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NASA NTRS1993

An experimental investigation of S-duct flow control using arrays of low-profile vortex generators

An experimental investigation was undertaken to measure the effect of various configurations of low-profile vortex generator arrays on the flow in a diffusing S-duct. Three parameters that characterize the vortex generator array were systematically varied to determine their effect: (1) the vortex generator height; (2) the streamwise location of the vortex generator array; and (3) the vortex generator spacing. Detailed measurements of total pressure at the duct exit, surface static pressure, and surface flow visualization were gathered for each vortex generator configuration. These results are reported here along with total pressure recovery and distortion coefficients determined from the experimental data. Each array of vortex generators tested improved total pressure recovery. The configuration employing the largest vortex generators was the most effective in reducing total pressure recovery. No configuration of vortex generators completely eliminated the flow separation that naturally occurs in the S-duct, however the extent of the separated flow region was reduced.

Reichert, Bruce A.↗

NASA NTRS2008

High-Voltage, Asymmetric-Waveform Generator

The shapes of waveforms generated by commercially available analytical separation devices, such as some types of mass spectrometers and differential mobility spectrometers are, in general, inadequate and result in resolution degradation in output spectra. A waveform generator was designed that would be able to circumvent these shortcomings. It is capable of generating an asymmetric waveform, having a peak amplitude as large as 2 kV and frequency of several megahertz, which can be applied to a capacitive load. In the original intended application, the capacitive load would consist of the drift plates in a differential-mobility spectrometer. The main advantage to be gained by developing the proposed generator is that the shape of the waveform is made nearly optimum for various analytical devices requiring asymmetric-waveform such as differential-mobility spectrometers. In addition, this waveform generator could easily be adjusted to modify the waveform in accordance with changed operational requirements for differential-mobility spectrometers. The capacitive nature of the load is an important consideration in the design of the proposed waveform generator. For example, the design provision for shaping the output waveform is based partly on the principle that (1) the potential (V) on a capacitor is given by V=q/C, where C is the capacitance and q is the charge stored in the capacitor; and, hence (2) the rate of increase or decrease of the potential is similarly proportional to the charging or discharging current. The proposed waveform generator would comprise four functional blocks: a sine-wave generator, a buffer, a voltage shifter, and a high-voltage switch (see Figure 1). The sine-wave generator would include a pair of operational amplifiers in a feedback configuration, the parameters of which would be chosen to obtain a sinusoidal timing signal of the desired frequency. The buffer would introduce a slight delay (approximately equal to 20 ns) but would otherwise leave the fundamental timing signal unchanged. The buffered timing signal would be fed as input to the level shifter. The output of the level shifter would serve as a timing and control signal for the high-voltage switch, causing the switch to alternately be (1) opened, allowing the capacitive load to be charged from a high-voltage DC power supply; then (2) closed to discharge the capacitive load to ground. Hence, the output waveform would closely approximate a series of exponential charging and discharging curves (see Figure 2).

Beegle, Luther W.↗

NASA NTRS2008

Automatic Testcase Generation for Flight Software

The TacSat3 project is applying Integrated Systems Health Management (ISHM) technologies to an Air Force spacecraft for operational evaluation in space. The experiment will demonstrate the effectiveness and cost of ISHM and vehicle systems management (VSM) technologies through onboard operation for extended periods. We present two approaches to automatic testcase generation for ISHM: 1) A blackbox approach that views the system as a blackbox, and uses a grammar-based specification of the system's inputs to automatically generate *all* inputs that satisfy the specifications (up to prespecified limits); these inputs are then used to exercise the system. 2) A whitebox approach that performs analysis and testcase generation directly on a representation of the internal behaviour of the system under test. The enabling technologies for both these approaches are model checking and symbolic execution, as implemented in the Ames' Java PathFinder (JPF) tool suite. Model checking is an automated technique for software verification. Unlike simulation and testing which check only some of the system executions and therefore may miss errors, model checking exhaustively explores all possible executions. Symbolic execution evaluates programs with symbolic rather than concrete values and represents variable values as symbolic expressions. We are applying the blackbox approach to generating input scripts for the Spacecraft Command Language (SCL) from Interface and Control Systems. SCL is an embedded interpreter for controlling spacecraft systems. TacSat3 will be using SCL as the controller for its ISHM systems. We translated the SCL grammar into a program that outputs scripts conforming to the grammars. Running JPF on this program generates all legal input scripts up to a prespecified size. Script generation can also be targeted to specific parts of the grammar of interest to the developers. These scripts are then fed to the SCL Executive. ICS's in-house coverage tools will be run to measure code coverage. Because the scripts exercise all parts of the grammar, we expect them to provide high code coverage. This blackbox approach is suitable for systems for which we do not have access to the source code. We are applying whitebox test generation to the Spacecraft Health INference Engine (SHINE) that is part of the ISHM system. In TacSat3, SHINE will execute an on-board knowledge base for fault detection and diagnosis. SHINE converts its knowledge base into optimized C code which runs onboard TacSat3. SHINE can translate its rules into an intermediate representation (Java) suitable for analysis with JPF. JPF will analyze SHINE's Java output using symbolic execution, producing testcases that can provide either complete or directed coverage of the code. Automatically generated test suites can provide full code coverage and be quickly regenerated when code changes. Because our tools analyze executable code, they fully cover the delivered code, not just models of the code. This approach also provides a way to generate tests that exercise specific sections of code under specific preconditions. This capability gives us more focused testing of specific sections of code.

