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DOE OSTI2020

Pump-and-Treat Impacts on Aquifer Conditions and the Development of System-Wide Performance Strategies - 20377

The pump-and-treat (P and T) system on the Hanford Site's Central Plateau currently treats multiple contaminants within the 200-ZP-1 operable unit, including nitrate through its biological treatment processes. Although it was initially designed to support the 200-ZP-1 Remedial Action Objectives, the P and T system has evolved in use to address contaminants from other regions of the aquifer as well. The P and T influents are biogeochemically distinct, treating groundwaters with elevated concentrations of cyanide, uranium, technetium-99, and nitrate. Given the varying geochemical signatures from current and potential future sources, operational conditions, and amendments considered for treatment processes, there is a need to identify the impacts that the P and T effluent has on the aquifer, and how the aquifer affects P and T performance. To this end, laboratory efforts have focused on characterizing P and T effluent and its biogeochemical effects on the sediments through a series repacked column experiments. The P and T effluent is rich in particulate matter. A systematic inspection of this particulate matter in the P and T effluent showed significant levels of manganese/iron oxides, calcite crystals, relatively large organic matter molecules, and biomass. Therefore, the column experiments were designed and conducted for four different treatment systems: artificial groundwater, filtered P and T effluent, non-filtered P and T effluent, and chlorinated P and T effluent. Different levels of microbiologically- and geochemically-induced changes in the columns occurred and modified the flow systems. For example, physical filtration occurred in the sediments where the particulate material had accumulated in the top portion of the column. Reactive transport modeling of the laboratory experiments is being carried out so that the reaction network can be extrapolated to the field scale. These simulations will provide predictive evaluations of system performance based on P and T operational changes and aquifer mass loading and capacity estimates. This information can be used to address combined subsurface and operational challenges, such as the need for frequent well redevelopment to maintain injection capacity. This information also provides the technical basis for decisions related to the P and T system operations that support remedy optimization efforts and short- and long-term remedy decisions related to multiple operable units on the Hanford Site Central Plateau. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Optimization of an Energy Tuning Assembly for High Explosives Detection

The Portable Isotopic Neutron Spectroscopy (PINS) system, employs neutron-induced gamma-ray spectroscopy and provides a nondestructive method for high explosives detection. In standard operation it uses Californium-252 as a neutron source. Operating PINS with a deuterium-tritium (DT) neutron generator has some advantages over Cf-252, including lifetime and ability to produce high-energy inelastic scattering gamma rays. However, current systems using DT neutron generators suffer from a high environmental background and reduced ability to induce neutron capture, reducing spectral quality and limiting nitrogen sensitivity. Here, this study presents the development of an energy-tuning assembly (ETA) designed to optimize the DT neutron energy spectrum to increase nitrogen reaction rates in a target, thereby improving high explosive detection capabilities. A metaheuristic optimization framework, MultiGNOWEE, coupled with MCNP, was employed to generate two ETA configurations: a single-objective ETA, which maximizes nitrogen capture reactions, and a multi-objective ETA, which balances neutron capture and inelastic scattering. Simulations demonstrated the optimized configurations achieved up to a 10-fold improvement in nitrogen capture rates compared to the bare configuration. Experimental validation was conducted using a DT neutron generator and a high-purity germanium (HPGe) detector. Two prototype ETAs were constructed and assessed on a melamine simulant. Measurements demonstrated improved nitrogen detection for both prototype ETA configurations when compared to the standard system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

