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DOE OSTI2025

Performance evaluations of signed and unsigned noisy approximate quantum Fourier arithmetic

The Quantum Fourier Transform (QFT) grants competitive advantages, especially in resource usage and circuit approximation, for performing arithmetic operations on quantum computers, and offers a potential route toward a numerical quantum-computational paradigm. In this paper, we utilize efficient techniques to implement QFT-based integer addition and multiplications. These operations are fundamental to various quantum applications including Shor’s algorithm, weighted-sum optimization problems in data processing and machine learning, and quantum algorithms requiring inner products. We carry out performance evaluations of these implementations based on IBM’s superconducting-qubit architecture using different compatible noise models. We isolate the sensitivity of the component quantum circuits on both one-/two-qubit gate error rates, and the number of the arithmetic operands’ superposed integer states. We analyze performance and identify the most effective approximation depths for unsigned quantum addition and quantum multiplication within the given context. We then perform a similar analysis of signed addition and compare to the unsigned results. We observe significant dependency of the optimal approximation depth on the degree of machine noise and the number of superposed states in certain performance regimes. Finally, we elaborate on the algorithmic challenges—relevant to signed, unsigned, modular and non-modular versions—that could also be applied to current implementations of QFT-based subtraction, division, exponentiation, and their potential tensor extensions. Here, we analyze the performance trends in our results and speculate on possible future developments within this computational paradigm.

Computational models↗

DOE OSTI2021

Mocking the u-plane integral

Abstract The u -plane integral is the contribution of the Coulomb branch to correlation functions of $${\mathcal {N}}=2$$ N = 2 gauge theory on a compact four-manifold. We consider the u -plane integral for correlators of point and surface observables of topologically twisted theories with gauge group $$\mathrm{SU}(2)$$ SU ( 2 ) , for an arbitrary four-manifold with $$(b_1,b_2^+)=(0,1)$$ ( b 1 , b 2 + ) = ( 0 , 1 ) . The u -plane contribution equals the full correlator in the absence of Seiberg–Witten contributions at strong coupling, and coincides with the mathematically defined Donaldson invariants in such cases. We demonstrate that the u -plane correlators are efficiently determined using mock modular forms for point observables, and Appell–Lerch sums for surface observables. We use these results to discuss the asymptotic behavior of correlators as function of the number of observables. Our findings suggest that the vev of exponentiated point and surface observables is an entire function of the fugacities.

Mathematics↗

DOE OSTI2023

Large Format Composite Additive Manufacturing for Low-Head Hydropower

Hydropower with a small elevation change from inlet to outlet, known as “low-head” hydropower, is a relatively untapped resource for reliable green power generation. One major barrier to entry is the cost of the components needed to generate the power. Each installation site is unique, with various head levels, flow rates, and other unique site characteristics that drive up the cost of development and installation. As a result, custom-made components are necessary because the sites are intrinsically inefficient. However, customized parts are generally more expensive to manufacture than ready-made parts. Often times, the cost of custom-made components is so high that the low-head hydropower installation becomes non-viable. Additive manufacturing offers the ability to make custom components, ideal for one-off applications, at low costs that are well suited for the needs of low-head hydropower. Indirect additive manufacturing, such as making tools or dies rather than end use components, can also be used to make low-cost composite tooling as needed for these custom applications. This paper explores the use of additive manufacturing, both directly and indirectly, to produce the components of a turbine system for a low-head hydropower site. The parts were designed to form a unique modular system, which saves time for future designs and iterations. The system has operated for more than three years without failure at a test site in Wisconsin, USA. This work serves as a basis for future application of AM to low-head systems, in which the modular components can be customized for each unique hydropower installation.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Automated compatibility checking of prefabricated components using 3D as-built models and BIM

There have been recent efforts to use reality capture technologies to perform remote quality control in construction. However, there is a lack of research efforts in detecting construction incompatibilities in modular construction using reality capture technologies. The construction incompatibilities in modular construction often cause reworks and delays in the project schedule. To address this issue, this paper presents a general compatibility analysis method that propose scanning the modules in manufacturing plant and construction site, and check module-to-module compatibility remotely, prior to the shipment and installation. This study provides three sample module-to-module compatibility scenarios to validate the proposed compatibility analysis. The case study results show that the compatibility analysis method was able to identify the compatibility issues with high accuracy. Lastly, the compatibility analysis method was validated in terms of accuracy and time performance in six scenarios that was defined on the modules.