Bushnell, David Henry↗

NASA NTRS2011

Inclined Jet in Crossflow Interacting with a Vortex Generator

An experiment is conducted on the effectiveness of a vortex generator in preventing liftoff of a jet in crossflow, with possible relevance to film-cooling applications. The jet issues into the boundary layer at an angle of 20 degreees to the freestream. The effect of a triangular ramp-shaped vortex generator is studied while varying its geometry and location. Detailed flowfield properties are obtained for a case in which the height of the vortex generator and the diameter of the orifice are comparable with the approach boundary-layer thickness. The vortex generator produces a streamwise vortex pair with a vorticity magnitude 3 times larger (and of opposite sense) than that found in the jet in crossflow alone. Such a vortex generator appears to be most effective in keeping the jet attached to the wall. The effect of parametric variation is studied mostly from surveys 10 diameters downstream from the orifice. Results over a range of jet-to-freestream momentum flux ratio (1 < J < 11) show that the vortex generator has a significant effect even at the highest J covered in the experiment. When the vortex generator height is halved, there is a liftoff of the jet. On the other hand, when the height is doubled, the jet core is dissipated due to larger turbulence intensity. Varying the location of the vortex generator, over a distance of three diameters from the orifice, is found to have little impact. Rounding off the edges of the vortex generator with the increasing radius of curvature progressively diminishes its effect. However, allowing for a small radius of curvature may be quite tolerable in practice.

Zaman, K. B. M. Q.↗

NASA NTRS2012

Goldstone Solar System Radar Waveform Generator

Due to distances and relative motions among the transmitter, target object, and receiver, the time-base between any transmitted and received signal will undergo distortion. Pre-distortion of the transmitted signal to compensate for this time-base distortion allows reception of an undistorted signal. In most radar applications, an arbitrary waveform generator (AWG) would be used to store the pre-calculated waveform and then play back this waveform during transmission. The Goldstone Solar System Radar (GSSR), however, has transmission durations that exceed the available memory storage of such a device. A waveform generator capable of real-time pre-distortion of a radar waveform to a given time-base distortion function is needed. To pre-distort the transmitted signal, both the baseband radar waveform and the RF carrier must be modified. In the GSSR, this occurs at the up-conversion mixing stage to an intermediate frequency (IF). A programmable oscillator (PO) is used to generate the IF along with a time-varying phase component that matches the time-base distortion of the RF carrier. This serves as the IF input to the waveform generator where it is mixed with a baseband radar waveform whose time-base has been distorted to match the given time-base distortion function producing the modulated IF output. An error control feedback loop is used to precisely control the time-base distortion of the baseband waveform, allowing its real-time generation. The waveform generator produces IF modulated radar waveforms whose time-base has been pre-distorted to match a given arbitrary function. The following waveforms are supported: continuous wave (CW), frequency hopped (FH), binary phase code (BPC), and linear frequency modulation (LFM). The waveform generator takes as input an IF with a time varying phase component that matches the time-base distortion of the carrier. The waveform generator supports interconnection with deep-space network (DSN) timing and frequency standards, and is controlled through a 1 Gb/s Ethernet UDP/IP interface. This real-time generation of a timebase distorted radar waveform for continuous transmission in a planetary radar is a unique capability.

