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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-resolution chemical patterns from negative tone resists for the integration of extreme ultraviolet patterns of metal-oxide resists with directed self-assembly of block copolymers

Extreme ultraviolet (EUV) lithography faces significant challenges in designing suitable resist materials that can provide adequate precision, while maintaining economically viable throughput. These challenges in resist materials have led to printing failures and high roughness in EUV patterns, compromising the performance of semiconductor devices. Integrating directed self-assembly (DSA) of block copolymers (BCPs) with EUV lithography offers a promising solution because, while the BCPs register to the EUV-defined chemical guiding pattern, the thermodynamically determined structures of the BCPs automatically rectify defects and roughness in the EUV pattern. Despite the superior resolution of metal-oxide EUV resists (MORs), their application to DSA is limited by the difficulty in converting them into chemical patterns that allow effective transfer of the rectified patterns of DSA films into inorganic materials. To address this challenge, this study introduces a novel strategy for fabricating chemical patterns using hydrogen silsesquioxane (HSQ), a high-resolution negative tone inorganic resist, as a model system for MORs. Initially, a sacrificial Cr pattern is generated from HSQ patterns via reactive ion etching. The sacrificial Cr pattern is converted into a chemical pattern by first grafting a water-soluble polyethylene oxide brush onto the substrate, then wet etching the Cr, and finally grafting nonpolar polystyrene brushes. Assembling polystyrene-block-poly(methyl methacrylate) on these patterns results in structures oriented and registered with the underlying pattern, achieving 24 nm full-pitch resolutions. In conclusion, this approach has the potential to integrate MOR patterns into the DSA process, thereby enabling the generation of high-quality sub-10 nm patterns with high-χ BCPs.

Atomic force microscopy↗
DOE OSTI2026

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗
DOE OSTI2025

Effect of pattern transfer process on roughness of block copolymer patterns from directed self-assembly

Block copolymer-directed self-assembly (DSA) remains promising for improving pattern quality and reducing the stochastic variations that challenge high numerical aperture extreme ultraviolet lithography. Equally critical is refining pattern transfer methods for accurately transferring the rectified DSA features to the underlying substrate. We compare two atomic layer deposition (ALD)-based techniques: sequential infiltration synthesis (SIS) and dry liftoff, applied to polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) DSA patterns. Both methods utilize aluminum oxide hard masks, with one synthesized through infiltration into the PMMA domains and the other through conformal ALD coating. High-resolution scanning electron micrographs were analyzed to measure line edge, width, and placement roughness for both the line (PMMA) and space (PS) features. Although both methods yielded similar overall 3σ rms roughness, they differed significantly in the frequency-dependent power spectral density (PSD) profiles. SIS reduced line placement roughness at length scales associated with the polymer pitch, but increased space width roughness at low frequencies, whereas dry liftoff mimicked the frequency content of the original guiding pattern. This study underscores the importance of PSD evaluation in selecting optimal pattern transfer strategies for specific applications.

Block copolymers↗
DOE OSTI2026

QPatLib v1.0 — Measurement-based quantum simulation Pauli string unitary pattern collections

This Zenodo record accompanies the paper “Scalable Measurement-Based Quantum Simulation Patterns for Benchmarking” arXiv.2605.12502 and provides QPatLib v1.0 measurement-pattern datasets in human-readable JSONL together with a ZIP archive of OpenQASM 3.0 circuits used for validation and reproducibility. The patterns and circuits implement Pauli string unitaries for benchmark cases. Cases include all possible string combinations for less than 6 qubits and strings used in Hamiltonians for certain diatomic molecules for 6 or more qubits. Format: Each pattern_*.jsonl file is containins measurement patterns for all subsets for a given model/instance and subset strategy: it begins with a preamble containing model metadata, subset definitions, provenance, and (when feasible) full-pattern test results, followed by one pattern entry per subset. Each subset entry includes a required pattern_ascii field storing the measurement pattern in the measurement-calculus/Graphix standard with signal shifting, written left-to-right in the canonical order nodes → edges → measurements (with signal dependencies) → byproduct corrections (X/Z). The circuits are included as circuit_files.zip. Patterns in this record were validated against the corresponding circuits and checked for causal flow. Codes for generating these patterns can be found at QPatLib repository on Github

