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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Approach to qualification using E-PBF in-situ process monitoring in Ti-6Al-4V

Traditional design and qualification methodologies for parts manufactured by traditional methods are being applied to Additive Manufacturing (AM) without understanding the nuances of the machines. While mapping process variables and tracking build data is helpful, some variables such as build geometry, support structure, and part melt order have not been researched in depth. Changing these variables can result in significant variations in material properties and defect structure such that the process appears to be unreliable compared to traditional manufacturing. Hence, this research focuses on the need to understand the effects of overlooked variables such as melt order and nested geometry on the distribution of defects and bulk material properties in Ti-6Al-4 V alloy builds manufactured using the Arcam AB ® electron beam powder bed fusion process 1 . This work collected and analyzed process log data and near infrared (NIR) images for every layer to correlate trends in porosity formation and mechanical performance. The location of pores, while naturally stochastic, is greatly influenced by the cross-sectional area as detected by NIR images and correlates with the failure sites from uniaxial testing.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Constitutive Behavior and Hot Workability of a Hot Isostatic Pressed Ti-22Al-25Nb Alloy during Hot Compression

A Ti-22Al-25Nb alloy was fabricated from prealloyed powders by hot isostatic pressing for 2 h at a temperature of 1050 °C and pressure of 100 MPa. The hot deformation behavior of the Ti-22Al-25Nb alloy was characterized by isothermal compression testing at deformation temperatures between 900 and 1060 °C and strain rates between 0.001 and 1 s{sup −1}. Based on the true stress–strain curves, a constitutive equation was constructed to describe the flow stress as a function of the strain rate and deformation temperature. Three-dimensional (3D) processing maps were developed based on dynamic material model theory using the stress flow data to identify the instability and optimization regions of the hot processing parameters. The results show that the flow stress decreases with increasing deformation temperature and decreasing strain rate, and the softening mechanisms are different under different deformation conditions. The apparent activation energies in the (α{sub 2} + β/B2 + O) and (α{sub 2} + B2) phase regions are calculated to be 865.177 and 590.661 kJ/mol, respectively, which suggests that the hot isostatic pressed (HIPed) Ti-22Al-25Nb alloy requires a high hot deformation activation energy. Combined with microstructural observations, the optimal processing domains are determined to be a temperature range of 1030-1060 °C and strain rate range of 0.01-0.1 s{sup −1} in the α{sub 2} + B2 phase region. Moreover, the results indicate that adiabatic shear bands and severe inhomogeneous deformation cause flow instability at lower temperatures (900-1005 °C) and higher strain rates (> 0.1 s{sup −1}).

36 MATERIALS SCIENCE↗
DOE OSTI2019

Study on Tensile Deformation Behavior of TC21 Titanium Alloy

To investigate the tensile deformation behavior of TC21 titanium alloy wires, the isothermal tensile deformation tests were conducted by a Geeble-1500D simulator in the temperature range of 720-880 °C and strain rates of 0.01-10 s{sup −1}. The in situ tensile deformation behavior has been studied by SEM SURPA40. The stress–strain curves indicate that the flow stress has shown an inverse relationship with temperature and a direct relationship with strain rate. The flow stress immediately reached the peak value and, then, gradually decreased due to the dynamic softening induced by dynamic recovery and dynamic recrystallization. According to the hot processing maps, the temperatures ranging from 720 to 760 °C (corresponding to the strain rates of 0.01-0.032 s{sup −1}) and 800-840 °C (corresponding to the strain rates of 0.01-0.056 s{sup −1}) are suitable for processing. The in situ tensile results reveal that the cracks initiated at the pre-fabricated defects with the concentrated stress and mainly propagated in the transgranular mode.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2022

Process window estimation in manufacturing through Entropy-Sigma active learning

In manufacturing, there exist boundary identification problems for defining parameter spaces that meet desired thresholds on outcomes. This paper presents an Entropy-Sigma acquisition function for active learning of the process window/map in manufacturing using a Gaussian Process surrogate. Here, the method is applied to identify the stability boundary for the stability process map in machining using time-domain simulations with a periodic sampling stability metric. Results show that the proposed Entropy-Sigma method significantly outperforms Latin hypercube sampling or grid-based methods. The described method can be applied to identify the process window/map for any manufacturing application using a quantitative process outcome metric.

