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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine Learning Framework for Characterizing Processing–Structure Relationship in Block Copolymer Thin Films

The morphology of block copolymers (BCPs) critically influences material properties and applications. This work introduces a machine learning (ML)-enabled, high-throughput framework for analyzing grazing incidence small-angle X-ray scattering (GISAXS) data and atomic force microscopy (AFM) images to characterize BCP thin film morphology. A convolutional neural network was trained to classify AFM images by surface features, achieving 97% testing accuracy. Classified images were then analyzed to extract 2D grain size measurements from the samples in a high-throughput manner. ML models were trained to predict domain orientation based on processing parameters such as solvent ratio, additive type, and additive ratio. GISAXS-based properties were predicted with strong performances (R 2 > 0.75), while AFM-based property predictions were less accurate (R 2 < 0.60), likely due to the localized nature of AFM measurements compared to the bulk information captured by GISAXS. Beyond model performance, interpretability was addressed using SHapley Additive exPlanations (SHAP). SHAP analysis revealed that the additive ratio had the largest impact on morphological predictions, where additive provides the BCP chains with increased volume to rearrange into thermodynamically favorable morphologies. This interpretability helps validate model predictions and offers insight into parameter importance. Altogether, the presented framework combining high-throughput characterization and interpretable ML offers an approach to exploring and optimizing BCP thin film morphology across a broad processing landscape.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Robotic High-Throughput Grid-Search Platform for Mapping Phase Behavior in Triblock Copolymer–Homopolymer Blends

We present a high-throughput experimental investigation of the phase behavior in triblock copolymers (PS-b-PB-b-PS and PS-b-PI-b-PS) and polystyrene (PS) homopolymer blends as a function of homopolymer molecular weight (MW) and blend ratio. Using a robotic thin-film processing platform (NOVA) integrated with Grazing Incidence Small-Angle X-ray Scattering (GISAXS) and Atomic Force Microscopy (AFM), we systematically mapped the order–disorder transition (ODT) boundaries and domain spacing evolution across a broad MW range (4.0–101.3 kDa) with varying homopolymer loadings (10% to 90%). The results reveal three distinct regimes: low-MW homopolymers, corresponding to the wet-brush regime produced only gradual domain swelling before disordering at high blend ratios (weight fraction); medium-MW homopolymers, corresponding to thedry-brush regime induced significant domain spacing increase up to 80% followed by earlier disordering, while high-MW homopolymers led to macrophase separation with minimal changes in domain spacing. Additionally, coarse-grained molecular dynamics simulations confirmed our experimental finding that in the low-MW region, the PS homopolymer uniformly distributed in the PS domain. These findings demonstrate that homopolymer molecular weight critically governs both the extent of domain swelling and the onset of disorder in triblock copolymer systems. This high-throughput platform enables the rapid mapping of composition–morphology relationships and can be integrated with AI/ML tools for designing next-generation nanostructured polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Automated and High-Throughput Phase Separation Control for Supramolecular Polymer Blends Enabled by Machine Learning

Supramolecular polymer blends (SPBs) offer tunable morphologies that dictate their macroscopic properties, yet their rational design is limited by the absence of predictive structure−morphology models. Here, we introduce a data-driven highthroughput workflow that integrates modular polymer synthesis, robotic formulation, automated morphology characterization, and machine learning (ML) for accelerated SPB discovery. Using a plug-and-play synthetic strategy, 33 hydrogen-bonding endfunctional homopolymers were prepared and orthogonally combined to generate 260 SPBs in 1 day. A fully automated atomic force microscopy (AFM) pipeline enabled systematic imaging, producing 2340 morphology data sets with minimal human intervention. Domain spacings were extracted through complementary imageprocessing methods and used to train ML models. A support vector regression (SVR) model accurately predicted target phase-separation sizes (50, 100, and 150 nm), which were experimentally validated. This work demonstrates the power of coupling high-throughput experimentation with ML to accelerate morphology discovery and provides one of the first large-scale experimental data sets for supramolecular polymer systems.

