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DOE OSTI2025

Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1997

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Koch, Patrick N.↗

DOE OSTI2019

PAPI software-defined events for in-depth performance analysis

The methodology and standardization layer provided by the Performance Application Programming Interface (PAPI) has played a vital role in application profiling for almost two decades. It has enabled sophisticated performance analysis tool designers and performance-conscious scientists to gain insights into their applications by simply instrumenting their code using a handful of PAPI functions that “just work” across different hardware components. In the past, PAPI development had focused primarily on hardware-specific performance metrics. However, the rapidly increasing complexity of software infrastructure poses new measurement and analysis challenges for the developers of large-scale applications. In particular, acquiring information regarding the behavior of libraries and runtimes—used by scientific applications—requires low-level binary instrumentation, or APIs specific to each library and runtime. No uniform API for monitoring events that originate from inside the software stack has emerged. In this article, we present our efforts to extend PAPI’s role so that it becomes the de facto standard for exposing performance-critical events, which we refer to as software-defined events (SDEs), from different software layers. Upgrading PAPI with SDEs enables monitoring of both types of performance events—hardware- and software-related events—in a uniform way, through the same consistent PAPI. The goal of this article is threefold. First, we motivate the need for SDEs and describe our design decisions regarding the functionality we offer through PAPI’s new SDE interface. Second, we illustrate how SDEs can be utilized by different software packages, specifically, by showcasing their use in the numerical linear algebra library MAGMA-Sparse, the tensor algebra library TAMM that is part of the NWChem suite, and the compiler-based performance analysis tool Byfl. Third, we provide a performance analysis of the overhead that results from monitoring SDEs and discuss the trade-offs between overhead and functionality.

Jagode, Heike↗

DOE OSTI2025

Single-Determinant Ground State in Ce 4+ Imidophosphorane Complexes

X-ray spectroscopy techniques are critical in the electronic structure analysis of high-valent lanthanides. The interpretation of multipeaked features at the lanthanide L 3 -edge has remained a challenging question, as it is observed across a range of material classes. A series of structurally related Ce 4+ complexes were prepared to probe the potential ligand field perturbation of the ground state within the series. The tuning of relative 4f and ligand orbital energies in homoleptic and heteroleptic tetravalent Ce imidophosphorane complexes is achieved through ligand derivatization and is clearly demonstrated by UV−vis spectroscopy and electrochemically measured redox potentials. However, Ce L 3 - edge high-energy resolution fluorescence-detected (HERFD) X-ray absorption near-edge structure (XANES) spectra present features at consistent numbers and energies across the range of complexes. Resonant inelastic X-ray scattering (RIXS) is employed to visualize the observed features in the HERFD-XANES spectra. Large complete active space configuration interaction singles and doubles (CASCISD) calculations demonstrate that the ground-state wave function of all complexes can be described employing a single determinant. As a result, the multielectron feature at the L 3 -edge observed in this study for the Ce 4+ imidophosphorane complexes is described as excited-state multiconfigurational behavior that is independent of ligand variation, in systems where the ground state is described using the simple single determinant wave function.

Lanthanides↗

DOE OSTI2022

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Assemblies of Polyacrylonitrile-Derived Photoactive Polymers as Blue and Green Light Photo-Cocatalysts for Cu-Catalyzed ATRP in Water and Organic Solvents

Photoluminescent nanosized quasi-spherical polymeric assemblies prepared by the hydrothermal reaction of polyacrylonitrile (PAN), ht-PLP PAN , were demonstrated to have the ability to photo-induce atom transfer radical polymerization (ATRP) catalyzed by low, parts per million concentrations of Cu II complex with tris(2-pyridylmethyl)amine (TPMA). Such photo induced ATRP reactions of acrylate and methacrylate monomers were performed in water or organic solvents, using ht-PLP PAN as the photo-cocatalyst under blue or green light irradiation. Mechanistic studies indicate that ht-PLP PAN helps to sustain the polymerization by facilitating the activation of alkyl bromide species by two modes: 1) green or blue light-driven photoreduction of the Cu II catalyst to the activating Cu I form, and 2) direct activation of dormant alkyl bromide species which occurs only under blue light. The photoreduction of the Cu II complex by ht-PLP PAN was confirmed by linear sweep voltammetry performed under illumination. Analysis of the polymerization kinetics in aqueous media indicated even though Cu I complexes comprised only 1–1.4% of all Cu species at equilibrium, they exhibited high activation rate constant and activated the alkyl bromide initiators five to six orders of magnitude faster than ht-PLP PAN .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