42 ENGINEERING↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
DOE OSTI2019

Small Modular Reactors in Canada: Planning for Waste from the Outset - 19254

Canada is exploring the potential for on- and off-grid applications for small modular reactors (SMRs). SMRs are at an early stage of development and a road-mapping process was launched in Canada in February 2018 to better understand the views on priorities and challenges related to the possible development and deployment of SMRs. In addition to engaging partners, stakeholders and Indigenous representatives through workshops, a number of working groups were formed to advise the Road-map Secretariat on topics such as understanding the value proposition of different SMR technologies, matters associated with regulatory readiness, and issues related to waste management and transportation. The Waste Working Group (Waste WG) brought together experts from current nuclear waste generators, the organization responsible for managing Canada's nuclear fuel waste, government, and the regulator to identify waste disposal and storage considerations for Canadian SMR applications, including an analysis of waste streams, waste transportation, short and long-term disposal and storage requirements, and decommissioning considerations. Radioactive waste has been safely managed within a regulatory framework in Canada for decades. Technologies for waste storage and transport exist and also have been in use for decades, and therefore provide a technical basis to explore any specific differences that would apply to waste streams resulting from the construction, operation and decommissioning of SMRs. The Waste WG concluded that a disposal path for SMR used fuel exists through the Nuclear Waste Management Organisation's (NWMO) Adaptive Phased Management (APM) approach, but that R and D work is needed to demonstrate that SMR waste can meet the acceptance criteria. The Waste WG noted that although projects are progressing to realize disposal facilities for the two largest producers of low and intermediate level waste, small producers including potential SMR operators currently have no defined path to disposal for low and intermediate level waste. The Waste WG also highlighted that there could be potential logistical challenges with the transportation of irradiated reactor cores, in particular for remote locations, which will need to be explored. The Waste WG recognized that some uncertainties remain, and early and open communication and coordination between the SMR developers and the NWMO, and potential waste receivers will be key to ensuring a robust framework for SMR waste management from the outset in Canada. This paper explores the results of the analysis and the key findings, high-level recommendations and actions of the Waste WG. It presents the results of the Waste WG's analysis of waste categories against Canadian SMR technologies that best align to end-user requirements; identification of key gaps in research and development for waste categories; and identification of potential work that could address the key gaps. The Waste WG undertook its work between February and August 2018. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Systems Innovation: Modernization & Efficiencies for ESH&Q Reviews

Environmental compliance reviews at INL have traditionally been managed through fragmented systems, relying on multiple spreadsheets and manual processes. This inefficiency led to time-consuming status updates and redundant tasks, such as manually sending reminder emails and transferring data from Excel to the Environmental Review Process (ERP). Initial attempts to streamline these processes using Power Automate and Excel revealed significant limitations, necessitating a more comprehensive solution. To address these immediate inefficiencies, automated workflows were developed using Power Automate. These workflows were designed to send scheduled status update reminders and capture responses through standardized forms, with submitted data flowing directly into centralized Excel trackers. This automation reduced the administrative burden, improved data accuracy, and enabled faster, more consistent reporting. Specifically, email automation achieved a 65% efficiency gain, while data integration saw a 48% improvement, resulting in 91% of project statuses being updated within two months. Despite the improvements brought by Power Automate, the fragmented nature of the review processes persisted. To further enhance efficiency and accuracy, the Integrated Review Tool (IRT) was developed. The IRT aims to centralize review initiation and connect team systems, creating an interconnected data infrastructure that preserves team autonomy while enhancing overall efficiency. This tool automates email reminders, centralizes reviews, and streamlines data integration, significantly improving the accuracy and efficiency of environmental compliance reviews. The design and development of the IRT involved advanced systems methodology, process mapping, project management, and collaboration with subject matter experts. The minimum viable product design is 100% complete, and system development is currently underway, with expected outcomes including a centralized entry point for all ESH&Q reviews, automated routing, real-time tracking and analytics, AI integration, and a user-friendly interface. This project demonstrates the potential of leveraging automation and integrated systems to enhance efficiency, accuracy, and decision-making in environmental reporting and compliance processes at INL.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Planck 2018 results: III. High frequency instrument data processing and frequency maps