M2CT-22IN1202096 Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration

Coal is a globally abundant resource that historically has been used for power generation via combustion. As the power industry replaces coal with cleaner methods of generation, energy-rich coal could be used in other chemical and fuel applications. This study presents a coal utilization option in which coal combustion is replaced with a carbon-free nuclear power plant and the coal is upgraded to valuable products for a variety of markets. Coal is prepared for conversion first by the pyrolysis process, which will optimize solid, liquid, and gaseous products based on the market size and potential product value, maximizing the monetary value of coal. This process is designed using bituminous coal from the Appalachian region as a basis to provide a pathway to preserve or transition coal-related jobs and create new jobs associated with the clean energy transition. Process modeling in the AspenOne Suite will be used to determine each component’s sensitivities, costs, inputs, and outputs. Dispatch modeling in the FORCE toolset will optimize the entire system and calculate the NPV for the refinery lifetime. Advanced and light-water reactors are considerations to supply the heat, steam, and electricity to the process. This paper focuses on the technical and market analysis used to determine the optimal processes and product pathways for the carbon refinery. Product pathways are on activated carbon, formic acid synthesis, and methanol synthesis for further upgrading to marketable chemical and polymer products.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Exploring the Great Pyramid: Stand-Alone Monte Carlo Simulations for Detector Optimization

Cosmic-ray muon imaging has been used to non-destructively examine the Pyramids of Khufu and Khafre on the Giza Plateau; the EGP project will continue this line of research by undertaking a full tomographic scan of the former and, in doing so, will increase the sensitivity of the technique by upwards of two orders of magnitude. This paper details the development of stand-alone Monte Carlo simulations intended to aid in optimizing the EGP detector system. While the rectangular scintillator model considered here does provide sucient position resolution in a few specic test cases, it is not the optimal telescope design. An attempted detector modication to permit tagging of muons by their incident momenta is also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Engineering local strain for single-atom nuclear acoustic resonance in silicon

Mechanical strain plays a key role in the physics and operation of nanoscale semiconductor systems, including quantum dots and single-dopant devices. In this report we describe the design of a nanoelectronic device, where a single nuclear spin is coherently controlled via nuclear acoustic resonance (NAR) through the local application of dynamical strain. The strain drives spin transitions by modulating the nuclear quadrupole interaction. We adopt an AlN piezoelectric actuator compatible with standard silicon metal–oxide–semiconductor processing and optimize the device layout to maximize the NAR drive. We predict NAR Rabi frequencies of order 200 Hz for a single 123Sb nucleus in a wide region of the device. Spin transitions driven directly by electric fields are suppressed in the center of the device, allowing the observation of pure NAR. Using electric field gradient-elastic tensors calculated by the density-functional theory, we extend our predictions to other high-spin group-V donors in silicon and to the isoelectronic 73Ge atom.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

A Comparison of Three Types of Computer-Based Procedures: An Experiment Using the Rancor Microworld Simulator

The nuclear power industry has historically used paper-based procedures, but a shift towards computer-based procedures (CBPs) has the potential to reduce human errors, alleviate mental workload, and improve work performance. Twenty-seven participants were randomly assigned to one of three CBP types using the Rancor Microworld Simulator, and each performed two different types of operational scenarios (startup and loss of feedwater). The three CBP types varied in levels of digitalization. It was hypothesized that there would be less favorable impressions of the most basic procedures, and that these would demonstrate lower usability than types with greater digitalization. Overall, our predictions were partially supported with some interesting caveats, specifically with some performance benefits for CBPs that provided indicators but not embedded controls. We discuss our findings in terms of optimal levels of digitalization/automation within nuclear operations and suggest pathways for future directions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

M2CT-22IN1202096 Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Evaluation of LPBF Steels for Nuclear Applications

