypothesized to occur because O 3 is destroyed on the surfaces in contact with the plasma. Including N 2 in the gas mixture enables N atoms to occupy surface sites that would otherwise participate in O 3 destruction. The effect of N 2 in ozone-producing DBDs was computationally investigated using a global plasma chemistry model. A general surface reaction mechanism is proposed to explain the increase in O 3 production with N 2 admixtures. The mechanism includes O 3 formation and destruction on the surfaces, adsorption and recombination of O and N, desorption of O 2 and N 2 , and NO x reactions. Without these reactions on the surface, the density of O 3 monotonically decreases with increasing N 2 admixture due to power absorption by N 2 leading to the formation of nitrogen oxides. With N-based surface chemistry, the concentrations of O 3 are maximum with a few tenths of percent of N 2 depending on the O 3 destruction probability on the surface. The consequences of the surface chemistry on ozone production are less than the effect of gas temperature without surface processes. An increase in the O 3 density with N-based surface chemistry occurs when the surface destruction probability of O 3 or the surface roughness was decreased.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Towards complete assignment of the infrared spectrum of the protonated water cluster H + (H 2 O) 21

The spectroscopic features of protonated water species in dilute acid solutions have been long sought after for understanding the microscopic behavior of the proton in water with gas-phase water clusters H + (H 2 O) n extensively studied as bottom-up model systems. We present a new protocol for the calculation of the infrared (IR) spectra of complex systems, which combines the fragment-based Coupled Cluster method and anharmonic vibrational quasi-degenerate perturbation theory, and demonstrate its accuracy towards the complete and accurate assignment of the IR spectrum of the H + (H 2 O) 21 cluster. The site-specific IR spectral signatures reveal two distinct structures for the internal and surface four-coordinated water molecules, which are ice-like and liquid-like, respectively. The effect of inter-molecular interaction between water molecules is addressed, and the vibrational resonance is found between the O-H stretching fundamental and the bending overtone of the nearest neighboring water molecule. The revelation of the spectral signature of the excess proton offers deeper insight into the nature of charge accommodation in the extended hydrogen-bonding network underpinning this aqueous cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A redox model for NO oxidation, NH 3 oxidation and high temperature standard SCR over Cu-SSZ-13

A kinetic model is developed to predict the influence of temperature and hydrothermal aging on the redox of active Cu sites under standard SCR, NO oxidation and NH 3 oxidation conditions over a practically relevant fully-formulated Cu-SSZ-13 catalyst. NO 2 /N 2 production during NO/NH 3 titration of Cu II sites is utilized to identify rate parameters associated with NO-only RHC (reduction half cycle) and NH 3 -only RHC respectively. Integral N 2 formation during subsequent NO + NH 3 titration is consistent with the production of one NO 2 per two CuII sites reduced during NO-only RHC and one N 2 per six Cu II sites reduced during NH 3 -only RHC. Decreased reduction of Cu II sites by NO/NH 3 upon hydrothermal aging, along with the production of one NO 2 per two CuII sites during NO-only RHC, is accordant with the involvement of proximal ZCuOH and oxygen-bridged dimeric Cu II sites. Oxidation of partially solvated and framework coordinated ZCu (Cu I ) sites occurs in presence of O 2 , does not produce N 2 and can lead to the consumption of Brønsted acid sites. A global OHC kinetic model is developed to predict transient and integral N 2 formation during exposure of CuI sites to a mixture of NO and O 2 . The resulting redox kinetic model quantitatively predicts NO and NH 3 consumption during isothermal transient response Cu redox (TRCR) protocols, along with temperature and age dependent steady-state standard SCR and oxidation conditions. The redox model presented in this work synthesizes recent kinetic, spectroscopic and computational findings to provide a foundational description of active site redox during standard SCR, NO oxidation and NH3 oxidation over Cu-SSZ-13.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Enhancing photoionization rate calculations in low-temperature plasmas using spectral methods

Photoionization plays a central role in the development of streamer discharges and other non-equilibrium plasma phenomena. It creates seed electrons, which are essential for positive streamer propagation, allowing the ionization front to move forward. Because of this, accurate modeling of photoionization is very important for predicting streamer behavior and plasma evolution. The photoionization process in air (N 2 – O 2 mixture) is often described by the Zheleznyak model (1982). This model is usually solved through Helmholtz-type equations that approximate the Zheleznyak photoionization model (Zheleznyak et al. 1982) as Partial Differential Equations (PDEs). Conventional numerical methods, such as the Finite Difference Method (FDM) or Finite Volume Method (FVM), are widely used to solve these equations. Although they are prevalent, the computational cost of these methods due to their need for matrix operations and iterative solver is demanding. To address this challenge, this work develops a spectral solver based on the Fast Fourier Transform (FFT) combined with Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) to calculate the photoionization rate efficiently in an axisymmetric cylindrical domain. This method naturally satisfies the boundary conditions used in the model and converts the PDE into algebraic ones in spectral space. Thus, avoids the need for iterative matrix solvers. When compared with FDM results, it is demonstrated that the new solver not only maintains accuracy, but also reduces the computational cost, showing a performance increase of approximately 100 compared to FDM over a wide range of problem sizes. The method is parallelized using Message Passing Interface (MPI) and has been integrated into a fluid plasma model for streamer simulation. Here, this FFT-based approach provides a fast and reliable alternative for calculating photoionization in fluid models, helping large-scale plasma simulations run faster and efficiently, and allows higher-resolution simulation without extra computational cost.

