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At least 19 records

Modern control system applications at Fermilab with Dart and Flutter

The control system at Fermilab is undergoing an unprecedented modernization effort. Hundreds of legacy applications originally developed with technology from the early nineties will be replaced with a suite of modern web applications. The selection of an user interface framework is a key technology decision that will impact on all the applications developed over the next decade. The Controls department at Fermilab has decided to use Google’s Dart language and Flutter framework for future application development. In this paper we will discuss the decision process that selected Dart/Flutter and the development of early general purpose control system applications with the framework.

Diamond, John [Fermilab]

PQML: Enabling the Predictive Reproducibility on NISQ Machines for Quantum ML Applications

Quantum computing represents a groundbreaking approach to high-performance computing. In recent years, quantum computers have progressed from single-qubit processors to systems boasting over 400 qubits. The presence of such a large number of qubits offers significant advantages, including enhanced computational speed—a capability beyond classical computing methods. However, the current stage of quantum computing is referred to as the noisy intermediate-scale quantum (NISQ) era. The existence of noise in this era presents challenges in testing quantum computing applications, leading to considerable variance in application results. Furthermore, the diverse noise characteristics observed across different machines exacerbate this issue, complicating the selection of the appropriate machine for application execution. In response to these challenges, we introduce our Predictive Quantum Machine Learning (PQML) tool. This tool is designed to predict outcomes when executing identical quantum machine learning applications—specifically, a critical suite of variational quantum algorithms—across various quantum computers during the NISQ era. This effort relies on data collected over a 12-month period. To the best of our knowledge, this study represents the first attempt to ensure reproducibility across quantum computers for complex circuits. Additionally, we have developed a model capable of forecasting the accuracy of quantum computers for variational quantum algorithms, with a particular emphasis on quantum machine learning as a case study.

Senapati, Priyabrata [Kent State University]

Application Potential of a Dew-Point Cooling Tower in Selected Energy Intensive Applications in Temperate Climate

In the article, the application potential of the dew-point cooling tower (DPCT) in selected energy-intensive applications in temperate climates was analyzed and discussed. The applications selected for analysis are power generation with natural gas turbines and chilled water air conditioning systems. The study is based on a mathematical model derived from a modified ε-NTU model. The model was validated against experimental results and showed satisfactory agreement with the experimental data. DPCT was compared with a typical cooling tower limited by the wet-bulb temperature (wet-bulb cooling tower, WBCT). The simulation results showed that DPCT is able to provide significant energy savings in energy-intensive applications; therefore, its application potential in temperate climates can be considered justified. In the case of gas turbines, DPCT was able to generate 2 to 10 percentage points more capacity than operating on outdoor air and 1.8 to 5 percentage points more than operating with WBCT. In the case of air conditioning systems, the system equipped with DPCT achieved EERs (energy efficiency ratios) higher by 1 to 7.2 compared to dry cooling and by 0.3 to 5.1 compared to systems equipped with WBCT. The annual energy savings obtained by the system with DPCT were 14.7 MWh compared to WBCT and 30 MWh compared to dry cooling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Influence of Pt-Metal Alloy Catalysts with Various Ionomers on Oxygen Reduction Reaction in Fuel Cell Application

