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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Efficient anharmonic vibrational spectroscopy for large molecules using local-mode coordinates

This article presents a general computational approach for efficient simulations of anharmonic vibrational spectra in chemical systems. An automated local-mode vibrational approach is presented, which borrows techniques from localized molecular orbitals in electronic structure theory. This approach generates spatially localized vibrational modes, in contrast to the delocalization exhibited by canonical normal modes. The method is rigorously tested across a series of chemical systems, ranging from small molecules to large water clusters and a protonated dipeptide. It is interfaced with exact, grid-based approaches, as well as vibrational self-consistent field methods. Most significantly, this new set of reference coordinates exhibits a well-behaved spatial decay of mode couplings, which allows for a systematic, a priori truncation of mode couplings and increased computational efficiency. Convergence can typically be reached by including modes within only about 4 Å. The local nature of this truncation suggests particular promise for the ab initio simulation of anharmonic vibrational motion in large systems, where connection to experimental spectra is currently most challenging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Recent advances in stellarator optimization

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—was written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Compiler-Directed File Layout Optimization for Hierarchical Storage Systems

File layout of array data is a critical factor that effects the behavior of storage caches, and has so far taken not much attention in the context of hierarchical storage systems. The main contribution of this paper is a compiler-driven file layout optimization scheme for hierarchical storage caches. This approach, fully automated within an optimizing compiler, analyzes a multi-threaded application code and determines a file layout for each disk-resident array referenced by the code, such that the performance of the target storage cache hierarchy is maximized. We tested our approach using 16 I/O intensive application programs and compared its performance against two previously proposed approaches under different cache space management schemes. Our experimental results show that the proposed approach improves the execution time of these parallel applications by 23.7% on average.

Ding, Wei↗
DOE OSTI2021

Industry Level Integrated Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

The software Fire Risk Investigation in 3D (FRI3D) has been developed over the last 2 years to integrate 3D spatial modeling with existing fire probabilistic risk assessment (PRA) models and fire simulation codes. The goal of this research and development is to automate many of the fire analysis manual tasks to reduce industry efforts in the initial fire modeling and operational costs for the model maintenance and evaluations required during normal plant operations. The tasks for Fiscal Year (FY) 2021 include first testing the FRI3D modeling capabilities by importing an industry fire model into FRI3D and making a 3D model of a complex/high-risk significant area. (For this work, the switchgear room was chosen.) Then, the second task of FY 2021 is to develop a dynamic fire PRA process that can help optimize traditional fire PRA models. The switchgear room model will be used for the dynamic fire PRA work. This report describes the work and insights learned when using FRI3D software to model both a Nuclear Regulatory Report (NUREG) example models and a full industry switchgear room.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Deployment of Advanced Electroanalytical Sensors in the Kairos Power Engineering Test Unit (ETU) (Final CRADA Report)

This document serves as a summary report for the work conducted under CRADA 2022-22119 between Argonne National Laboratory and Kairos Power LLC. As part of this project, Argonne and Kairos worked to develop an advanced electrochemical system and testing protocol for the Kairos Power Enineering Test Unit (ETU), an industrial scale 14 ton molten FLiBe salt system. The main goals were (1) measurements of fundamental properties for key salt species, (2) the deployment and operations of sensors in the ETU, and (3) the development of automated approaches to analyze the measurements.

42 ENGINEERING↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Implementation of data citations and persistent identifiers at the ORNL DAAC

A requirement of data archives is that data holdings can be easily discovered, accessed, and used. One approach to improving data discovery and access is through data citations coupled with Digital Object Identifiers (DOI). The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) since 1998 has issued data citations that have been accepted and used in peer-reviewed journals. Citation elements established by the ORNL DAAC are similar to those used for journal articles (authors, year, product title, and information to locate), and beginning in 2007 included a DOI that is persistent, actionable, specific, and complete. The approach used at the ORNL DAAC also allows for referring to subsets of the data, by including within the citation the temporal and spatial extent, and parameters used. Data citations allow readers to find data and reproduce the results of the research article, and also use those data to test new hypotheses, design new sample collections, or construct or evaluate models. The ORNL DAAC uses a manual method to compile data citations and has developed a database that links research articles and their use of specific ORNL DAAC data products. Automation of the data citation compilation process, as is the case for articles, will enable data citations to become a more common practice. In addition to enhancing discovery and access of the data used in a research article, the citation gives credit to data generators, data centers and their funders, and, through citation indices, determine the scientific impact of a data set.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Electron cyclotron resonance (ECR) magnetometry with a plasma reservoir