This report provides an update on the prioritization of existing reactor materials for advanced manufacturing. This report is a Milestone 3 deliverable in FY2023, under work package CT-23AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). The focus of FY23 for ANL included the determination of a decision criteria matrix for the prioritization of existing materials, the literature review of a select few Fe-based alloys, and working with vendors to obtain customized powders. The work package also includes fabricating test samples in a Renishaw AM400 Laser Powder Bed Fusion (LPBF) system and optimizing the process parameters. The major outcomes of this work package are: With collaborations from PNNL, ORNL, and INL, we were able to establish a decision criteria matrix containing a total of 6 categories and 31 different criteria. These will be used to downselect alloys for further evaluation; As part of that, 6 different Fe-based alloys were selected, 3 austenitic stainless steels (A709, D9, AFA) and 3 ferritic/martensitic steels (HT9, Grade 91, Grade 92). Customized powders were obtained from vendors in small quantities to fabricate initial prints to check printability of these specific alloys; A total of 72 single track experiments were performed on two alloy systems, 1 austenitic stainless steel (A709) and 1 ferritic/martensitic steel (Grade 91) in order to optimize the process parameters for the full 3d prints. The optimization led to the selection of 20 different processing conditions, 10 for each class of alloys; D9 and AFA alloys showed extensive cracking and porosity in the samples. This was due to less-than-ideal conditions present in the chamber during the deposition. A709 printed using the same process parameters showed almost fully dense samples with no noticeable porosity or any other defects. SEM and EBSD analysis revealed single phase FCC microstructure with cellular structure within the grains; HT9, Grade 91, Grade 92 alloys also showed no noticeable signs of cracking and ImageJ analysis showed porosity <0.5% in all conditions. While Grade 91 and Grade 92 showed single phase BCC microstructures, the presence of martensite laths was noted in HT9 alloy; Future work will include further characterization of these alloys to better understand the microstructural evolution during the 3d printing process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Review of Tools for Modeling Core Radial Expansion in Liquid Metal-Cooled Fast Reactors

Core radial expansion in liquid-metal cooled fast reactor systems is a well-known phenomenon that produces strong reactivity feedback effects. It is crucial from a safety standpoint to design a reactor with the proper core restraint system to guide expansion of the fuel assemblies into a formation that produces negative reactivity feedback in accident conditions. However, the modeling of core radial expansion and its associated reactivity feedback is extremely challenging. Liquid metal-cooled fast reactor designers (both industry and commercial) have pointed to improved modeling of core radial expansion as a key modeling challenge for these types of reactors. The Department of Energy Nuclear Energy Advanced Modeling and Simulation (DOE-NEAMS) program has an important role to play in helping to develop a robust, predictive tool for this phenomenon. A literature review has been performed to identify current simulation capabilities applicable to the prediction of core radial expansion in liquid metal-cooled fast reactors and the resultant reactivity feedback effects. An overview as well as a detailed description of the multi-physics phenomena underlying core radial expansion is given in the first two chapters. The objective of this report is to identify existing software that has been or could be applied to the core radial expansion problem, and then to identify possible paths to develop a robust, coupled Multiphysics tool for advanced analysis, in which all three physics (radiation transport, structural mechanics, thermal fluids) are taken into account considering feedback effects from each physics to the other. Several computer codes and workflows have been developed in the United States and abroad to perform individual aspects of radial expansion calculations or to perform loosely coupled analysis. No code system currently exists which tightly and robustly couples the neutronics, thermal hydraulics, and thermal mechanical physics with enough detail to fully resolve the complex core radial expansion reactivity feedback effects. The future availability of such a code system is of vital importance to fully understanding the reactivity feedback effects that occur due to radial expansion, and consequently to optimizing the design of the core restraint system. A potential code development path forward using MOOSE-based tools is suggested in order to leverage the natural tight coupling and robustness of MOOSE-based applications. Additionally, potential gaps for modeling and common assumptions are listed which require further investigation to ensure accuracy for prediction of deformations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe-Cr alloy

Laser Direct Energy Deposition (DED) is a metal additive manufacturing technique with the ability to fabricate large and complex parts through deposition of metal powders. However, achieving high-density parts and targeted build heights using DED can be challenging due to the large number of highly sensitive process variables. This work proposes a robust fabrication parameter optimization framework to generate process maps for primary parameters in DED, including laser power, scan speed, mass flow rate, hatch spacing, and layer height. Simple single-track experiments were utilized to map out the parameter space, and a combination of geometric criteria for hatch spacing and layer height were proposed to determine parameter sets that achieve both targeted build heights and mitigate porosity formation. Using this framework, specimens with >99 % density and consistent mechanical properties were successfully fabricated over a wide range of process parameters for an Fe-9wt.%Cr (Fe9Cr) alloy, a surrogate for radiation damage-resistant reduced activation ferritic/martensitic (RAFM) steels. Processing these materials using DED is of particular interest in the development of plasma facing components for nuclear fusion applications. The microstructure and mechanical properties of as-printed Fe9Cr were characterized using optical and electron microscopy, X-ray diffraction, and uniaxial tensile tests. As-printed Fe9Cr displayed ~25 % elongation and ultimate tensile strengths of up to 475 MPa which is comparable to similar wrought alloys. Finally, the proposed framework will allow for accelerated DED parameter optimization for novel alloy systems, as well as open the possibility for local microstructure control while simultaneously mitigating defect formation.