Quirk, Kevin J.↗

NASA NTRS2012

NASA's Next Generation Space Geodesy Program

Requirements for the ITRF have increased dramatically since the 1980s. The most stringent requirement comes from critical sea level monitoring programs: a global accuracy of 1.0 mm, and 0.1mm/yr stability, a factor of 10 to 20 beyond current capability. Other requirements for the ITRF coming from ice mass change, ground motion, and mass transport studies are similar. Current and future satellite missions will have ever-increasing measurement capability and will lead to increasingly sophisticated models of these and other changes in the Earth system. Ground space geodesy networks with enhanced measurement capability will be essential to meeting the ITRF requirements and properly interpreting the satellite data. These networks must be globally distributed and built for longevity, to provide the robust data necessary to generate improved models for proper interpretation of the observed geophysical signals. NASA has embarked on a Space Geodesy Program with a long-range goal to build, deploy and operate a next generation NASA Space Geodetic Network (SGN). The plan is to build integrated, multi-technique next-generation space geodetic observing systems as the core contribution to a global network designed to produce the higher quality data required to maintain the Terrestrial Reference Frame and provide information essential for fully realizing the measurement potential of the current and coming generation of Earth Observing spacecraft. Phase 1 of this project has been funded to (1) Establish and demonstrate a next-generation prototype integrated Space Geodetic Station at Goddard's Geophysical and Astronomical Observatory (GGAO), including next-generation SLR and VLBI systems along with modern GNSS and DORIS; (2) Complete ongoing Network Design Studies that describe the appropriate number and distribution of next-generation Space Geodetic Stations for an improved global network; (3) Upgrade analysis capability to handle the next-generation data; (4) Implement a modern survey system to measure inter-technique vectors for co-location; and (5) Develop an Implementation Plan to build, deploy and operate a next-generation integrated NASA SGN that will serve as NASA's contribution to the international global geodetic network. An envisioned Phase 2 (which is not currently funded) would include the replication of up to ten such stations to be deployed either as integrated units or as a complement to already in-place components provided by other organizations. This talk will give an update on the activities underway and the plans for completion.

Merkowitz, S. M.↗

NASA NTRS2012

NASA's Next Generation Space Geodesy Program

Requirements for the ITRF have increased dramatically since the 1980s. The most stringent requirement comes from critical sea level monitoring programs: a global accuracy of 1.0 mm, and 0.1mm/yr stability, a factor of 10 to 20 beyond current capability. Other requirements for the ITRF coming from ice mass change, ground motion, and mass transport studies are similar. Current and future satellite missions will have ever-increasing measurement capability and will lead to increasingly sophisticated models of these and other changes in the Earth system. Ground space geodesy networks with enhanced measurement capability will be essential to meeting the ITRF requirements and properly interpreting the satellite data. These networks must be globally distributed and built for longevity, to provide the robust data necessary to generate improved models for proper interpretation of the observed geophysical signals. NASA has embarked on a Space Geodesy Program with a long-range goal to build, deploy and operate a next generation NASA Space Geodetic Network (SGN). The plan is to build integrated, multi-technique next-generation space geodetic observing systems as the core contribution to a global network designed to produce the higher quality data required to maintain the Terrestrial Reference Frame and provide information essential for fully realizing the measurement potential of the current and coming generation of Earth Observing spacecraft. Phase 1 of this project has been funded to (1) Establish and demonstrate a next-generation prototype integrated Space Geodetic Station at Goddard s Geophysical and Astronomical Observatory (GGAO), including next-generation SLR and VLBI systems along with modern GNSS and DORIS; (2) Complete ongoing Network Design Studies that describe the appropriate number and distribution of next-generation Space Geodetic Stations for an improved global network; (3) Upgrade analysis capability to handle the next-generation data; (4) Implement a modern survey system to measure inter-technique vectors for co-location; and (5) Develop an Implementation Plan to build, deploy and operate a next-generation integrated NASA SGN that will serve as NASA s contribution to the international global geodetic network. An envisioned Phase 2 (which is not currently funded) would include the replication of up to ten such stations to be deployed either as integrated units or as a complement to already in-place components provided by other organizations. This talk will give an update on the activities underway and the plans for completion.