The local magnetic field in a Penning–Malmberg trap is found by measuring the temperatures that result when electron plasmas are illuminated by microwave pulses. Multiple heating resonances are observed as the pulse frequencies are swept. The many resonances are due to electron bounce and plasma rotation sidebands. The heating peak corresponding to the cyclotron frequency resonance is identified to determine the magnetic field. A new method for quickly preparing low density electron plasmas for destructive temperature measurements enables a rapid and automated scan of microwave frequencies. This technique can determine the magnetic field to high precision, obtaining an absolute accuracy better than 1 ppm and a relative precision of 26 ppb. One important application is in situ magnetometry for antihydrogen-based tests of charge-parity-time symmetry and of the weak equivalence principle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Invited: Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications

This paper presents the open-source High-Level Synthesis research framework Bambu. The framework provides an open-source starting point to experiment with new ideas across High-Level Synthesis, high-level verification and debugging, FPGA/ASIC design, design flow space exploration, and parallel hardware accelerator design. The tool accepts as input standard C/C++ specifications and compiler intermediate representations (IRs) coming from the well-known Clang/LLVM and GCC com- pilers. The broad spectrum and flexibility of input formats allow the electronic design automation (EDA) research community to explore and integrate new transformations and optimizations. The easily extendable modular framework already includes many op- timizations and HLS benchmarks. The integration with synthesis and verification backends (commercial and open-source) allows researchers to quickly test any new finding and easily obtain performance and resource usage metrics for a given application. Different FPGA devices are supported from several different vendors: AMD/XILINX, Intel/Altera, Lattice Semiconductor, and NanoXplore. Finally, integration with the OpenRoad open-source end-to-end silicon compiler perfectly fits with the recent push towards open-source EDA.

Ferrandi, Fabrizio↗
DOE OSTI2014

Expression of a Humanized Viral 2A-Mediated lux Operon Efficiently Generates Autonomous Bioluminescence in Human Cells

Expression of autonomous bioluminescence from human cells was previously reported to be impossible, suggesting that all bioluminescent-based mammalian reporter systems must therefore require application of a potentially influential chemical substrate. While this was disproven when the bacterial luciferase (lux) cassette was demonstrated to function in a human cell, its expression required multiple genetic constructs, was functional in only a single cell type, and generated a significantly reduced signal compared to substrate-requiring systems. Here we investigate the use of a humanized, viral 2A-linked lux genetic architecture for the efficient introduction of an autobioluminescent phenotype across a variety of human cell lines. The lux cassette was codon optimized and assembled into a synthetic human expression operon using viral 2A elements as linker regions. Human kidney, breast cancer, and colorectal cancer cell lines were both transiently and stably transfected with the humanized operon and the resulting autobioluminescent phenotype was evaluated using common imaging instrumentation. Autobioluminescent cells were screened for cytotoxic effects resulting from lux expression and their utility as bioreporters was evaluated through the demonstration of repeated monitoring of single populations over a prolonged period using both a modified E-SCREEN assay for estrogen detection and a classical cytotoxic compound detection assay for the antibiotic Zeocin. Furthermore, the use of self-directed bioluminescent initiation in response to target detection was assessed to determine its amenability towards deployment as fully autonomous sensors. In all cases, bioluminescent measurements were supported with traditional genetic and transcriptomic evaluations. Our results demonstrate that the viral 2A-linked, humanized lux genetic architecture successfully produced autobioluminescent phenotypes in all cell lines tested without the induction of cytotoxicity. This autobioluminescent phenotype allowed for repeated interrogation of populations and self-directed control of bioluminescent activation with detection limits and EC 50 values similar to traditional reporter systems, making the autobioluminescent cells amenable to automated monitoring and significantly reducing the time and cost required to perform bioluminescent workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Introduction to Special Section: Machine Learning for Image-based Geologic Interpretation

Image-based geological interpretation has been a labor-intensive and time-consuming process because it requires well-trained geoscientists to identify geological structures, features, and textures from various types of images. These images include scanning electron microscopic images, optical microscopic images, optical photos, resistivity images, seismic volumes, remote-sensing images, etc. With fast-evolving machine learning (ML) technology and computing power in recent decades, computers can achieve nearhuman-level to super-human-level performance with scalable high efficiency in the computer vision field. These technological revolutions facilitated image-based geological interpretation in petroleum exploration and production. For example, a fault picking method applied to 3-D seismic volume data using deep learning can achieve superior performance in comparison to conventional auto-picking methods. In addition, under the new normal of low oil prices, the petroleum industry seeks cost-effective strategies such as automating traditionally labor-intensive processes. Nevertheless, the potential of applying ML to geological image interpretation is still facing a few key challenges including data scarcity, data distribution, poor data and/or label quality, data leakage, learning algorithms, model architecture, training methodologies, testing and evaluation metrics, hyper-parameters optimization, model drift, production deployment, and the like.