42 ENGINEERING↗

DOE OSTI2022

Development and verification of the pyIsoDep depletion package for nuclear thermal propulsion reactors

Nuclear thermal propulsion technology is currently being developed by the National Air and Space Administration for future manned Mars missions. There are multiple on-going activities to develop and enhance computational capabilities, single- and multi-physics, to advance the readiness level of this technology. The prediction of short-lived fission products is crucial to understand the reactivity penalty and the decay heat production during the different burnout stages of the vehicle. Generally, the solution entails coupled neutronic-depletion analysis. However, such simulations are somewhat expensive, especially if the duration of each engine burn is to be optimized. Therefore, there is a need to complement such high-fidelity techniques with time-efficient alternatives that do not require the sequential neutronic and depletion analysis. This paper details the methods and capabilities of pyIsoDep, an open-source code used for depletion analysis of nuclear thermal propulsion reactors. The package is general, in principle, and thus can be applied to any fission system, and can potentially be extended for fusion systems. The package was developed to provide a flexible and efficient alternative to pre-existing higher order depletion codes that could integrate well into mission and transient analysis of nuclear thermal propulsion reactors. Finally, this paper presents a validation and verification of pyIsoDep against analytical and Serpent-generated solutions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Initial Characterization and Optimization of the Liquid Sampling-Atmospheric Pressure Glow Discharge Ionization Source Coupled to an Orbitrap Mass Spectrometer for the Determination of Plutonium

Plutonium measurements are essential to the nuclear forensics and safeguards community. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled with an Orbitrap mass spectrometer is a proven platform for uranium isotope ratio determinations. Here, this work expands the LS-APGD-Orbitrap platform capabilities by reporting the first-ever analysis of plutonium with the LS-APGD and the first-ever measurement of elemental plutonium with an Orbitrap mass spectrometer. This coupling has the potential to dramatically reduce the complex sample manipulations required for traditional analysis techniques employed for actinide isotope ratio determinations. As a first step toward the goal of simultaneous uranium and plutonium isotope ratio determinations, the initial characterization and optimization of the platform for the detection of plutonium are reported. Collision-induced dissociation modality settings were optimized to reduce water-related and other molecular clusters containing plutonium, maximizing 242 Pu 16 O 2 + responses. A design of experiments study was conducted to optimize the discharge conditions of the dual-electrode LS-APGD toward the responsivity of 242 Pu 16 O 2 +. The measurement sensitivity was determined from a Pu response curve, yielding a limit of detection of 10 fg (absolute) of total analyte when data was collected and processed with a Spectroswiss FTMS Booster X2 data acquisition system. Additionally, plutonium and uranium were measured in a simultaneous acquisition, and each analyte remained unaffected by the other. It is believed that the LS-APGD-Orbitrap platform could be a valuable addition to the nuclear forensics’ toolbox and, indeed, other scientific disciplines and regulatory communities in which rapid, high-resolution plutonium determinations are paramount.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Improved high-throughput screening technique to rapidly isolate Chlamydomonas transformants expressing recombinant proteins

