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DOE OSTI2026

SetGo: Metadata Readiness for Scientific AI Datasets

Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse. The Readiness Engine for Data Integration (REDI) addresses computational readiness, but no corresponding tool evaluates whether a dataset’s metadata are sufficiently complete, governed, and standards-compliant for publication and agent-based consumption. Existing FAIR assessors operate only on published repository records, and no single system covers FAIR compliance, licensing, provenance, governance, reproducibility, and catalog readiness together. We present SetGo, an open-source Python toolkit that assesses and repairs metadata readiness across these six dimensions before a dataset is published or archived. Applied to four scientific corpora, SetGo surfaces deficiencies that general-purpose tools do not detect: ERA5 climate metadata scores 4% on ACDD 1.3 compliance; materials datasets fail OPTIMADE species-definition requirements; and PDB-derived proteomics data carries licensing terms incompatible with standard SPDX identifiers. Guided enrichment raises overall FAIR scores from 52–57% to 81–91%, and a single setgo publish command pushes to Hugging Face Hub, CKAN, or OpenMetadata with ML Commons Croissant 1.0 metadata sidecars. To support interactive and automated workflows, SetGo integrates with coding agents powered by large language models (LLMs) through a /setgo skill that enables natural-language execution of the full assess–enrich–publish loop, with user involvement limited to supplying missing metadata values.

Wilkinson, Sean [ORNL] (ORCID:0000000214437479)↗
DOE OSTI2021

Structural Polymorphism of Chitin and Chitosan in Fungal Cell Walls From Solid-State NMR and Principal Component Analysis

Chitin is a major carbohydrate component of the fungal cell wall and a promising target for novel antifungal agents. However, it is technically challenging to characterize the structure of this polymer in native cell walls. Here, we recorded and compared 13 C chemical shifts of chitin using isotopically enriched cells of six Aspergillus, Rhizopus, and Candida strains, with data interpretation assisted by principal component analysis (PCA) and linear discriminant analysis (LDA) methods. The structure of chitin is found to be intrinsically heterogeneous, with peak multiplicity detected in each sample and distinct fingerprints observed across fungal species. Fungal chitin exhibits partial similarity to the model structures of α- and γ-allomorphs; therefore, chitin structure is not significantly affected by interactions with other cell wall components. Addition of antifungal drugs and salts did not significantly perturb the chemical shifts, revealing the structural resistance of chitin to external stress. In addition, the structure of the deacetylated form, chitosan, was found to resemble a relaxed two-fold helix conformation. This study provides high-resolution information on the structure of chitin and chitosan in their cellular contexts. The method is applicable to the analysis of other complex carbohydrates and polymer composites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Critical Minerals and Rare Earth Elements in Powder River Basin Coal and Associated Sediments, Wyoming, USA