Pearlman, M. R.↗

NASA NTRS2018

Summary of the 1st AIAA Geometry and Mesh Generation Workshop (GMGW-1) and Future Plans

The 1st AIAA Geometry and Mesh Generation Workshop (GMGW-1) was held in conjunction with the AIAA Aviation Forum and Exposition 2017 and in collaboration with the 3rd AIAA Computational Fluid Dynamics (CFD) High Lift Prediction Workshop (HiLiftPW-3). As the first AIAA workshop on these topics, GMGW-1's broad objectives were to assess the current state-of-the art in geometry preprocessing and mesh generation technology as well as software as applied to aircraft and spacecraft systems. The workshop was intended to identify and develop understanding of areas of needed improvement in terms of performance, accuracy, and applicability. It was also to provide a foundation for documenting best practices for geometry preprocessing and mesh generation. The genesis of GMGW-1 is found in the indictments levied against geometry preprocessing and mesh generation - not undeservedly - by the NASA CFD Vision 2030 Study. In order to create a reference against which future progress in geometry preprocessing and mesh generation can be measured, the organizers of GMGW-1, with the assistance of the organizers of HiLiftPW- 3, focused GMGW-1 on generation of meshes of the NASA High Lift Common Research Model (HL-CRM). Some of the generated meshes were provided for use by the participants in HiLiftPW-3. All meshes and the processes by which they were generated were analyzed by GMGW-1 as a first assessment of state of the art practices. The results of GMGW-1 added quantitative detail to known problem areas including geometry modeling, data interoperability, and amount of human intervention. They do provide a clear path toward a vision of geometry preprocessing and mesh generation in the year 2030. The next milepost along this path will be a second workshop.

Chawner, John R.↗

NASA NTRSDate not supplied

Hall Magnetohydrodynamic Power Generation and Drag Augmentation Using A Coaxial-Electrode Configuration During Hypersonic Entry

For interplanetary missions, a spacecraft must reduce its relative velocity from orbital speeds of multiple kilometers per second to zero in order to safely land on the surface of a planetary body. During this phase known as planetary reentry, the spacecraft undergoes high speed above Mach 5 up to Mach 30. This hyper-sonic flight regime imposes a strong bow shock in front of the vehicle that imparts extreme aerodynamic and thermal effects. In addition, during portions of this regime, a plasma is formed in the post-shock flow-field around the vehicle due to these high temperatures. Interaction between an applied magnetic field with this electrically conductive fluid, or magnetohydrodynamic (MHD) interaction, can be utilized to convert kinetic energy from the flow into storable electrical energy. Onboard MHD energy generation can benefit the spacecraft by increasing the power of active thermal control components and vehicle control systems during reentry. MHD interaction also exerts a Lorentz body force on the plasma flow that can be manipulated to act as an additional drag force through the vehicle body. MHD drag augmentation can benefit the spacecraft with an additional control mechanism that operates without moving parts. This can be utilized at higher altitudes and subsequently reduce convective heat transfer to the vehicle. MHD interaction with plasma flow suggests that both power generation and drag augmentation can be integrated together in one design. Modern numerical studies have only demonstrated the viability and potential of MHD energy generation and drag modulation separately for implementation into future spacecraft designs [1] [2] [3]. Steeves et. al. presented one possible generator design specifically for reentry vehicles that utilized a modular panel with two embedded electromagnets and two extruding electrodes for air plasma to flow between. Fujino et. al. presented results that indicated increased total drag with a permanent magnet embedded in the blunt body of the Orbital Reentry Experiment (OREX) trajectory. Furthermore, experimental investigations of these two MHD applications have been limited and separate due to the difficult technical nature of experimental de-sign and analysis. For MHD energy generation, there have been two designs which used a cylindrical fore-body with two embedded permanent magnets and two outward facing curved electrodes for tangency to an artificially ionized plasma that flowed along the body length [4] [5]. The first design was studied using an air microwave (MW) ionized supersonic plasma wind tunnel and the second design used radio frequency (RF) ionization of Argon, but both physically demonstrated the feasibility of MHD energy generation in reentry plasma conditions. For MHD drag modulation, one study involved a small-scale cylindrical blunt body embedded with permanent magnets immersed in plasma flow in an arcjet tunnel [6], and another utilized a spherical permanent magnet enclosed with a spherical forebody that was evaluated in a shock expansion tunnel [7]. Both experimental studies provided physical evidence of drag augmentation due to MHD interactions. Therefore, because of the multi-faceted effects of MHD along with both applications having been deemed feasible and beneficial during reentry, this indicates that a coupled power generation and drag modulation design could be achievable. The axi-symmetric nature of blunt bodies for reentry suggests that a spherical set of two ring electrodes near the nose along the body axis. Based on first principles, flow along the walls of the spherical body can then produce MHD interactions between the electrodes. As a result, two currents are generated: a Hall current that produces power and a primary inductive current that augments the drag force. The goal of this work is to provide a simulated design of a coaxial-electrode con-figuration for power generation and drag modulation for experimental testing.