The physics of the environmental sensitivity of rubidium gas cell atomic frequency standards

Environmental sensitivity is often the most significant limitation to the practical stability of rubidium frequency standards (RFS). For example, temperature sensitivity can cause a rapid frequency change of several parts in 10(exp 10) for a tactical RFS that has an aging of only 1 times 10(exp -11)/month. Other important environmental factors are barometric pressure, vibration, magnetic field, and nuclear radiation. The physical mechanisms that lie behind these environmental sensitivities are considered. These physical mechanisms are related to the performance of actual rubidium frequency standards. For the user of these devices, a better knowledge of the causes for Rb clock instability will aid in their testing and proper application. For the time frequency specialist, a review of these factors may prove useful toward improving RFS design. Some of the RFS environmental sensitivities are due to simple physical mechanisms like the effect of dc magnetic field on the Rb hyperfine resonance frequency. For these, an analysis can be based on physical principles and straightforward design factors. Other environment factors, like temperature sensitivity, are more complex combinations of many effects, both physical and practical, and the analysis often takes the form of an error budget with large unit-to-unit variations. Today's rubidium frequency standards span a wide performance range from small, inexpensive units with pp 10(exp 10) error budgets to larger, higher performance versions offering pp 10(exp 10) stabilities. For both extremes, however, environmental sensitivity can be the most significant performance limitation. Why this is the case and how to make improvements are discussed.

Riley, William J.↗

NASA NTRS2005

State Analysis: A Control Architecture View of Systems Engineering

A viewgraph presentation on the state analysis process is shown. The topics include: 1) Issues with growing complexity; 2) Limits of common practice; 3) Exploiting a control point of view; 4) A glimpse at the State Analysis process; 5) Synergy with model-based systems engineering; and 6) Bridging the systems to software gap.

state analysis↗

DOE OSTI2026

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗

DOE OSTI2024

Scaling the SciDAC QuantOm Workflow

As part of the Scientific Discovery through Advanced Computing (SciDAC) program, the Quantum Chromodynamics Nuclear Tomography (QuantOM) project aims to analyze data from Deep Inelastic Scattering (DIS) experiments conducted at Jefferson Lab and the upcoming Electron Ion Collider. The DIS data analysis is performed on an event-level by combining the input from theoretical and experimental nuclear physics into a single, composable workflow. The optimization itself (I.e. fitting the experimental data with theoretical predictions) is carried out by a machine / deep learning algorithm. The size of the acquired DIS data as well as the complexity of the workflow itself require that the analysis is performed across multiple GPUs on high performance computing systems, such as Polaris at Argonne National Laboratory. This presentation discusses the novelties and challenges that came along with parallelizing this workflow. Recent results are compared to common distributed training techniques.

Lersch, Daniel↗

DOE OSTI2018

Spectroscopic, Computational, Antimicrobial, DNA Interaction, In Vitro Anticancer and Molecular Docking Properties of Biochemically Active Cu(II) and Zn(II) Complexes of Pyrimidine-Ligand