The demand for Rare Earth Elements (REE) and other critical minerals (CM) required for consumer products, defense-related applications, and low-carbon energy technology is increasing rapidly. Unconventional sources of REE/CM, such as coal and associated sediments, could prove very important in building resilient and ethical energy supply chains. Utilization of existing infrastructure and the highly trained energy workforce in traditionally coal-producing regions in emerging REE/CM industries could provide an economic boost to coal communities. The Powder River Basin (PRB) of Wyoming and Montana, USA, is a prime candidate to investigate the feasibility of extracting REE/CM from coal and associated sediments. The PRB hosts thick (>50 ft) coal seams that are mined at the surface and more than 40% of the coal produced in the US comes from the PRB. Geochemical data from multiple locations in PRB coal systems show REE enrichments at the top and bottom margins and at internal partings in coal seams. This trend is exhibited in two cores drilled at Peabody’s North Antelope Rochelle mine in the east central PRB, the largest coal mine in the world. The two cores include the Wyodak Anderson coal zone as well as the over- and underlying shale units. The Wyodak Anderson coal zone is part of the Paleocene Tongue River Member of the Fort Union Formation in which most of the coal resources in the PRB reside. To understand REE/CM enrichment, a total of 188 samples were analyzed for their major and trace element chemistry from both cores, sampled at one foot or smaller intervals. The two cores show distinct REE enrichments in the uppermost and lowermost 3 to 12 feet of the Wyodak Anderson coal zone, as well as enrichments in bounding carbonaceous shale units. Total REE+Y (REY) concentrations as high as 2510 ppm (all concentrations reported on an ash basis), or 15 times average upper continental crust values (Taylor and McLennan, 1995), were identified in the coal. Partings within the coal zone also show relative REE enrichment, with concentrations up to 485 ppm REY. The remaining interior portions of the coal zone contain lower concentrations of REE, resulting in an average REY for all samples from both cores of 288 ppm. The proportion of high-value critical REE (Nd, Eu, Tb, Dy, Er, Y) compared to REY averages 36%, which is higher than the critical REE proportion in average upper continental crust of 33%. This finding highlights the relative enrichment of middle REE compared to light REE, in contrast to many conventional REE deposits. Other critical trace elements that show enrichments above average upper continental crust include Ga, Nb, and V. Within this sample suite, Ga concentrations range from 2.8 to 213 ppm, with an average of 29 ppm; Nb from 2.9 to 166 ppm with an average of 26 ppm; and V from 27 to 1695 ppm with an average of 188 ppm. None of these trace elements exhibit the same distinct pattern of enrichment as REE in the upper and lower bounding layers and internal partings of the coal zone. Major element chemistry indicates CaO concentrations averaging ~25% in the coal samples from both cores, which has important implications for the extractability of REE from coal. Calcium-rich PRB coal has been shown to be more amenable to REE extraction than lower calcium coals by some methods (Stuckman et al., 2019; Taggart et al., 2016), highlighting the importance of REE extractability in addition to REE concentration in assessing the value of potential feedstocks. The original coal resource in the PRB is estimated at 1.16 trillion short tons (Luppens et al., 2015). Thus, the PRB represents an important potential unconventional source for REE and other CM. Ongoing research to fully characterize the REE/CM resource, identify enrichment mechanisms, and further develop and scale extraction technologies is necessary to understand the full potential of this resource.

Phillips, Erin↗
DOE OSTI2023

A Multi-scale, Geo-data Science Method for Assessing Unconventional Critical Mineral Resources

Critical minerals (CM) supply raw materials that constitute many of our essential infrastructure, defense, technology, and electrification needs. Currently, production and refinement of these materials from conventional sources is limited to few regions globally, which makes supply of these resources particularly venerable to disruption. To help overcome these risks and meet growing demand, attention has focused on identifying and developing resource potential of unconventional geologic CM sources, such as rare-earth elements in sedimentary systems. However, the unconventional nature of these types of sources means they are often poorly characterized and/or under-explored with respect to conventional counterparts. We present a regional case study for an Unconventional Rare-earth and Critical minerals (URC) assessment method for predicting and identifying REE resource potential and occurrence in unconventional systems in the Central Appalachian Basin (CAB). The method utilizes a geologic and geospatial data-driven approach, informed and guided by knowledge of REE enrichment processes, to systematically predict and identify areas of higher enrichment. Results from the test case indicate locations with potential for different types of coal-REE deposits, demonstrating its utility for reducing the area of exploration and identifying sites for more detailed investigation. Building upon the regional scale assessment capability, ongoing science-based enhancements to the method will allow for finer-scale (e.g., mine-scale) predictions required to support technical and economic assessments.

Creason, Christopher↗
DOE OSTI2026

A path to intelligent watersheds: coordinating the data to decision pipeline

Operations of multi-reservoir systems are challenged in-part by the interplay of complex physical processes functioning within the watershed. The employment of intelligent systems can be of aid by linking environmental sensing, information technology, data analytics, simulation and decision support to achieve a data-to-decision flow of information. A further challenge is that watershed resources are managed for multiple purposes requiring some level of coordination among numerous resource managers, asset operators and users. System intelligence in this context relies on shared community platforms (data portals, community models), and coordinated communication between decision makers. Opportunities to enrich watershed intelligence has been the subject of a roadmapping exercise for the Department of Energy’s Water Power Technologies Office which has relied on broad stakeholder engagement. Initial phases of engagement involved personal interviews and a series of virtual group meetings, which focused on identifying opportunities to improve the intelligence of the physical infrastructure within our watersheds—examples of feedback include improved sensing of snowpack and runoff, data standards for facilitated data sharing, and better forecasting tools. The latter phase of engagement involved the conduct of a case study in the Upper Colorado River basin where key stakeholders were interviewed to map how their decisions are informed by intelligence from other basin stakeholders. Our presentation will highlight the interdisciplinary flow of information in complex watershed systems and identify physical and institutional opportunities toward the strategic operation of water infrastructure.