This paper presents the High Frequency Instrument (HFI) data processing procedures for the Planck 2018 release. Major improvements in mapmaking have been achieved since the previous Planck 2015 release, many of which were used and described already in an intermediate paper dedicated to the Planck polarized data at low multipoles. These improvements enabled the first significant measurement of the reionization optical depth parameter using Planck-HFI data. This paper presents an extensive analysis of systematic effects, including the use of end-to-end simulations to facilitate their removal and characterize the residuals. The polarized data, which presented a number of known problems in the 2015 Planck release, are very significantly improved, especially the leakage from intensity to polarization. Calibration, based on the cosmic microwave background (CMB) dipole, is now extremely accurate and in the frequency range 100-353 GHz reduces intensity-to-polarization leakage caused by calibration mismatch. The Solar dipole direction has been determined in the three lowest HFI frequency channels to within one arc minute, and its amplitude has an absolute uncertainty smaller than 0.35 μK, an accuracy of order 10 -4 . This is a major legacy from the Planck HFI for future CMB experiments. The removal of bandpass leakage has been improved for the main high-frequency foregrounds by extracting the bandpass-mismatch coefficients for each detector as part of the mapmaking process; these values in turn improve the intensity maps. This is a major change in the philosophy of "frequency maps", which are now computed from single detector data, all adjusted to the same average bandpass response for the main foregrounds. End-to-end simulations have been shown to reproduce very well the relative gain calibration of detectors, as well as drifts within a frequency induced by the residuals of the main systematic effect (analogue-to-digital convertor non-linearity residuals). Using these simulations, we have been able to measure and correct the small frequency calibration bias induced by this systematic effect at the 10 -4 level. There is no detectable sign of a residual calibration bias between the first and second acoustic peaks in the CMB channels, at the 10 -3 level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The effect of boron addition on the deformation behavior and microstructure of β-solidify TiAl alloys

Highlights: • Borides could promote the DRX formation to soften TiAl alloys. • Boron addition increases firstly and then stabilizes the deformation activate energy. • The stable region expands with boron increasing in processing maps. • The DRX critical strain increases firstly and then decreases with boron increasing. • DRX softening and strengthening from solid solution and borides influence deformation behavior. - Abstract: The effect of boron addition on the deformation behavior and microstructure of Ti-43Al-6Nb-1Mo -1Cr alloys have been studied in this paper. Boron addition would induce Ti{sub 2}Al(P6{sub 3}/mmc) phase with hexagonal structure formation on the interfaces between TiB and γ phase. TiB would be the obstacles for dislocations slipping and increase the stacking fault energy. Ti{sub 2}Al could also provide the chemical foundation for DRXed γ nucleation and disappear after thermal deformation. Both these two phase could promote DRXed grains nucleation to soften the alloys during thermal deformation. With the strengthen effect of boron solid solution and TiB obstacles, the microstructure evolution, phase transformation and deformation behavior are also discussed and concluded as follow.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High-Temperature Deformation Behavior of Ti-6Al-2Sn-4Zr-2Mo Alloy with Lamellar Microstructure Under Plane-Strain Compression