42 ENGINEERING↗

DOE OSTI2023

Reinforced double-threaded slide-ring networks for accelerated hydrogel discovery and 3D printing

Traditionally, slide-ring gels are stretchable but soft as a result of an elasticity-stretchability trade-off. Herein, we introduce a new approach to breaking this trade-off and creating reinforced slide-ring networks with mobile crosslinkers. Our approach involves the construction of a polyethylene glycol double-threaded γ-cyclodextrin-based pro-slide-ring crosslinker that serves as a modular component for 3D printing and copolymerization. The resulting crystalline-domain-reinforced slide-ring hydrogels, or CrysDoS-gels, exhibit both high elasticity and high stretchability. The modular synthesis allows for high-throughput synthesis of CrysDoS-gels, generating a large amount of data for structure-property analysis. Here, by employing data science techniques, such as machine learning and linear regression, not only were we able to identify which chemical components influence the mechanical properties of CrysDoS-gels, but this analysis also aided in the discovery of better-performing CrysDoS-gels. Finally, we demonstrate the potential application of the newly discovered CrysDoS-gels as sensing devices by 3D printing them as stress sensors with high sensitivity and a broad detection range.

3D-printing↗

DOE OSTI2026

Phenomena-based graph representations and applications to chemical process simulation

Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.

Convergence↗

DOE OSTI2021

Water desalination through the dewpoint evaporative system

This paper presents the first numerical analysis of a novel Dew Point Desalination unit (DPD), which utilizes the phenomenon of the evaporative cooling process to minimize energy consumption. The proposed solution is based on a modular structure, which allows it to obtain any required water production capacity. The analyses for various operational parameters and various climatic conditions are based on the numerical simulations conducted using a validated mathematical model. The system performance was described with different factors, including specific energy consumption (SEC) and daily water production rate respected to 1 m^3*s^-1 of passing air stream (DWP). It is shown that the DPD system can operate in almost every climate zone, and the desalinated water production consumes less than 1.5 kWh*m^-3 of electric energy It is noted the best performance of the DPD system is achieved in the semi-arid, desert and subtropical climate zones. In these climate zones, the 2-stage DPD system allows the production of desalinated water with an electric energy consumption SEC lower than 0.5 kWh*m^-3. The additional benefit of the DPD system is its modularity. The presented DPD system stands as a module, that can be multiplied as needed to achieve the desired size of the desalination plant.

Desalination↗

DOE OSTI2026

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Documentation, assessment, and improvements of fission gas modeling capabilities in BISON

Fission gas behavior critically affects nuclear fuel performance, influencing thermal conductivity, microstructure, swelling, and fuel-cladding interactions. The Simple Integrated Fission Gas Release and Swelling (Sifgrs) model, implemented within the BISON fuel performance code, provides advanced capabilities for modeling these phenomena. This manuscript reviews and assesses Sifgrs’ modular structure and submodels describing intragranular, intergranular, and release mechanisms. The modular implementation enables rapid improvements as our understanding advances and new fuel forms emerge. After an overview of capabilities, we present a comprehensive validation suite, comparing predictions to experimental data from tests under normal and transient conditions, including reproduction of the Vitanza curve. Results demonstrate Sifgrs’ accuracy, robustness, and applicability. Current limitations and ongoing efforts are discussed, including mechanistic, multiscale modeling, uncertainty quantification, and validation within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, supporting the safe and efficient use of nuclear fuels.