Axisymmetric system↗
DOE OSTI2024

Reduction of spectroscopic overlap across the Z = 8 shell in neutron-rich nuclei

The recent discovery and spectroscopic measurements of 27 O and 28 O suggests the disappearance of the N = 20 shell structure in these neutron-rich oxygen isotopes. We measured one- and two-proton removal cross sections from 27 F and 29 N, respectively, extracting spectroscopic factors and comparing them to shell model overlap functions coupled with eikonal reaction model calculations. The invariant mass technique was used to reconstruct the two-body ( 24 O + n) and three-body ( 24 O + 2n) decay energies from knockout reactions of 27 F (106.2 MeV/u) and 29 Ne (112.8 MeV/u) beams impinging on a 9 Be target. The one-proton removal from 27 F strongly populated the ground state of 26 O and the extracted cross section of $3.4^{+0.3}_{-1.5}$ mb agrees with eikonal model calculations that are normalized by the shell model spectroscopic factors and account for the systematic reduction factor observed for single nucleon removal reactions within the models used. For the two-proton removal reaction from 29 Ne an upper limit of 0.08 mb was extracted for populating states in 27 O decaying though the ground state of 26 O. The measured upper limit for the population of the ground state of 26 O in the two-proton removal reaction from 29 Ne indicates a significant difference in the underlying nuclear structure of 27 F and 29 Ne.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Quantum and anharmonic effects in non-adiabatic transition state theory

Quantitative descriptions of non-adiabatic transition rates at intermediate temperatures are challenging due to the simultaneous importance of quantum and anharmonic effects. Here, in this paper, the interplay between quantum effects—for motion across or along the seam of crossing—and anharmonicity in the seam potential is considered within the weak coupling limit. The well-known expression for quantized 1-D motion across the seam (i.e., tunneling) in the linear terms approximation is derived in the thermal domain using the Lagrangian formalism, which is then applied to the case when tunneling is distributed along the seam of crossing (treating motion along the seam classically). For high-frequency quantum modes, a vibrationally adiabatic (VA) approach is developed that introduces to the non-adiabatic rate constant a factor associated with high-frequency wavefunction overlap; this approach treats the high-frequency motion along the seam quantum mechanically. To test these methodologies, the reaction N 2 O ↔ N 2 + O( 3 P) was chosen. CCSD(T)-F12b/cc-pVTZ-F12 explorations of the 3 A'- 1 A' seam of N 2 O revealed that seam anharmonicity has a strong effect on the rate constant (a factor of ~20 at 2000 K). Several quantum effects were found to be significant at intermediate/lower temperatures, including the quantum N–N vibration that was coupled with seam anharmonicity using the VA approach. Finally, a 1-D approximation to non-adiabatic instanton theory is presented to estimate the validity limit of the linear terms model at low temperatures (⁠~ 250 K for N 2 O). We recommend that the assumptions built into many statistical theories for non-adiabatic reactions—harmonic behavior, classical motion, linear terms, and weak coupling—should be verified on a case-by-case basis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Benchmarking greenhouse gas emissions from US wastewater treatment for targeted reduction

Here, in this study, to assess the national climate impact of wastewater treatment and inform decarbonization, we assembled a comprehensive greenhouse gas inventory of 15,863 facilities in the contiguous USA. Considering location and treatment configurations, we modelled on-site CH 4 , N 2 O and CO 2 production and emissions associated with energy, chemical inputs and solids disposal. Using Monte Carlo simulations, we estimated median national emissions at 47 million tonnes of CO 2 equivalent per year, with on-site process CH 4 and N 2 O emissions exceeding current government estimates by 41%. Treatment configurations with anaerobic digesters are responsible for 16 million tonnes of CO 2 equivalent per year of fugitive methane, outweighing benefits achieved through on-site electricity generation. Systems designed for nutrient removal have the highest greenhouse gas emissions intensity, attributable to energy requirements and N 2 O production, demonstrating current trade-offs between meeting water quality and climate objectives. We analysed key sensitivities and included a geospatial analysis to highlight the scale and distribution of opportunities for reducing life cycle greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Quantum block encoding for one-pair semiseparable matrices

Quantum block encoding (QBE) is a crucial step in the development of most quantum algorithms, as it provides an embedding of a given matrix into a suitable larger unitary matrix. Historically, the development of efficient techniques for QBE has mostly focused on sparse matrices; less effort has been devoted to data-sparse (e.g., rank-structured) matrices. In this work we examine a particular case of rank structure, namely, one-pair semiseparable matrices. We present a new block encoding approach that relies on a suitable factorization of the given matrix as the product of triangular and diagonal factors. To encode the matrix, the algorithm needs $2\log(N)+7$ ancillary qubits. Assuming that the data input oracles can be implemented with polylogarithmic depth, or that a QRAM input model is available, our proposed method requires $\mathcal{O}({\rm polylog} (N))$ time and has an error of $\mathcal{O}(N^2)$, where $N$ is the matrix size.

Antonioli, Giacomo [Pisa U.; CERN] (ORCID:00090000↗