High-temperature plane-strain compression of a Ti-6Al-2Sn-4Zr-2Mo (Ti-6242) alloy with a lamellar structure was applied by a thermal simulation machine Gleeble 3800 at a temperature of 1223-1370 K and a strain rate of 0.01-10 s{sup −1}. Constitutive relations between the flow stress and strain at different temperatures and strain rates were constructed based on the Arrhenius equation. Processing maps based on the dynamic material model at strains of 0.5, 1.0, and 1.25 were also constructed to analyze the mechanism and instability of high-temperature deformation. Dynamic recrystallization was found to occur at 1223-1313 K and 0.01-0.1 s{sup −1}, with a peak efficiency of power dissipation of 70%. Observations of the microstructure demonstrated that α platelets and dynamic globularization were responsible for dynamic softening in the α + β phase field. Flow instability behaviors occurred at 1263-1343 K/1.78-10 s{sup −1}, 1233-1283 K/0.1-3.16 s{sup −1}, and 1353-1373 K/0.56-1.78 s{sup −1}, and adiabatic shear bands and microcracks were observed in these domains. Thus, for the lamellar Ti-6242 alloy, the recommended hot rolling parameters were 1243-1333 K and 0.01-0.1 s{sup −1}. Electron backscattered diffraction results revealed that the dynamic restoration mechanism in the β phase field was dynamic recovery when the strain rate was as high as 10 s{sup −1}.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Development of a Novel Cr21 Lean Duplex Stainless Steel and Its Hot Deformation Behavior

In this study, a novel Cr21 lean duplex stainless steel has been developed. In order to investigate the difference in hot workability between the novel steel and the conventional LDX2101, the hot deformation tests were carried out in the temperature ranges from 950 to 1150 °C and strain rate ranges from 0.01 to 10 s{sup −1} by using a thermo-mechanical simulator. The peak stress increased with an increase in strain rate and a decrease in deformation temperature. However, the peak stress of the novel Cr21 lean DSS was always higher than that of the conventional LDX2101 under the same deformation conditions. The novel steel with lower deformation activation energy can be more easily deformed than the LDX2101. Meanwhile, the processing maps based on the specific plastic work approach indicated that the novel steel possessed a narrower flow instability region than the LDX2101. The lower difference in softening rate between ferrite and austenite can lead to the better deformation coordination in the novel steel compared to the LDX2101. The excellent hot workability of the novel steel can be obtained due to the low strength difference between the dual phases and the inhibition of the thin lamellar structures along the rolling direction on the transverse propagation of small cracks originating from the edge of the hot-rolled plates.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Comparative Study of Constitutive Characteristics and Microstructure Evolution between Uniaxial and Plane Strain Compression of an AA6061 Alloy

The hot deformation behavior of an AA6061 alloy was comparatively studied by uniaxial compression (UC) and plane strain compression (PSC) in the temperature range of 300-450 °C and strain rate range of 0.01-5 s{sup −1}. The processing maps were constructed based on a dynamic materials model, and the associated microstructures were observed. Under the same deformation conditions, the flow stress of the AA6061 alloy during PSC is higher than that during UC, which can be characterized by the Zener–Hollomon (Z) parameter in a hyperbolic sine-type equation with an activation energy Q of 175.2 kJ mol{sup −1} and 201.9 kJ mol{sup −1}, respectively. In addition, the instability domain is narrower under PSC compared to that under UC. The observed microstructures also indicate that as the Z value decreases, the tendency of dynamic recrystallization increases during PSC. The softening mechanisms in the AA6061 alloy after PSC and UC mainly consist of the dynamic recovery that is accompanied by a slight dynamic recrystallization. The optimum parameters are in the temperature range of 360-450 °C and strain rate range of 0.03-0.3 s{sup −1} for UC, and for PSC, the optimum parameters are in the temperature range of 320-400 °C and strain rate range of 0.01-0.05 s{sup −1}.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multichannel Analysis of Surface Waves Accelerated (MASWAccelerated): Software for efficient surface wave inversion using MPI and GPUs