E. Leong↗

DOE OSTI2025

GrainPaint: A multi-scale diffusion-based generative model for microstructure reconstruction of large-scale objects

Simulation-based approaches to microstructure generation can suffer from a variety of limitations, such as high memory usage, long computational times, and difficulties in generating complex geometries. Generative machine learning models present a way around these issues, but they have previously been limited by the fixed size of their generation area. Here, we present a new microstructure generation methodology leveraging advances in inpainting using denoising diffusion models to overcome this generation area limitation. We show that microstructures generated with the presented methodology are statistically similar to grain structures generated with a kinetic Monte Carlo simulator, SPPARKS.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Proposed Algorithm for Placement and Sizing of Generation and Storage Stations in Urban Environments

The placement of generation and storage stations (GSSs) in distribution grids has been extensively investigated. Most traditional methods are applicable to rural or homogeneous environments and do not account for external restrictions on generation placement in urban or semi-urban environments. In this article, we propose a method for generation placement considering externality constraints. New utility-scale generation in distribution grids potentially occupies footprint and interferes in areas with existing infrastructure with architectural, historical, or touristic value. Urban environments are often regulated by municipal legislation. The placement of utility-scale generation in urban landscapes is economically and physically restricted by such externalities, and existing methods for generation placement in distribution grids based on technical optimization fail to account for this important nuance. The proposed algorithm flexibly adapts to changes in government energy policies and priorities. The selection of the type of generation suitable for the power grid is left to the preference of external high-level stakeholders, such as urban planners, industry development leaders, and energy policymakers. The proposed algorithm is a unique tool for determining the placement and sizing of generation in realistic conditions in distribution grids; it is adaptable to urban externalities and sensitive to stakeholder preferences.

generation and storage station placement↗

DOE OSTI2024

Impacts of Climate Change on the Generation Potential of Solar and Wind Energy Systems in India

Low-carbon energy sources like wind and solar are essential for decarbonizing the electricity sector. In addition, the cost of electricity generated from these sources has plummeted over the last decade. Therefore, these energy sources are poised to take a significant share of the total installed capacity soon. However, they are susceptible to the impacts of climate change as their generation potential depends on the weather conditions. Estimating the installed capacity requirements of solar and wind energy to decarbonize the power sector without accounting for these possible changes in generation potential could lead to missing out on the set climate goals and meeting future electricity demand. This study evaluates the effect of climate change on the generation potential of wind and solar energy systems in India for two future periods, 2050 and 2070, under two climate scenarios or Shared Socioeconomic Pathway (SSP): SSP245 and SSP585. Almost all regions show a decrease, and most regions show a significant decline (>5%) in the generation potential of solar Photovoltaic (PV) as compared to 2010 levels under both climate scenarios and future periods. The changes in the generation potential of wind energy are more significant (>10%), and the majority of regions show a decline in generation potential. Southwestern and central regions show an increase in wind generation potential for 2070 as compared to 2050 levels under the SSP245 scenario and the SSP585 scenario, respectively.

climate change↗

NASA NTRS2016

Vortex Generators in a Two-Dimensional, External-Compression Supersonic Inlet

Vortex generators within a two-dimensional, external-compression supersonic inlet for Mach 1.6 were investigated to determine their ability to increase total pressure recovery, reduce total pressure distortion, and improve the boundary layer. The vortex generators studied included vanes and ramps. The geometric factors of the vortex generators studied included height, length, spacing, and positions upstream and downstream of the inlet terminal shock. The flow through the inlet was simulated through the computational solution of the steady-state Reynolds-averaged Navier-Stokes equations on multi-block, structured grids. The vortex generators were simulated by either gridding the geometry of the vortex generators or modeling the vortices generated by the vortex generators. The inlet performance was characterized by the inlet total pressure recovery, total pressure distortion, and incompressible shape factor of the boundary-layer at the engine face. The results suggested that downstream vanes reduced the distortion and improved the boundary layer. The height of the vortex generators had the greatest effect of the geometric factors.

computational fluid dynamics↗

NASA NTRS2015

Model Generation to Support Model-Based Testing Applied on NASA DAT - An Experience Report