Biochemically active Cu(II) and Zn(II) complexes [CuL(ClO{sub 4}){sub 2}(1) and ZnL(ClO{sub 4}){sub 2}(2)] have been synthesized from N,N donor Schiff base ligand L derived from4,6-dichloropyrimdine-5-carboxaldehyde with 4-(2-aminoethyl)morpholine. The L, complexes 1 and 2 have been structurally characterized by elemental analysis, {sup 1}H-NMR, FTIR, MS, UV-Visible and ESR techniques. The results obtained from the spectral studies supports the complexes 1 and 2 are coordinated with L through square planar geometry. DFT calculations results supports, the ligand to metal charge transfer mechanism can occur between L and metal(II) ions. The antimicrobial efficacy results have been recommended that, complexes 1 and 2 are good anti-pathogenic agents than ligand L. The interaction of complexes 1 and 2 with calf thymus (CT) DNA has been studied by electronic absorption, viscometric, fluorometric and cyclic voltammetric measurements. The calculated K{sub b} values for L, complexes 1 and 2 found from absorption titrations was 4.45 × 10{sup 4}, L; 1.92 × 10{sup 5}, 1 and 1.65 × 10{sup 5}, 2. The Ksv values were found to be 3.0 × 10{sup 3}, 3.68 × 10{sup 3}and 3.52 × 10{sup 3} for L, complexes 1 and 2 by using competitive binding with ethidium bromide (EB). These results suggest that, the compounds are interacted with DNA may be electrostatic binding. The molecular docking studies have been carried out to confirm the interaction of compounds with DNA. Consequently, in vitro anticancer activities of L, complexes 1 and 2 against selected cancer (lung cancer A549, liver cancer HepG2 and cervical carcinoma HeLa) and normal (NHDF) cell lines were assessed by MTT assay.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Dichlorosilylene–hydrogen chloride complex: direct IR spectroscopic detection in argon matrix

A 1: 1 donor–acceptor complex between SiCl{sub 2} and HCl was detected by matrix IR spectroscopy. The existence of the complex was previously predicted theoretically in the course of analysis of mechanisms of chemical vapor deposition (CVD) processes involving chlorosilanes. The quantum chemical calculations at the G4(MP{sub 2}) level confirmed the possibility of formation of only one stable complex upon the reaction of SiCl{sub 2} with HCl. In addition to the complex of the simplest composition, complexes of SiCl{sub 2} with HCl associates were observed upon matrix annealing. The only product formed upon the photolysis of the complexes of all types was trichlorosilane, a product of silylene insertion into the H–Cl bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1988

Dypas: A dynamic payload scheduler for shuttle missions

Decision and analysis systems have had broad and very practical application areas in the human decision making process. These software systems range from the help sections in simple accounting packages, to the more complex computer configuration programs. Dypas is a decision and analysis system that aids prelaunch shutlle scheduling, and has added functionality to aid the rescheduling done in flight. Dypas is written in Common Lisp on a Symbolics Lisp machine. Dypas differs from other scheduling programs in that it can draw its knowledge from different rule bases and apply them to different rule interpretation schemes. The system has been coded with Flavors, an object oriented extension to Common Lisp on the Symbolics hardware. This allows implementation of objects (experiments) to better match the problem definition, and allows a more coherent solution space to be developed. Dypas was originally developed to test a programmer's aptitude toward Common Lisp and the Symbolics software environment. Since then the system has grown into a large software effort with several programmers and researchers thrown into the effort. Dypas is currently using two expert systems and three inferencing procedures to generate a many object schedule. The paper will review the abilities of Dypas and comment on its functionality.

Davis, Stephen↗

DOE OSTI2023

Operation Optimization using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Improved Platform for the Benchtop Study of Complex Radiological Environments that Affect Fallout Formation: DHS Feasbility Study (Final Report)

Fallout analysis is a crucial field of study as it provides insight into the structural interactions that occur between radiological components and their surroundings following a nuclear event. Due to the complexity of actual fallout samples, setups like the plasma flow reactor (PFR) at LLNL have been developed to synthesize fallout in a controlled environment. While the PFR allows for control of parameters such as initial temperature, cooling rate, and concentration of radiological species, controlling the concentration of water has remained a challenge as samples are introduced into the setup via aqueous solution. To that end, our goal with this project was to develop methodologies to (1) monitor and (2) control the presence of water in the PFR. We found that a commercially available FTIR and MCT detector was sufficient to monitor the presence of both condensed and vapor-phase water, while a desolvating nebulizer could be used to control the amount of water injected into the system. In total, the results of this feasibility study have expanded the ability of the flow reactor to investigate key sensitivities that influence fallout formation.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2026