Pt-M/C (M = Co, Ni, Mn, etc.) alloy catalysts exhibit superior oxygen reduction reaction (ORR) activity compared to pure Pt/C, leading to a high energy efficiency in hydrogen fuel cells. However, many Pt-M/C alloy catalysts were synthesized and evaluated at the lab scale in model test-bed systems like rotating disc electrodes, which don't always correlate to performance within a fuel cell system; there is a clear need to evaluate catalysts in electrodes that can be prepared at industrially relevant scales to evaluate how factors like ink formulation can greatly affect device-level of fuel cell performance. Herein, three commercial Pt-M/C alloy catalysts (two Pt-Co/C and one Pt-Ni/C) were comprehensively characterized by various techniques. The results show that the average particle sizes of the three catalysts are close to 5 nm; the atomic ratio of Pt/M is around 4; and the M was successfully embedded into Pt lattice, resulting in the positive shift of Pt 4f in XPS spectra and XRD patterns. These catalytic materials were incorporated into 9 different cathode catalyst layers (CCLs) with three kinds of ionomers (Nafion D2020, high oxygen permeability ionomer (HOPI), and Aquivion D79-25BS), and their performance in proton exchange membrane fuel cells (PEMFCs) were investigated. The results demonstrate that the Pt-Co/C catalysts possess a higher mass activity (MA) than Pt-Ni/C; the cathodes with Nafion ionomer provide the highest MA while electrodes with Aquivion ionomer showed the lowest activity, attributed to poor H+ conductivity resulting from suboptimal ionomer incorporation. Finally, these alloys were shown to exceed DOE targets for MA and H2/Air performance reported in the recent publications at beginning of life and after 90k cycle catalyst AST protocol. This study provides valuable performance benchmarks for these materials guiding future Pt-M/C catalyst design and material integration for heavy duty PEMFC applications.

08 HYDROGEN

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY

Power Electronic Development Challenges for High Power Density Integrated Electric Drive Applications

The ever-increasing demand for compact, efficient, and high-performance traction drive systems for transportation applications has accelerated the development of integrated electric drives. In these systems, the electric machine and inverter are integrated within a single housing, offering significant advantages in electrical performance, volume, weight, cost, and overall system efficiency. Despite these benefits, such high levels of integration introduce a new set of challenges, particularly in power electronic design and component selection. This article presents an in-depth investigation of a highly integrated electric drive architecture with an internal stator-mounted inverter, highlighting key design considerations and trade-offs aimed exclusively at maximizing system power density.Based on a comprehensive review of the literature, the power density of a voltage-source-inverter-driven electric drive is primarily governed by the volumetric contributions of the power modules, heat sinks, and DC-link capacitors. Accordingly, this work focuses on the optimization of these three critical components to enhance the inverter's overall power density. The proposed design achieves a power density of 100 kW/L, demonstrating the effectiveness of the presented approach for next-generation integrated electric drive systems.

33 ADVANCED PROPULSION SYSTEMS

Data for "Discovery, Characterization, and Application of Chromosomal Integration Sites in the Hyperthermophilic Archaeon Sulfolobus islandicus"

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

AI/ML

Study of Applications of Radiological Data Fusion for Nuclear Security and Non-proliferation Applications

This report describes the radiological Scene Data Fusion (SDF) technology and the potential to apply the SDF technology to a variety of problems related to nuclear non-proliferation, radiological security, and other missions related to the national nuclear security agency and the US government, more broadly. The application space was conceived by both the authors of this report and the many scientists and stakeholders they interviewed. In order to successfully apply the SDF technology to the various applications, further research and development is often necessary and those R&D steps are also outlined herein.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P

Evaluations for medium- and high-mass nuclei for FUSION applications

There is a renewed attention to nuclear fusion as a commercial source of carbon-free energy, however there are many scientific needs that must be addressed to enable the future success of fusion as an economical energy option. Among these is the proper description of the impact of radiation produced in the fusion vessel chamber and all other components of the reactor. In this work we will focus on the nuclear data needs to describe the interaction between primary and secondary neutron radiation and the medium- and high-mass nuclei commonly present in structural (such as stainless steel) and superconducting (e.g., electromagnets) materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

A Perspective on Quantum Computing Applications in Quantum Chemistry Using 25-100 Logical Qubits