Model-based Testing (MBT), where a model of the system under tests (SUT) behavior is used to automatically generate executable test cases, is a promising and versatile testing technology. Nevertheless, adoption of MBT technologies in industry is slow and many testing tasks are performed via manually created executable test cases (i.e. test programs such as JUnit). In order to adopt MBT, testers must learn how to construct models and use these models to generate test cases, which might be a hurdle. An interesting observation in our previous work is that the existing manually created test cases often provided invaluable insights for the manual creation of the testing models of the system. In this paper we present an approach that allows the tester to first create and debug a set of test cases. When the tester is happy with the test cases, the next step is to automatically generate a model from the test cases. The generated model is derived from the test cases, which are actions that the system can perform (e.g. a button clicks) and their expected outputs in form of assert statements (e.g. assert data entered). The model is a Finite State Machine (FSM) model that can be employed with little or no manual changes to generate additional test cases for the SUT. We successfully applied the approach in a feasibility study to the NASA Data Access Toolkit (DAT), which is a web-based GUI. One compelling finding is that the test cases that were generated from the automatically generated models were able to detect issues that were not detected by the original set of manually created test cases. We present the findings from the case study and discuss best practices for incorporating model generation techniques into an existing testing process.

State Machines↗

DOE OSTI2024

Is a Generator the Only Solution When the Grid Fails? Optimizing Systems for Resiliency and Carbon Reduction: Preprint

Traditionally, buildings are dependent on utility infrastructure, and when a grid failure happens, end users rely on the closest source of energy storage to sustain operation until power is restored. For buildings, that typically means using an electric generator. This electric generator either uses on-site energy storage such as fossil fuels in a tank or a gas connection which is, in turn, tied to gas wells—also a form of energy storage. Generators are popular for their ease of implementation and low capital costs; however, they have limited value outside of disruptions, and they are a source of scope 1 emissions, or direct greenhouse gas emissions from sources controlled by the building owner. In contrast, some power generation and storage systems, such as photovoltaic (PV) panels and battery energy storage systems (BESS), can serve the same purpose during grid disruptions while presenting advantages outside of power failure. This paper explores methods for storing and converting energy on-site to increase building resiliency, focusing on solutions that minimize scope 1 emissions. We analyze the cost and carbon impacts of energy efficiency measures, PV arrays, and BESS, with and without generators, in a simulation test case. We find significant benefits can be achieved both during and outside of power failure events when designing systems that integrate the on-demand capability of generators, the low carbon energy supplied by PV, and the storage capabilities of BESS. Specifically, adding even minimal BESS and PV can result in downsizing the generator, increasing generator efficiency and requiring less fuel.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2026

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Enhancing generative molecular design via uncertainty-guided fine-tuning of variational autoencoders

In recent years, deep generative models have been successfully applied to various molecular design tasks, particularly in the life and materials sciences. One critical challenge for pre-trained generative molecular design (GMD) models is to fine-tune them to be better suited for downstream design tasks that aim at optimizing specific molecular properties. However, redesigning and training an existing effective generative model from scratch for each new design task are impractical. Furthermore, the black-box nature of typical downstream tasks that involve property prediction makes it nontrivial to optimize the generative model in a task-specific manner. In this work, we propose an uncertainty-guided fine-tuning strategy that can effectively enhance a pre-trained variational autoencoder (VAE) for GMD through performance feedback in an active learning setting. The strategy begins by quantifying the model uncertainty of the generative model using an efficient active subspace-based UQ (uncertainty quantification) scheme. Next, the decoder diversity within the characterized model uncertainty class is explored to expand the viable space of molecular generation. The low-dimensionality of the active subspace makes this exploration tractable using a black-box optimization scheme, which in turn enables us to identify and leverage a diverse set of high-performing models to generate enhanced molecules. Empirical results across six target molecular properties using multiple VAE-based generative models demonstrate that our uncertainty-guided fine-tuning strategy consistently leads to improved models that outperform the original pre-trained models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Crystal structure prediction with host-guided inpainting generation and foundation potentials

Unconditional crystal structure generation with diffusion models faces challenges in identifying symmetric crystals as the unit cell size increases. Here, we present the crystal host-guided generation (CHGGen) framework to address this challenge through conditional generation using an inpainting method, which optimizes a fraction of atomic positions within a predefined and symmetrized host structure to improve the success rate for symmetric structure generation. By integrating inpainting structure generation with a foundation potential for structure optimization, we demonstrate the method on the ZnS–P 2 S 5 and Li–Si chemical systems, where the inpainting method generates a higher fraction of symmetric structures than unconditional generation. The practical significance of CHGGen extends to enabling the structural modification of crystal structures, particularly for systems with partial occupancy or intercalation chemistry. The inpainting method also allows for seamless integration with other generative models, providing a versatile framework for accelerating materials discovery.

Zhong, Peichen [University of California, Berkeley↗