Average hydrodynamic radius analysis reveals critical solvation thresholds in high-concentration lithium electrolytes

Understanding the solvation structures of lithium salts in carbonate- and ether-based electrolytes is central to explaining the exceptional stability of high-concentration electrolytes (HCEs) and localized high-concentration electrolytes (LHCEs). Conventional techniques such as vibrational spectroscopy and one-dimensional NMR provide only limited information, typically restricted to coordination ratios and ion-pair distributions, without revealing the actual size and mass of solution complexes. Here, in this study, we introduce an average hydrodynamic radius (AHR) analysis based on internally referenced DOSY NMR, which enables direct estimation of the average volume and molecular weight of lithium–solvent complexes in solution. Using LiFSI–EMC and LiFSI–EMC–TTE electrolytes, we demonstrate that the onset of effective lithium metal stabilization and aluminum corrosion suppression coincides with the formation of very large complexes, whose average volume exceeds 300 times that of free EMC molecules. This finding supports a new “blocking mechanism,” wherein bulky solvated complexes impede direct solvent access to reactive surfaces. The AHR analysis thus not only clarifies the fundamental origin of HCE and LHCE effectiveness, but also provides a broadly applicable experimental framework for probing complex solvation structures and guiding rational electrolyte design.

Concentrated electrolytes↗

DOE OSTI2023

Development of LpxH Inhibitors Chelating the Active Site Dimanganese Metal Cluster of LpxH

Abstract Despite the widespread emergence of multidrug‐resistant nosocomial Gram‐negative bacterial infections and the major public health threat it brings, no new class of antibiotics for Gram‐negative pathogens has been approved over the past five decades. Therefore, there is an urgent medical need for developing effective novel antibiotics against multidrug‐resistant Gram‐negative pathogens by targeting previously unexploited pathways in these bacteria. To fulfill this crucial need, we have been investigating a series of sulfonyl piperazine compounds targeting LpxH, a dimanganese‐containing UDP‐2,3‐diacylglucosamine hydrolase in the lipid A biosynthetic pathway, as novel antibiotics against clinically important Gram‐negative pathogens. Inspired by a detailed structural analysis of our previous LpxH inhibitors in complex with K. pneumoniae LpxH ( Kp LpxH), here we report the development and structural validation of the first‐in‐class sulfonyl piperazine LpxH inhibitors, JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ), that achieve chelation of the active site dimanganese cluster of Kp LpxH. The chelation of the dimanganese cluster significantly improves the potency of JH‐LPH‐45 ( 8 ) and JH‐LPH‐50 ( 13 ). We expect that further optimization of these proof‐of‐concept dimanganese‐chelating LpxH inhibitors will ultimately lead to the development of more potent LpxH inhibitors for targeting multidrug‐resistant Gram‐negative pathogens.

Pharmacology & Pharmacy↗

DOE OSTI2020

Metabolic Pathway Engineering

Modern microbial and enzyme engineering and their advancement are increasingly dependent on the marriage of a wide range of sophisticated technologies. For students entering the field of biotechnology, the outlook is indeed daunting. Expertise at levels beyond that of simple familiarity will be needed to conduct competitive research. It goes without saying that to be competitive, all new researchers in this field will need basic preparation in molecular biology, biochemistry, and genetics. Further, experience working with concepts and experimental tools in enzyme biochemistry and kinetics, gene editing, computational metabolic pathway modeling, experimental pathway flux analysis, and computational clustering tools to process complex data sets will be vital for success. We speculate that most biotechnology researchers in early career at this time will build teams of collaborators to address these disparate science fields rather than attempt to become experts in one lab.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