Abstract The single-celled eukaryotic green alga Chlamydomonas reinhardtii has long been a model system for developing genetic tools for algae, and is also considered a potential platform for the production of high-value recombinant proteins. Identifying transformants with high levels of recombinant protein expression has been a challenge in this organism, as random integration of transgenes into the nuclear genome leads to low frequency of cell lines with high gene expression. Here, we describe the design of an optimized vector for the expression of recombinant proteins in Chlamydomonas , that when transformed and screened using a dual antibiotic selection, followed by screening using fluorescence activated cell sorting (FACS), permits rapid identification and isolation of microalgal transformants with high expression of a recombinant protein. This process greatly reduces the time required for the screening process, and can produce large populations of recombinant algae transformants with between 60 and 100% of cells producing the recombinant protein of interest, in as little as 3 weeks, that can then be used for whole population sequencing or individual clone analysis. Utilizing this new vector and high-throughput screening (HTS) process resulted in an order of magnitude improvement over existing methods, which normally produced under 1% of algae transformants expressing the protein of interest. This process can be applied to other algal strains and recombinant proteins to enhance screening efficiency, thereby speeding up the discovery and development of algal-derived recombinant protein products. Key points • A protein expression vector using double-antibiotic resistance genes was designed • Double antibiotic selection causes fewer colonies with more positive for phenotype • Coupling the new vector with FACS improves microalgal screening efficiency > 60%

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Tandem synthesis of tetrahydroquinolines and identification of the reaction network by operando NMR

The study of the reaction mechanism and complex network for heterogeneously catalyzed tandem reactions is challenging but can guide reaction design and optimization. Here, we describe a case study using bifunctional metal–organic framework supported Pd nanoparticles (Pd/UiO-66(HCl)) for the one-pot tandem synthesis of substituted tetrahydroquinolines via the Claisen–Schmidt condensation and reductive intramolecular cyclization. The directly observed evolution of intermediates and products, including reactive species containing hydroxylamine group and unstable intermediate 2-phenyl-3,4-dihydroquinoline, was enabled by operando magic angle spinning nuclear magnetic resonance studies under 50 bar H 2 . The reaction network of the tandem reaction is deduced based on reaction kinetic information obtained from the operando study. The optimized procedure was applied to various acetophenone and nitrobenzaldehyde derivatives carrying different functional groups, and eight valuable substituted tetrahydroquinolines were obtained in moderate to good yields. This work provides a molecular-level understanding of the catalytic system and brings up new opportunities for efficient and sustainable synthesis of medicinally relevant building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Structure optimization with stochastic density functional theory

Linear-scaling techniques for Kohn–Sham density functional theory are essential to describe the ground state properties of extended systems. Still, these techniques often rely on the localization of the density matrix or accurate embedding approaches, limiting their applicability. In contrast, stochastic density functional theory (sDFT) achieves linear- and sub-linear scaling by statistically sampling the ground state density without relying on embedding or imposing localization. In return, ground state observables, such as the forces on the nuclei, fluctuate in sDFT, making optimizing the nuclear structure a highly non-trivial problem. In this work, we combine the most recent noise-reduction schemes for sDFT with stochastic optimization algorithms to perform structure optimization within sDFT. We compare the performance of the stochastic gradient descent approach and its variations (stochastic gradient descent with momentum) with stochastic optimization techniques that rely on the Hessian, such as the stochastic Broyden–Fletcher–Goldfarb–Shanno algorithm. In conclusion, we further provide a detailed assessment of the computational efficiency and its dependence on the optimization parameters of each method for determining the ground state structure of bulk silicon with varying supercell dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Non-Hermitian Quantum Mechanics Approach for Extracting and Emulating Continuum Physics Based on Bound-State-like Calculations

Here, this Letter introduces a unified emulation framework for studying continuum physics in finite quantum systems. Using a reduced basis method, we construct powerful emulators for the inhomogeneous Schrödinger equation that operate in a combined parameter space of complex energy (𝐸) and other inputs (𝜽). Within the space, the emulators simultaneously perform analytical continuation in 𝐸—extracting continuum physics from numerically simpler bound-state-like calculations—and interpolate this entire process across 𝜽. This yields a small, non-Hermitian system whose properties (e.g., resonances and scattering observables) can be rapidly predicted for any 𝜽. Crucially, the complex-𝐸 emulation provides a pathway to compute continuum observables for complex systems where advanced bound-state methods exist but direct continuum calculations are yet to be developed, while the 𝜽 emulation enables rapid parameter-space exploration and can be adapted to accelerate other existing continuum calculations. Demonstrations with two- and three-body systems highlight the method’s effectiveness and suggest its connection to (near-)optimal rational approximation. This Letter presents the key results, with further details reserved for a companion paper.

ab initio calculations↗