58 GEOSCIENCES↗
DOE OSTI2023

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

PVDeg: Enhancing Usability and AI-Driven Multi-Mechanism Degradation Modeling

PVDeg version 0.7.0, released in December 2025, introduced major enhancements to improve usability and performance. This update reorganized tutorials and tool notebooks to create a more intuitive experience, enabling users to easily follow and adapt workflows for their specific analyses. In addition to structural improvements, both the notebooks and core logic underwent significant optimization for efficiency, robustness, and style. These refinements were supported by new testing frameworks built on nbval and pytest, adherence to PEP8 standards, and extensive code refactoring, which collectively simplify onboarding for new developers. Looking ahead, version 0.8.0 will deliver advanced AI-driven capabilities. The primary focus is to further develop and automate the degradation workflow, designed to analyze PV module degradation across diverse locations and system configurations. By integrating large language models (LLMs) to scan literature and compile a comprehensive database of materials and degradation rates, this feature will enable modeling of multiple materials and mechanisms within a single, streamlined workflow. Users will be able to evaluate degradation impacts on different system architectures under varying environmental conditions, facilitating informed decisions on bill-of-materials optimization for specific deployment scenarios. These advancements position PVDeg as a powerful, user-friendly tool for accelerating PV reliability research and system design.

14 SOLAR ENERGY↗
DOE OSTI2018

Beyond Widgets: Validated Systems Energy Savings and Utility Custom Incentive Program Systems Trends

Energy efficiency upgrades to buildings to date through avenues such as utility incentive programs have been largely limited to component-based products (e.g., lamps, RTUs). While some utilities do provide ‘custom’ incentive programs with whole building and system level technical assistance, these programs require deeper levels of analysis, resulting in higher program costs. This results in custom programs being restricted to utilities with greater resources, and are typically applied mainly to large or energy-intensive facilities, leaving much of the market without cost effective access and incentives for these solutions. In addition, with increasingly stringent energy codes, cost effective component-based solutions that achieve significant savings are dwindling. Integrated building systems (e.g., integrated façade, HVAC and/or lighting solutions) can deliver higher savings (Regnier et al. 2017) that translate into large sector-wide savings if deployed at the scale of these programs. However, systems application poses a number of challenges – energy savings assessments are inherently more complex and are not easily suited to the deemed measure model, and implementation of systems can be more disruptive. This paper presents the outcomes of a project to develop validated utility incentive program packages for three specific integrated building systems, in collaboration with ComEd, a consortium of California Public Owned Utilities (CA POUs) (Northern California Power Agency(NCPA) and the Southern California Public Power Authority(SCPPA)), and Xcel Energy (CO, MN). Previous work described the potential for energy savings of these systems at the individual and market level, early test findings for the task-ambient lighting system, and described the work products to develop utility incentive programs (Regnier et al. 2016). This paper presents validated end use energy savings of all three systems showing energy savings of ~20% for automated shading combined with daylight dimming (does not include light fixture retrofit savings); 30-46% for task-ambient lighting systems combined with plug load occupancy controls, depending on technology package and office building size (no daylight dimming impacts); and ~94% in the south-façade daylit zone for workstation specific lighting systems with daylight dimming (including lighting retrofit and task tuning). Using a U.S. Department of Energy (DOE) reference building model (DOE 2018), this translates to whole building savings of 2-5% (large-medium commercial), 12-23% (large-small commercial), and 13-15% (medium-large commercial) for these systems respectively. Early findings from the utilities in deploying these systems through their incentive programs indicate that deployment methods such as direct install programs might be best suited for these integrated systems. Further, early findings from a scoping study across custom utility programs and federal retrofit programs indicate that component level retrofits are still prevalent even in these programs, pointing towards an opportunity for deeper energy savings deployment. High performance retrofit case studies demonstrate that deeper energy savings is possible through integrated approaches. Market stakeholder interviews indicate however that there is generally a low level of awareness of the potential for energy savings of these three integrated systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

The electric current effect on electrochemical deconsolidation of spherical fuel elements - 18447

For High-Temperature Gas-cooled Reactor in China, fuel particles are bonded into spherical fuel elements by a carbonaceous matrix. In conjunction with the development of a system to determine fuel failure fractions through {gamma}-analysis of individual and undamaged fuel particles, an automated electrochemical deconsolidation apparatus was developed in this study to separate the particles from the carbonaceous matrix by disintegrating the matrix into fine graphite powder, based on the anodic oxidation of graphite in an electrolyte containing nitric acid. A series of tests were conducted under a range of deconsolidation conditions to develop procedures and refine the equipment. The easy-handle un-irradiated spherical fuel elements were used as samples for initial tests. It is found that the morphology, size, and element content of deconsolidated graphite matrix and free particles were notably affected by electric current intensity. During the electrolysis, the nitric acid electrolyte gradually infiltrated into the micropores of graphite matrix, and the electrochemical reaction would take place around micropore structure as well as matrix surface. With much higher surface reaction capability due to the large specific area of micropore structure, the expansion stress originated from inner surface of micropores widened the c-spacing of the layer lattice of carbonaceous matrix, which was thought to be one of the main driving force of deconsolidation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan

It has been shown that shared automated electric vehicles (SAEVs) hold great promise for improving transportation access in urban centers while drastically reducing transportation-related energy consumption and air pollution. Using taxi-trip data from New York City, we develop an agent-based model to predict the battery range and charging infrastructure requirements of a fleet of SAEVs operating on Manhattan Island. We also develop a model to estimate the cost and environmental impact of providing service and perform extensive sensitivity analysis to test the robustness of our predictions. We estimate that costs will be lowest with a battery range of 50-90 mi, with either 66 chargers per square mile, rated at 11 kW or 44 chargers per square mile, rated at 22 kW. We estimate that the cost of service provided by such an SAEV fleet will be $0.29-$0.61 per revenue mile, an order of magnitude lower than the cost of service of present-day Manhattan taxis and $0.05-$0.08/mi lower than that of an automated fleet composed of any currently available hybrid or internal combustion engine vehicle (ICEV). We estimate that such an SAEV fleet drawing power from the current NYC power grid would reduce GHG emissions by 73% and energy consumption by 58% compared to an automated fleet of ICEVs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Engineering Scale Testing of Robotic Inspection Tools for Double Shell Tanks at Hanford - 18349

Waste found in the annulus of the AY-102 double-shell tank (DST) at Hanford has prompted the need for the development of inspection tools that are able to access confined spaces around and underneath the tanks. During the last year, Florida International University (FIU) has been developing inspection tools that are capable of accessing the tank floors through the air supply line, the air refractory channels and the drain lines. This effort has led to the development of a pneumatic pipe crawler and a miniature rover. In this paper, updates to the inspection tool designs and the full scale testing of both systems are presented. The tools provide visual feedback for the operator, carrying with them onboard cameras and light sources. The images are streamed back live via a tether, which also provides power to the devices. To increase the sensing capabilities of both tools, temperature, humidity and radiation sensor modules are being integrated onto the developed systems, and can be interchanged depending on the inspection objectives. The miniature rover measures 7 cm in length and 3.8 cm in width, and travels upside down on the bottom of the tank to avoid debris accumulated in the channels. The video is also being processed real-time to provide control of the unit semi-autonomously. The pipe crawler measures approximately 76 cm in length and 6.4 cm in diameter, and travels using pneumatic actuators that emulate the peristaltic movement contractions typical of worm type robots. A full-scale sectional mock-up of the DST foundation, refractory system and annulus is currently being developed as a test-bed for the testing of the inspection tools. The intention of the test-bed is to demonstrate the viability of using both inspection tools in configurations similar to the actual tank. The test-bed includes a 2.43 m wide section of both tank liners, refractory channels and concrete foundation with drain slots. The test-bed is designed to be modular so that various plate thicknesses can be easily utilized and different refractory configurations can be incorporated. Currently, the refractory channels are of the tree type structure with turns that are approximately 30 degrees. Both inspection tools were demonstrated in the mock-up facility. The miniature rover ran successfully through the drain slots from the annulus to central plenum and had no issues making the 90-degree turns. The peristaltic crawler was able to navigate through the 7.62 cm air supply line from the annulus to the central plenum. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

In Silico Guidance for In Vitro Androgen and Glucocorticoid Receptor ToxCast Assays

Molecular initiating events (MIEs) are key events in adverse outcome pathways (AOPs) that link molecular chemistry to target biology. As they are based in chemistry, these interactions are excellent targets for computational chemistry approaches to in silico modelling. In this work, we aim to link ligand chemical structure to MIEs for androgen receptor (AR) and glucocorticoid receptor (GR) binding using ToxCast data. This has been done using an automated computational algorithm to perform maximal common substructure searches on chemical binders for each target from the ToxCast dataset. The models developed show a high level of accuracy, correctly assigning 87.20% of AR binders and 96.81% of GR binders in a 25% test set using holdout cross-validation. The 2D structural alerts developed can be used as in silico models to predict these MIEs, and as guidance for in vitro ToxCast assays to confirm hits. These models can target such experimental work, reducing the number of assays to be performed to gain required toxicological insight. Development of these models has also allowed some structural alerts to be identified as predictors for agonist or antagonist behavior at the receptor target. This work represents a first step in using computational methods to guide and target experimental approaches.

Allen, Timothy H.↗