Colorado River↗
DOE OSTI2020

Prediction of condition-specific regulatory genes using machine learning

Recent advances in genomic technologies have generated data on large-scale protein–DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5–25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

The MUSIC Critical Benchmark and Nuclear Data

The Measurement of Uranium Subcritical and Critical (MUSIC) experiment was a series of measurements of critical and subcritical configurations of bare highly enriched uranium. The goal was to compare measurement methods, analysis techniques, and simulation methods across regimes of criticality and to provide high-quality validation of 235 U nuclear data. A benchmark evaluation of the two critical configurations of the MUSIC experiments will soon be published in the release of the International Criticality Safety Benchmark Evaluation Project Handbook. The recent execution of the experiment aids in proper quantification of model simplifications and all uncertainties associated with the experiment. Historical benchmark evaluations are heavily relied on for uranium nuclear data validation despite the fact that the same level of documentation and comparable uncertainty analysis may not be present. The MUSIC evaluation is less likely to include “unknown unknowns” that could impede accurately modeling the system. Presented are both highly detailed and very simplified models, which represent the experimental configurations accurately, aiding the users of the benchmark for nuclear data or transport code validation. The sensitivities of k eff to nuclear data and nuclear data–related uncertainties are very similar between this experiment and previous bare uranium sphere experiments. In addition, the nuclear data uncertainties to any nuclides other than 235 U are small. For all these reasons, the recently evaluated MUSIC benchmark critical configurations could prove very useful for 235 U nuclear data validation. Currently, major libraries have good agreement with the experimental results, within 200 pcm for all nuclear data libraries, and within one standard deviation of the experimental result for most. Suggested nuclear data adjustments based on MUSIC and Lady Godiva are also presented, with posterior improvements to both the agreement in k eff and the uncertainty associated with the nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Reactivity-initiated accidents in two pressurized water reactor high burnup core designs

Here, this paper presents a safety analysis of two proposed core loadings for 24-month Pressurized Water Reactor (PWR) fuel cycles. This analysis focuses on reactivity-initiated accidents (RIAs) and evaluates core safety performance impacts of rod-averaged burnup limits up to 75 GWD/MTU and less than 7 % enriched UO 2 . The capabilities of Polaris, PARCS, and RELAP5-3D are leveraged to evaluate the core neutronic and thermal–hydraulic behavior for normal-operation, uncontrolled control rod withdrawal (CRW) transients, and control rod ejection (CRE) accidents. The two core designs are compared to identify features of realistic high burnup/extended enrichment core design approaches which have significant safety impact, identify experimental data needs for high-fidelity predictive modeling, and provide recommendations for future high burnup core designs. The first core design evaluated in this study was developed by Southern Nuclear Company and used an ZrB 2 Integral Fuel Burnable Absorber (IFBA) and B 4 C Wet-Annular Burnable Absorber (WABA)-based burnable poison strategy. The second core design assessed in this work used a Gd 2 O 3 -doped UO 2 burnable poison, similar to that used in boiling water reactors or French PWRs. Results indicate that fuel thermal limits are maintained for limiting CRW and hot full power (HFP) CRE transients. Cladding failure is predicted for the highest energy deposition rods in each core during limiting hot zero power (HZP) CRE accidents (where maximum radially averaged enthalpy exceeds 120 cal/g), though licensing may be permissible with a limited number of failed rods. While concerns exist regarding high critical boron concentration during steady state for the IFBA core and large plenum pressures for the gadolinia core design, the analysis demonstrates adequate safety performance during limiting RIA accident scenarios for two representative high burnup core designs. Design changes limiting plenum pressures and implementation of accident tolerant fuel (ATF) cladding features which minimize hydriding and susceptibility to pellet-cladding mechanical interaction (PCMI) are recommended for future high burnup fuel concepts. To support the technical basis for burnup limit increases, high-fidelity fuel performance models are needed to address physical effects not considered in this analysis, and high burnup irradiated fuel tests are required to extend applicability of the fuel failure limits and validate existing and future models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