ML-guided polymer design↗
DOE OSTI2026

Chain entanglements enable regeneration of high-performance thermosets

Thermoset plastics underpin structural materials, electronics and transportation, yet the permanent covalent networks that prevent flow and provide dimensional stability also make them difficult to recycle without sacrificing performance. In this work we show that high-performance thermosets can be built around dense chain entanglements, the physical interlacing of long polymer strands, rather than dense permanent crosslinks, with only a small number of selectively cleavable junctions preserving connectivity. Long, rigid, entangled polyolefin backbones generated by frontal polymerization form glassy polymers with high stiffness, high toughness and excellent creep suppression yet can be fully deconstructed into soluble, linear oligomers. Varying oligomer length and end-group chemistry enables their reuse as re-entangling building blocks that regenerate thermosets with thermal and mechanical properties that remain unchanged across generations. The strategy further extends to high-temperature fibre-reinforced composite matrices and additively manufactured structures, establishing chain entanglement as a design principle for durable, regenerable thermosets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Moiré-driven topological electronic crystals in twisted graphene

In a dilute two-dimensional electron gas, Coulomb interactions can stabilize the formation of a Wigner crystal. Although Wigner crystals are topologically trivial, it has been predicted that electrons in a partially filled band can break continuous translational symmetry and time-reversal symmetry spontaneously, resulting in a type of topological electron crystal known as an anomalous Hall crystal. Here we report signatures of a generalized version of the anomalous Hall crystal in twisted bilayer–trilayer graphene, whose formation is driven by the moiré potential. The crystal forms at a band filling of one electron per four moiré unit cells (ν = 1/4) and quadruples the unit-cell area, coinciding with an integer quantum anomalous Hall effect. The Chern number of the state is exceptionally tunable, and it can be switched reversibly between +1 and −1 by electric and magnetic fields. Several other topological electronic crystals arise in a modest magnetic field, originating from ν = 1/3, 1/2, 2/3 and 3/2. As a result, the quantum geometry of the interaction-modified bands is likely to be very different from that of the original parent band, which enables possible future discoveries of correlation-driven topological phenomena.

Electronic properties and materials↗
DOE OSTI2023

A hybrid 3D/2D field response calculation for liquid argon detectors with PCB based anode plane

Liquid Argon Time Projection Chamber (LArTPC) technology is commonly utilized in neutrino detector designs. It enables detailed reconstruction of neutrino events with high spatial precision and low energy threshold. Its field response (FR) model describes the time-dependent electric currents induced in the anode-plane electrodes when ionization electrons drift nearby. An accurate and precise FR is a crucial input to LArTPC detector simulations and charge reconstruction. Established LArTPC designs have been based on parallel wire planes. It allows accurate and computationally economic two-dimensional (2D) FR models utilizing the translational symmetry along the direction of the wires. Recently, novel LArTPC designs utilize electrodes formed on printed circuit board (PCB) in the shape of strips with through holes. The translational symmetry is no longer a good approximation near the electrodes and a new FR calculation that employs regions with three dimensions (3D) has been developed. Extending the 2D models to 3D would be computationally expensive. Fortuitously, the nature of strips with through holes allows for a computationally economic approach based on the finite-difference method (FDM). In this paper, we present a new software package pochoir that calculates LArTPC field response for these new strip-based anode designs. This package combines 3D calculations in the volume near the electrodes with 2D far-field solutions to achieve fast and precise field response computation. We apply the resulting FR to simulate and reconstruct samples of cosmic-ray muons and 39 Ar decays from a Vertical Drift (VD) detector prototype operated at CERN. We find the difference between real and simulated data within 5%. Current state-of-the-art LArTPC software requires a 2D FR which we provide by averaging over one dimension and estimate that variations lost in this average are smaller than 7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The effect of radiation damage on the light yield and uniformity of candidate plastic scintillator tiles for the CMS hadron calorimeter upgrade

A study has been performed to understand the effects of radiation damage on various plastic scintillator tiles considered for a possible upgrade of the hadron calorimeter of the CMS detector. Measurements were made with unirradiated tiles and with tiles that had been irradiated in the CMS collision hall to a dose of 44 kGy. Results are presented for the tiles of different shapes in terms of the energy spectrum, efficiency as a function of the position at which each tile was hit, as well as light yield. All the tiles showed a light reduction of up to about 50%. The tiles with the shape currently used in the CMS detector did not see increased non-uniformity of light collection, while a significant disuniformity was observed for the tiles considered as alternatives.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Reverse order-disorder transition of Janus particles confined in two dimensions