BISON↗

DOE OSTI2016

High voltage testing for the Majorana Demonstrator

The Majorana Collaboration is constructing theMajorana Demonstrator, an ultra-low background, 44-kg modular high-purity Ge (HPGe) detector array to search for neutrinoless double-beta decay in 76Ge. The phenomenon of surface micro-discharge induced by high-voltage has been studied in the context of theMajorana Demonstrator. This effect can damage the front-end electronics or mimic detector signals. To ensure the correct performance, every high-voltage cable and feedthrough must be capable of supplying HPGe detector operating voltages as high as 5 kV without exhibiting discharge. R&D measurements were carried out to understand the testing system and determine the optimum design configuration of the high-voltage path, including different improvements of the cable layout and feedthrough flange model selection. Every cable and feedthrough to be used at the Majorana Demonstrator was characterized and the micro-discharge effects during theMajorana Demonstrator commissioning phase were studied. A stable configuration has been achieved, and the cables and connectors can supply HPGe detector operating voltages without exhibiting discharge.

high-voltage↗

DOE OSTI2017

Design and R&D of RICH detectors for EIC experiments

An Electron-Ion Collider (EIC) has been proposed to further explore the strong force and QCD, focusing on the structure and the interaction of gluon-dominated matter. A generic detector R& D program (EIC PID consortium) for the particle identification in EIC experiments was formed to explore technologically advanced solutions in this scope. In this context two Ring Imaging Cherenkov (RICH) counters have been proposed: a modular RICH detector which consists of an aerogel radiator, a Fresnel lens, a mirrored box, and pixelated photon sensor; a dual-radiator RICH, consisting of an aerogel radiator and C 2 F 6 gas in a mirror-focused configuration. We present the simulations of the two detectors and their estimated performance.

electron-ion collider↗

DOE OSTI2026

ALPHANSO: Open-source modeling of (α, n) neutron source terms

Applications ranging from nuclear safeguards to dark matter detection require accurate predictions of neutron yields and energy spectra produced by (α, n) reactions. Legacy tools like SOURCES-4C remain widely used despite significant limitations, including outdated nuclear data, missing target nuclides, and restricted accessibility. Here, we present ALPHANSO, an open-source Python package for calculating (α, n) neutron source terms. ALPHANSO incorporates modern nuclear data libraries and formats covering all naturally occurring target nuclides and provides a transparent, modular framework for updating or extending the data as new evaluations are released. Comparison with an updated version of SOURCES-4A, NeuCBOT, and experimental measurements across a range of elements and materials shows that ALPHANSO reproduces neutron yields and spectra in good agreement with experimental data and state-of-the-art (α, n) calculations. These results demonstrate that ALPHANSO is a reliable, accessible, and modern alternative to legacy (α, n) source term codes such as SOURCES-4C. Its open-source design and modular data handling make it readily extensible to future evaluated nuclear data and low-background applications.

(α, n) reactions↗

DOE OSTI2015

Status of the Majorana Demonstrator

The Majorana Collaboration is constructing the Majorana Demonstrator, an ultra-low background, 40-kg modular high purity Ge detector array to search for neutrinoless double-beta decay in 76 Ge. In view of the next generation of tonne-scale Ge-based neutrinoless double-beta decay searches that will probe the neutrino mass scale in the inverted-hierarchy region, a major goal of the Demonstrator is to demonstrate a path forward to achieving a background rate at or below 1 count/tonne/year in the 4 keV region of interest around the Q-value at 2039 keV. Lastly, the current status of the Demonstrator is discussed, as are plans for its completion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

The MAJORANA DEMONSTRATOR for 0νββ: Current Status and Future Plans

The Majorana Demonstrator will search for neutrinoless-double-beta decay in 76Ge, while establishing the feasibility of a future tonne-scale germanium-based neutrinoless-double-beta decay experiment, and performing searches for new physics beyond the Standard Model. The experiment, currently under construction at the Sanford Underground Research Facility in Lead, SD, will consist of a pair of modular high-purity germanium detector arrays housed inside of a compact copper, lead, and polyethylene shield. Through a combination of strict materials qualifications and assay, low-background design, and powerful background rejection techniques, the Demonstrator aims to achieve a background rate in the neutrinoless-double-beta decay region of interest (ROI) of no more than 3cnts/(ROI-t-y). The current status of the Demonstrator is discussed, as are plans for its completion.