The intersection of quantum computing and quantum chemistry represents a promising frontier for achieving quantum utility in domains of both scientific and societal relevance. Owing to the exponential growth of classical resource requirements for simulating quantum systems, quantum chemistry has long been recognized as a natural candidate for quantum computation. This perspective focuses on identifying scientifically meaningful use cases where early fault-tolerant quantum computers, which are considered to be equipped with approximately 25-100 logical qubits, could deliver tangible impact. While recent advances in classical computing have pushed the boundaries of tractable simulations to unprecedented scales, this logical-qubit regime represents the first window where quantum devices can pursue qualitatively distinct strategies, such as polynomial-scaling phase estimation, direct simulation of quantum dynamics, and active-space embedding, that remain challenging for classical solvers, such as multireference charge-transfer and conical-intersection states central to photochemistry and materials design. We highlight near-term opportunities in algorithm and software design, discuss representative chemical problems suited for quantum acceleration, and propose strategic roadmaps and collaborative pathways for advancing practical quantum utility in quantum chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

GPM IMERG V07B and V06B: Evaluation Using Ground-Based Radar Observations and Application in Global Mesoscale Convective System Tracking

This study evaluates the latest Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG V07B) against its predecessor V06B, for studying mesoscale convective systems (MCSs). Both versions are compared using ground-based radar and rain gauge data from five meteorologically diverse regions: the contiguous United States (including eastern coastlines), Amazon rainforest, central Argentina mountains, equatorial Indian Ocean, and northern Australia across multiple temporal (0.5–6 hours) and spatial scales (0.1°–0.25°). An updated global MCS tracking dataset is developed by integrating satellite-observed infrared brightness temperature with IMERG V07B. Comparation of IMERG against radar observations reveals that IMERG demonstrates better performance in capturing the probability distribution and quantitative contributions of rainfall (from no-rain to intense-rain conditions) over tropical oceans than over land, with marked improvements in IMERG V07B for heavy-to-intense rain (> 10 mm h-1). Over land, systematic biases persist: IMERG tends to overestimate light-to-moderate rain (1–10 mm h-1) while underestimating heavy-to-intense rain. Additionally, aggregating IMERG to coarser resolutions (3-hourly or 0.25°) improves consistency with radar observations, outperforming the 1-hourly/0.1° resolution. The new IMERG V07B-based global MCS dataset exhibits consistent statistical characteristics with the V06B-based dataset, despite lower mean rain rates and reduced heavy precipitation contributions. These findings offer valuable insights for utilizing IMERG V07B in global precipitation studies, MCS characterization, and model evaluation.

Zhang, Sihan

Application-level benchmarking of quantum computers using nonlocal game strategies

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise.

nonlocal games

Data for Rewiring Yeast Metabolism for Producing 2,3-Butanediol and Two Downstream Applications: Techno-Economic Analysis and Life Cycle Assessment of Methyl Ethyl Ketone (MEK) and Agricultural Biostimulant Production

Rising concerns for sustainability and global climate change have driven the development of sustainable production pathways for biofuels and chemicals from lignocellulosic biomass via integrated biological and chemical processes. We constructed an engineered Saccharomyces cerevisiae capable of producing 2,3-butanediol (2,3-BDO) from glucose without accumulating ethanol and glycerol, which hinder downstream processing of 2,3-BDO, through extensive metabolic reprogramming. Specifically, we introduced heterologous 2,3-BDO biosynthetic enzymes and deleted the major isozymes of ethanol and glycerol biosynthetic enzymes. In addition, we introduced an NAD+ regenerating Pyruvate-Malate (PM) cycle and enhanced the NAD+ regenerating capability of the PM cycle to resolve the redox imbalance from the deletion of ethanol and glycerol production pathways. The resulting engineered yeast produced 109.9 g/L of 2,3-BDO with a productivity of 1.0 g/L/h and a yield of 0.36 g/g glucose in a fed-batch fermentation. We also conducted techno-economic analysis (TEA) and life cycle assessment (LCA) of the production of methyl ethyl ketone (MEK) through catalytic dehydration of 2,3-BDO. A TEA based on the experimental results indicated that the minimum product selling price (MPSP) was estimated to be $1.90/kg. Regarding cradle-to-grave LCA, 100-year global warming potential (GWP100) and fossil energy consumption (FEC) were found to be 0.37 kg CO2 eq/kg and 3.1 MJ/kg, respectively. These results demonstrated the feasibility of cost-competitive and sustainable bio-based MEK production via yeast fermentation. In addition, we explored the possibility of using the fermentation broth containing 2,3-BDO as a biostimulant inducing drought tolerance in plants. As a result, the yeast 2,3-BDO fermentation broth can induce drought tolerance in Arabidopsis thaliana without a complicated purification process.