In this study Janus particles with different patch sizes, confined to two dimensions, generate a series of patterns of interest to the field of nanoscience. Here we observe reverse melting, where for some densities the system melts under cooling. For a broad range of hydrophobic patch sizes ( 60° < θ 0 < 90°), a reentrant transition from solid to liquid and then to an ordered phase emerges as temperature (T) decreases due to the formation of rhombus chains at low T. This reentrant phase has pseudo long-range orientational order but short-range translational order, similar to a hexatic phase. Our work provides guidelines to study the melting and assembly of Janus particles in two dimensions, as well as mechanisms to generate phases with specific symmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Chern Insulators at Integer and Fractional Filling in Moiré Pentalayer Graphene

The advent of moiré platforms for engineered quantum matter has led to discoveries of integer and fractional quantum anomalous Hall effects, with predictions for correlation-driven topological states based on electron crystallization. Here, we report an array of trivial and topological insulators formed in a moiré lattice of rhomobohedral pentalayer graphene (R5G). At a doping of one electron per moiré unit cell ( ν = 1 ), we see a correlated insulator with a Chern number that can be tuned between C = 0 and + 1 by an electric displacement field. This is accompanied by a series of additional Chern insulators with C = + 1 originating from fractional fillings of the moiré lattice— ν = 1 / 4 , 1 / 3 , and 2 / 3 —associated with the formation of moiré-driven topological electronic crystals. At ν = 2 / 3 the system exhibits an integer quantum anomalous Hall effect at zero magnetic field, but further develops hints of an incipient C = 2 / 3 fractional Chern insulator in a modest field. Our results establish moiré R5G as a fertile platform for studying the competition and potential intertwining of integer and fractional Chern insulators. Published by the American Physical Society 2025

Waters, Dacen (ORCID:0000000335880039)↗
DOE OSTI2022

3.5 kW/in3 Planar Coupled Inductor Design and Optimization for a 50 kW 3-level Four-Switch Buck-Boost (3L-FSBB) Converter

Planar magnetics design has been widely used in power electronics field because of the low profile, ease of manufacturability, and high power density. This paper first proposes a 3-level four-switch buck-boost (3L-FSBB) converter for the dc-dc applications where the zero common-mode (CM) voltage emissions, step-up and step-down are all required. With the consideration of power density, efficiency, and cost, a 15oz heavy copper coupled inductor for 3-level FSBB converter was designed and optimized with the low-cost commercial core and planar windings. According to the soft-switching quadrangle modulation for 3-L FSBB, the turns number and stacked core number are optimized first. And then, a two-board design is proposed to reduce the fringing effect and improve the thermal performance. Finally, a 75 kVA two-stage ac-dc-dc converter including a 3-level FSBB converter was built to verify the electrical design.

Cao, Yuliang↗
DOE OSTI2022

A 75 kVA Intelligent Power Stages (IPS) Unit Design for Future Grid-interface Application

The demand for grid-interface converter with flexible dc bus is driven by the fast development of energy storage system (ESS), electric vehicle (EV) charging system, and versatile residential load. This paper first proposes a two-stage intelligent power stage (IPS) unit for future grid-interface applications. To achieve zero common-mode (CM) voltage emissions, step-up and step-down voltage gain, a 3-level four-switch buck-boost (3-L FSBB) dc-dc converter is adopted with fully zero voltage switching (ZVS). In one IPS unit, an advanced fiberoptic communication with sub-nanosecond synchronization is developed for different enhanced gate drivers. Moreover, an enhanced gate driver integrated current and voltage sensors is designed for monitoring and diagnostics. To achieve a whole low-profile design, three 12 oz heavy copper planar ac inductors are designed and implemented. Finally, a 75 kVA IPS unit was built to verify both the thermal and electrical design.

Cao, Yuliang↗