"Russians in the Grid" Enrichment Process

Threat intelligence sources are numerous, and the quality of their intelligence is equally variable. The need for quality, actionable, and shareable intelligence is becoming increasingly important as cyber-threats continue to increase. In this paper, we describe the process we used to enrich U.S. CERT’s Technical Alert entitled “Russian Government Cyber-Activity Targeting Energy and Other Critical Infrastructure Sectors,” affectionately referred to as “Russians In the Grid,” from a series of separate but related reports to a final, actionable, unified Structured Threat Information Expression (STIX) v2 representation of the report. In the process, we detail the tools and procedures we used, some of which are automated and others highly manual. We identify some of the limitations of current STIX enrichment tools and techniques, and propose enhancements to allow for more effective enrichment and better overall threat intelligence to be used for more effective threat data-sharing, as well as machine learning-based predictive threat work being conducted at Idaho National Laboratory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Depletion benchmark for a high-assay low-enriched uranium fuel experiment in the advanced test reactor

Reactor physics depletion benchmarks for high-assay low-enriched uranium (HALEU) fuel are limited in number. In particular, there is limited data for HALEU benchmarks for U-10Mo (uranium-10% molybdenum) plate fuel that is being developed for use in the United States’ high performance research reactors including the Advanced Test Reactor (ATR), Advanced Test Reactor Critical Facility (ATR-C), High Flux Isotope Reactor (HFIR), Massachusetts Institute of Technology Reactor (MITR), University of Missouri Research Reactor (MURR), National Bureau of Standards Reactor (NBSR). These six reactors currently operate with highly enriched uranium dispersed fuel in an aluminum matrix. In support of conversion to a HALEU fuel, qualification of U-10Mo formed into a monolithic foil is being performed. Fuel qualification involves irradiating fuel specimens in the ATR. The irradiation tests provide an opportunity to benchmark depletion capabilities of reactor physics codes in support of the ATR operation, as well as develop benchmarks that can be used by other institutions to benchmark other reactor physics codes. This paper documents the development of a benchmark model of the irradiation of the ATR Full-size plate In center flux trap Position 7 (AFIP-7) experiment using the depletion codes MC21 and Advanced Dimensional Depletion for Engineering of Reactors (ADDER).

Nielsen, Joseph W. [Idaho National Laboratory (INL↗
DOE OSTI2024

What Are Ontologies and When Should They Be Used?

Data without description is at best unusable, and at worst, misused. If we do not understand the assumptions and meaning of our data, we are unable to confidently use it. Data today is largely described within a database’s schema, detailing structure and primitive datatypes as part of a relational model, but if we require assurance some data value can be correctly evaluated alongside others beyond the immediate systems in which they are defined, a more portable, richer semantics is needed. Ontologies define knowledge unambiguously across systems and establish the means to reason upon said knowledge using logical inference. They model neutral domains of information rather than data definitions from software or databases that would only serve to enrich a single system’s idiosyncrasies. In this paper, we take a casual stance to explore what ontologies are, how they are built, why they are useful, and when they should be used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Depletion Benchmark of the AFIP-7 Experiment in the Advanced Test Reactor

Reactor physics depletion benchmarks for low-enriched uranium fuel are limited in number. In particular, there is very limited data for LEU benchmarks for U-10Mo (Uranium-10% Molybdenum) plate fuel developed for use in U.S. high-performance research reactors (USHPRR). USHPRR includes the Advanced Test Reactor (ATR), Advanced Test Reactor Critical Facility (ATR-C), High Flux Isotope Reactor (HFIR), University of Missouri Research Reactor (MURR), Massachusetts Institute of Technology Reactor (MITR), and National Bureau of Standards Reactor (NBSR) at the National Institute of Science and Technology. These reactors are fueled with high-enriched uranium dispersed fuel in a silicon/aluminum matrix. In support of conversion to a HALEU fuel, qualification of U-10Mo formed into a monolithic foil is being performed. Fuel qualification involves irradiated fueled specimens in the ATR. The irradiation tests provide an opportunity to benchmark depletion capabilities of reactor physics codes in support of the ATR operation, as well as develop benchmarks that can be used by other institutions to benchmark other reactor physics codes. This report documents the development of a benchmark model of the irradiation of the ATR Full -size plate In center flux trap Position 7 (AFIP-7) experiment.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

(α,n) nuclear data scoping study

Neutrons from the (α,n) reaction are an important component of nondestructive assay techniques to determine enriched uranium and other actinide inventories in a variety of critical points in the nuclear fuel cycle. However, uncertainties in the cross section, total neutron yield and neutron spectrum, and gamma emissions from these reactions, such as 19 F(α,n) and 17,18 O(α,n), introduce large uncertainties in the determination of mass of actinides of interest and can represent several significant quantities in unaccounted material in certain facility processes. Calculations and measurements depend on accurate nuclear data; however, much of the relevant data in use today was measured in the 1980s and earlier and has not been updated. Thus, the current uncertainties in the cross sections and neutron emission spectra are unacceptably large. This report documents the results of a scoping study of (α,n) reaction data that considered the current state of the data and recommends areas of improvement. It also addresses the codes use to calculate the (α,n) neutron and gamma source terms and recommends code improvements to support required analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Processes in DNA damage response from a whole-cell multi-omics perspective