Economics

HydraGNN_OPF_GFM_2026 - Ensemble of predictive graph foundation models for power grid applications

This dataset supports research on graph foundation models for optimal power flow (OPF) on electric grids using HydraGNN. It contains heterogeneous graph representations of PGLib-OPF cases spanning systems from 14 to 13,659 buses, together with packed HDF5 datasets for pretraining, feasibility classification, and N-1 contingency analysis. The release includes OPF solution data, downstream fine-tuning datasets, pretrained HeteroSAGE and HeteroHEAT model checkpoints, hyperparameter-optimization summaries across multiple heterogeneous GNN architectures, and aggregated fine-tuning results for sample-efficiency studies. The dataset is designed to enable scalable training, evaluation, and transfer-learning studies for OPF surrogate modeling, including node-level AC-OPF solution prediction, graph-level prediction, feasibility classification, operating-condition generalization, and contingency-response tasks.

24 POWER TRANSMISSION AND DISTRIBUTION

Beyond Like-for-Like: A User-centered Approach to Modernizing Legacy Applications

When modernizing a legacy application, it is easy to fall back on a like-for-like replica with new tools and updated design stylings, but this is an opportunity to explore making a more intuitive application that supports user tasks and efficiency. Rather than having a blank canvas-unburdened by legacy tech debt-to create a new application, you are working with an existing application that is integral to accelerator operations and one that expert users are already familiar with. Due to this, you might assume people will prefer the like-for-like, but you could be carrying forward the pain points, processes that are inefficient, and ultimately wind up with an application that no one wants to use because it doesn't solve existing problems. Getting users involved can make all the difference in your approach to modernizing a legacy application that caters to both newer and expert users. It also can bridge the gap between like-for-like and introducing new GUI design. Having a legacy application doesn't have to make the modernized one difficult to develop, as the existing application is a tool in how you move forward with the new application. It provides insight into areas that an application with a clean slate doesn't give you.

Polzin, M. [Fermilab]

Refining HPCToolkit for application performance analysis at exascale

As part of the US Department of Energy’s Exascale Computing Project (ECP), Rice University has been refining its HPCToolkit performance tools to better support measurement and analysis of applications executing on exascale supercomputers. To efficiently collect performance measurements of GPU-accelerated applications, HPCToolkit employs novel non-blocking data structures to communicate performance measurements between tool threads and application threads. To attribute performance information in detail to source lines, loop nests, and inlined call chains, HPCToolkit performs parallel analysis of large CPU and GPU binaries involved in the execution of an exascale application to rapidly recover mappings between machine instructions and source code. To analyze terabytes of performance measurements gathered during executions at exascale, HPCToolkit employs distributed-memory parallelism, multithreading, sparse data structures, and out-of-core streaming analysis algorithms. To support interactive exploration of profiles up to terabytes in size, HPCToolkit’s hpcviewer graphical user interface uses out-of-core methods to visualize performance data. The result of these efforts is that HPCToolkit now supports collection, analysis, and presentation of profiles and traces of GPU-accelerated applications at exascale. These improvements have enabled HPCToolkit to efficiently measure, analyze and explore terabytes of performance data for executions using as many as 64K MPI ranks and 64K GPU tiles on ORNL’s Frontier supercomputer. HPCToolkit’s support for measurement and analysis of GPU-accelerated applications has been employed to study a collection of open-science applications developed as part of ECP. This paper reports on these experiences, which provided insight into opportunities for tuning applications, strengths and weaknesses of HPCToolkit itself, as well as unexpected behaviors in executions at exascale.

Adhianto, Laksono