Graphix↗
DOE OSTI2025

Predicting multi-nodal in-nozzle particle interactions in high-viscosity fluid mediums for acoustophoretic direct-ink writing of line-patterned composites

Patterned functional materials offer improved properties (electrical, thermal, etc.) over their bulk counterparts in many applications, including energy storage, flexible electronics, and sensors. However, manufacturing approaches for patterning materials over large areas with features on the order of hundreds of microns or less are limited. Acoustophoresis, which uses acoustic forces to control particle arrangement in a fluid medium, is a pathway to address this challenge. This process is dependent on particle and fluid properties and enables patterning of a broad range of materials. Herein, a model with experimental validation is presented to demonstrate that acoustophoresis can be combined with direct-ink writing (DIW) to fabricate line patterns over large cm-scale areas. An in-nozzle particle interaction model was developed to investigate the impact of processing conditions on multi-nodal acoustophoretic DIW. The model predicts patterned line widths within a factor of two relative to experimental results for a high viscosity case study. Here, the model was used to investigate the impact of frequency, particle loading, particle radius, and acoustic pressure on line width and patterning time, providing critical feedback regarding the processing conditions suitable for a target application. Model results illustrate that frequency has the greatest impact on line patterns: increasing from 1 to 3 MHz resulted in a greater than 65% reduction in line width and a greater than 85% reduction in patterning time. Additionally, experiments were conducted with an alumina-epoxy ink and a ~21 cm 2 area pattern was rastered in ~5.5 minutes, demonstrating a path towards large-area line-patterned composite fabrication.

25 ENERGY STORAGE↗
DOE OSTI2025

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electrostatically driven pattern formation in mixed charged–neutral multicomponent elastic membranes

Multicomponent crystalline and amorphous elastic shells exhibit heterogeneous surface patterns that provide distinctive functionalities in cellular environments. Such patterning typically arises from the competition between short-range attractive and long-range repulsive interactions in membranes. Here, we demonstrate that the intrinsic competition between electrostatic repulsion and elastic deformation is sufficient to drive spontaneous surface patterning in elastic shells, requiring no additional attractive interactions. Using numerical simulations, we demonstrate pattern formation in mechanically homogeneous membranes with heterogeneous surface charge composition across different topologies, including spheres, discs, and flat periodic membranes. We also examine patterns in crystalline and amorphous shells of coassembled charged and neutral components with different bending rigidities. At low charge fraction, discrete charged surface domains form. At intermediate charge fraction, the competition between electrostatics and elasticity leads to elongated domains (rods) of the charged component, which results in lamellar patterns at nearly equal fraction of the charged and neutral components. At high charge fraction, nanodomains of the neutral component form. Amorphous shells exhibit similar progressions but with disordered structures rather than ordered lamellar patterns. These pattern morphologies are observed in both the closed shells and flat membranes. As salt concentration increases, all patterns coarsen due to the screening of electrostatic interactions.

charge heterogeneity↗
DOE OSTI2025

Spatiotemporal pattern detection, generation, and computation with circuits

Abstract Implementations of neurons, delays, and synapse circuits are presented with simulations. These neural elements are used to create two small spiking neural networks, the Rate-Window and Order-Biased clusters, which are capable of detecting simple two-spike spatiotemporal patterns. A simple pattern detecting network (SPDN) is created by combining the Rate-Window and Order-Biased clusters, where clusters are small spiking neural networks, and its simple pattern detection ability is demonstrated in simulation. The SPDN is used to implement a complex pattern detecting network (CPDN) and its complex pattern detection ability is demonstrated in simulation. Methods for generating arbitrary spatiotemporal patterns are presented. The CPDN and spatiotemporal pattern generation methods are then used to implement a novel spatiotemporal computing paradigm based on detecting and responding to spatiotemporal symbols. A simulation of a spatiotemporal half adder is presented to demonstrate the computing paradigm.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Forest structural complexity and ignition pattern influence simulated prescribed fire effects

Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Directed self-assembly of block copolymers for high-precision patterning in the era of extreme ultraviolet lithography