Technological advances have made it feasible to collect multi-condition multi-omic time courses of cellular response to perturbation, but the complexity of these datasets impedes discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we report a whole-cell mechanistic analysis of HL-60 cellular response to bendamustine. We integrate both enrichment and network analysis to show the progression of DNA damage and programmed cell death over time in molecular, pathway, and process-level detail using an interactive analysis framework for multi-omics data. Our framework, Mechanism of Action Generator Involving Network analysis (MAGINE), automates network construction and enrichment analysis across multiple samples and platforms, which can be integrated into our annotated gene-set network to combine the strengths of networks and ontology-driven analysis. Taken together, our work demonstrates how multi-omics integration can be used to explore signaling processes at various resolutions and demonstrates multi-pathway involvement beyond the canonical bendamustine mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Progress Update on the MUSIC Critical Benchmark

The Measurement of Uranium Subcritical and Critical (MUSiC) experiment was carried out from December 2020 through April 2021 at the National Criticality Experiments Research Center (NCERC). This measurement campaign featured bare configurations of the Rocky Flats highly-enriched uranium (HEU) shells, with each configuration having different numbers of these shells. The goal of the experiment was to test multiple neutron multiplicity detectors and measurement methods for a large range of neutron multiplication values. The large range of multiplications allows researchers to see when the combination of detectors and methods break down as the configurations reach the delayed supercritical window. The critical configurations were the extreme end of the multiplication range in MUSIC configurations. A critical benchmark in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook is planned to help further validate nuclear data. Even though there are many benchmarks focusing on the fast spectrum for highly-enriched uranium, an additional benchmark that is well documented and up to the modern standard of the handbook would be a welcome addition. Given that there are no other materials such as moderators or significant reflectors, and its similarity to Lady Godiva, it is possible that this could be very useful for validation of 235 U nuclear data in the future.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Reaching For New Physics With MeV-scale Reconstruction In The MicroBooNE LArTPC Neutrino Detector

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing MeV-Scale energy depositions, or blips, in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV scale using reconstructed blips in MicroBooNE LArTPC data at Fermilab. A concentration of low-energy ($<$3 MeV) blips is observed around fiberglass mechanical support struts along the TPC edges, with spectral features consistent with the Compton edge of the 2.614 MeV $^{208}$Tl decay $\gamma$ ray. With these features we perform the electron energy scale calibration to few-percent precision and yield the specific activity of $^{208}$Tl in the struts, $(11.7 \pm 0.2 \text{(stat)} \pm 2.8 \text{(syst)})$ Bq/kg. Using cosmogenic blips above 3 MeV, we demonstrate the ability of large LArTPCs to discriminate low-energy proton and electron depositions. An enriched low-energy proton sample selected with this technique is smaller in data than in dedicated CORSIKA simulations, pointing to possible mismodeling in CORSIKA incident cosmic fluxes or Geant4 particle transport. These methods are applied to MicroBooNE's inclusive single-photon search, which reported a 2.2$\sigma$ excess below 600 MeV in shower energy for events with no reconstructed protons. By identifying and classifying blips near single-photon events selected by the WireCell reconstruction framework, a more comprehensive labeling of nearby hadronic activity is established: blips upstream of the shower axis indicate previously unidentified final-state protons, while elevated blip counts at wide angles signal final-state neutrons. Taken together with MiniBooNE's long-standing low-energy excess (LEE) and MicroBooNE electron-like and sterile neutrino searches disfavored as possible explanations of the MiniBooNE anomaly, this analysis motivates an expanded exploration of the single-photon channel in Fermilab's short-baseline LArTPC program. This thesis documents the current status of this enhanced analysis, which will form a key part of MicroBooNE's final low-energy-excess results.

Andrade Aldana, Diego Armando [IIT, Chicago (main)↗
DOE OSTI2021

Automatic Search of Cataclysmic Variables Based on LightGBM in LAMOST-DR7

The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.

79 ASTRONOMY AND ASTROPHYSICS↗