Green, M. P.↗

DOE OSTI2014

Theory and Implementation of Nuclear Safety System Codes - Part II: System Code Closure Relations, Validation, and Limitations

This is Part II of two articles describing the details of thermal-hydraulic sys- tem codes. In this second part of the article series, the system code closure relationships (used to model thermal and mechanical non-equilibrium and the coupling of the phases) for the governing equations are discussed and evaluated. These include several thermal and hydraulic models, such as heat transfer coefficients for various flow regimes, two phase pressure correlations, two phase friction correlations, drag coefficients and interfacial models be- tween the fields. These models are often developed from experimental data. The experiment conditions should be understood to evaluate the efficacy of the closure models. Code verification and validation, including Separate Effects Tests (SETs) and Integral effects tests (IETs) is also assessed. It can be shown from the assessments that the test cases cover a significant section of the system code capabilities, but some of the more advanced reactor designs will push the limits of validation for the codes. Lastly, the limitations of the codes are discussed by considering next generation power plants, such as Small Modular Reactors (SMRs), analyz- ing not only existing nuclear power plants, but also next generation nuclear power plants. The nuclear industry is developing new, innovative reactor designs, such as Small Modular Reactors (SMRs), High-Temperature Gas-cooled Reactors (HTGRs) and others. Sub-types of these reactor designs utilize pebbles, prismatic graphite moderators, helical steam generators, in- novative fuel types, and many other design features that may not be fully analyzed by current system codes. This second part completes the series on the comparison and evaluation of the selected reactor system codes by discussing the closure relations, val- idation and limitations. These two articles indicate areas where the models can be improved to adequately address issues with new reactor design and development.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. Finally, we anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A bimodular PKS platform that expands the biological design space

Traditionally engineered to produce novel bioactive molecules, Type I modular polyketide synthases (PKSs) could be engineered as a new biosynthetic platform for the production of de novo fuels, commodity chemicals, and specialty chemicals. Previously, our investigations manipulated the first module of the lipomycin PKS to produce short chain ketones, 3-hydroxy acids, and saturated, branched carboxylic acids. Building upon this work, we have expanded to multi-modular systems by engineering the first two modules of lipomycin to generate unnatural polyketides as potential biofuels and specialty chemicals in Streptomyces albus. First, we produce 20.6 mg/L of the ethyl ketone, 4,6 dimethylheptanone through a reductive loop exchange in LipPKS1 and a ketoreductase knockouts in LipPKS2. Furthermore, we then show that an AT swap in LipPKS1 and a reductive loop exchange in LipPKS2 can produce the potential fragrance 3-isopropyl-6-methyltetrahydropyranone. Highlighting the challenge of maintaining product fidelity, in both bimodular systems we observed side products from premature hydrolysis in the engineered first module and stalled dehydration in reductive loop exchanges. Collectively, our work expands the biological design space and moves the field closer to the production of "designer" biomolecules.

09 BIOMASS FUELS↗

DOE OSTI2019

A SQL to C compiler in 500 lines of code

Abstract We present the design and implementation of a SQL query processor that outperforms existing database systems and is written in just about 500 lines of Scala code – a convincing case study that high-level functional programming can handily beat C for systems-level programming where the last drop of performance matters. The key enabler is a shift in perspective toward generative programming. The core of the query engine is an interpreter for relational-algebra operations, written in Scala. Using the open-source lightweight modular staging framework, we turn this interpreter into a query compiler with very low effort. To do so, we capitalize on an old and widely known result from partial evaluation: the first Futamura projection, which states that a process that can specialize an interpreter to any given input program is equivalent to a compiler. In this context, we discuss lightweight modular staging programming patterns such as mixed-stage data structures (e.g., data records with static schema and dynamic field components) and techniques to generate low-level C code, including specialized data structures and data loading primitives.

Computer Science↗