Multichannel Analysis of Surface Waves (MASW) is a technique frequently used in geotechnical engineering and engineering geophysics to infer 1D layered models of seismic shear wave velocities in the top tens to hundreds of meters of the subsurface. We aim to accelerate MASW calculations by capitalizing on modern computer hardware available in the workstations of most engineers: multiple cores and graphics processing units (GPUs). We propose new parallel and GPU accelerated algorithms for computing 1D MASW inversion, and provide software implementations in C using Message Passing Interface (MPI) and CUDA. These algorithms take advantage of sparsity that arises in the problem, and the work balance between processes considers typical data trends. We compare our methods to an existing open source Matlab MASW tool. Our serial C implementation achieves a 2x speedup over the Matlab software, and we continue to see improvements by parallelizing the problem with MPI. Here we see nearly perfect strong and weak scaling for uniform data, and improve strong scaling for realistic data by repartitioning the problem to process mapping. By utilizing GPUs available on most modern workstations, we observe an additional 1.3x speedup over the serial C implementation on the first use of the method. We typically repeatedly evaluate theoretical dispersion curves as part of an optimization procedure, and on the GPU the kernel can be cached for faster reuse on later runs. We observe a 3.2x speedup on the cached GPU runs compared to the serial C runs. This work is the first open-source parallel or GPU-accelerated software tool for MASW imaging, and should enable geotechnical engineers to fully utilize all computer hardware at their disposal.

58 GEOSCIENCES↗
DOE OSTI2021

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗
DOE OSTI2018

Characteristic constitution model and microstructure of an Al-3.5Cu-1.5Li alloy subjected to thermal deformation

The constitution model and microstructure of 2A97 Al-Li alloy during thermal deformation were investigated. The thermal deformation behavior was dominated by the interaction between work hardening and dynamic softening. The constitution model was constructed to predict the rheology behavior, in which Zener-Holloman equation with a fifth-order polynomial was set to describe the effect of various strains on the material parameters. Processing maps displayed to exist two unstable domains in microstructure (one domain with the temperature range from 300 °C to 370 °C and the strain rate range from 10{sup 0.5} s{sup −1} to 10s{sup −1}, and the other with the temperature range from 380 °C to 500 °C and the strain rate range from 0 s{sup −1} to 10 s{sup −1}). Microstructural characteristics of dynamic recovery (DRV) and dynamic recrystallization (DRX) in the stable domain and local rheology in the unstable domain were observed, respectively. The dynamic precipitation (DPN) of T{sub 1} phases and the interaction between dislocations and Al{sub 20}Cu{sub 2}Mn{sub 3} and Al{sub 3}Zr phases were concluded by high resolution transmission electron microscopy (HRTEM), which was the first experimental evidence for the DPN in 2A97 Al-Li alloy. All these confirmed the occurrence of the continuous dynamic recrystallization during thermal deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High-Fidelity Single-Shot Readout for a Spin Qubit via an Enhanced Latching Mechanism

The readout of semiconductor spin qubits based on spin blockade is fast but suffers from a small charge signal. Previous work suggested large benefits from additional charge mapping processes; however, uncertainties remain about the underlying mechanisms and achievable fidelity. In this work, we study the single-shot fidelity and limiting mechanisms for two variations of an enhanced latching readout. We achieve average single-shot readout fidelities greater than 99.3% and 99.86% for the conventional and enhanced readout, respectively, the latter being the highest to date for spin blockade. The signal amplitude is enhanced to a full one-electron signal while preserving the readout speed. Furthermore, layout constraints are relaxed because the charge sensor signal is no longer dependent on being aligned with the conventional (2,0)–(1,1) charge dipole. Silicon donor-quantum-dot qubits are used for this study, for which the dipole insensitivity substantially relaxes donor placement requirements. One of the readout variations also benefits from a parametric lifetime enhancement by replacing the spin-relaxation process with a charge-metastable one. This provides opportunities to further increase the fidelity. The relaxation mechanisms in the different regimes are investigated. This work demonstrates a readout that is fast, has a one-electron signal, and results in higher fidelity. As a result, it further predicts that going beyond 99.9% fidelity in a few microseconds of measurement time is within reach.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in Plants

Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. Although it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. The average precision was 0.027 for Arabidopsis and 0.029 for rice. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. Furthermore, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.

59 BASIC BIOLOGICAL SCIENCES↗