Extreme ultraviolet (EUV) lithography enables unprecedented resolution in semiconductor patterning but faces critical challenges in developing resist materials that achieve high-precision at economically viable throughput. Directed self-assembly (DSA) of block copolymers (BCPs) offers a promising solution for pattern rectification by leveraging thermodynamically determined domain structures to decouple BCP pattern quality from the imperfect original lithographic pattern. This prospective presents an overview of recent progress on the EUV + DSA strategy, covering advances in BCP material design, processing, metrology, and pattern transfer. We highlight recent advances in high-χ BCPs with perpendicular orientation and domain spacings compatible with EUV dimensions, leveraging A-b-(B-r-C) architectures. We also discuss progress in chemical pre-pattern fabrication using both positive- and negative tone resists, along with processing strategies to minimize defects and roughness based on BCP thermodynamics and assembly kinetics. We further examine metrology platforms for characterizing the thermodynamics of BCP materials and quantifying the size and shape of BCP domains. Lastly, we review pattern transfer strategies for generating functional inorganic masks suitable for semiconductor manufacturing. Together, these advances highlight the potential of DSA to complement EUV lithography, offering a pathway to address critical challenges in achieving high-precision patterning for the semiconductor industry.

Lee, Kyunghyeon [Univ. of Chicago, IL (United Stat↗
DOE OSTI2025

Entropy-Assisted Quality Pattern Identification in Finance

Short-term patterns in financial time series form the cornerstone of many algorithmic trading strategies, yet extracting these patterns reliably from noisy market data remains a formidable challenge. In this paper, we propose an entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behavior over time. We ground our approach in the premise that historical patterns, when accurately clustered and pruned, can yield substantial predictive power for short-term price movements. To achieve this, we incorporate an entropy-based measure as a proxy for information gain: patterns that lead to high one-sided movements in historical data yet retain low local entropy are more “informative” in signaling future market direction. Compared to conventional clustering techniques such as K-means and Gaussian Mixture Models (GMMs), which often yield biased or unbalanced groupings, our approach emphasizes balance over a forced visual boundary, ensuring that quality patterns are not lost due to over-segmentation. By emphasizing both predictive purity (low local entropy) and historical profitability, our method achieves a balanced representation of Buy and Sell patterns, making it better suited for short-term algorithmic trading strategies. This paper offers an in-depth illustration of our entropy-assisted framework through two case studies on Gold vs. USD and GBPUSD. While these examples demonstrate the method’s potential for extracting high-quality patterns, they do not constitute an exhaustive survey of all possible asset classes.

Physics↗
DOE OSTI2026

T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph

Finding frequent subgraph patterns in a big graph is an important problem with many applications such as classifying chemical compounds and building indexes to speed up graph queries. Since this problem is NP-hard, some recent parallel and distributed systems have been developed to accelerate the mining. However, they often have a huge memory cost, very long running time, suboptimal load balancing, poor scale-out capability, and possibly inaccurate results. In this article, we propose an efficient system called T-FSM for parallel mining of frequent subgraph patterns in a big graph. T-FSM supports a new anti-monotonic frequentness measure called Fraction-Score, which is more accurate than the widely used MNI measure. The execution engine of T-FSM supports both intra-machine parallelism and inter-machine parallelism. For intra-machine parallelism, T-FSM adopts a novel task-based execution model to ensure high multithreading concurrency, bounded memory consumption, and effective load balancing. For inter-machine parallelism, T-FSM ensures good scale-out performance with a lightweight pattern rebalancing approach that reduces workload skewness of pattern evaluations among machines. To avoid recomputing the contexts for migrated patterns, we design a novel context cache table to support concurrent and asynchronous requesting and caching of remote context data, which can timely evict and garbage collect used pattern contexts that are no longer needed to keep memory consumption bounded. Extensive experiments show that T-FSM is orders of magnitude faster than existing state-of-the-art parallel systems (more than 10×, 51×, 131×, 55× speedup over ScaleMine, DistGraph, Pangolin and Peregrine, respectively) and distributed systems (more than 42× and 88× over ScaleMine and DistGraph, respectively) for frequent subgraph pattern mining, and it scales out satisfactorily to 512 CPU cores on the Polaris supercomputer at Argonne National Laboratory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Emulation of the calculations of final r -process abundance patterns with a neural network

This work explores the construction of a fast emulator for the calculation of the final pattern of nucleosynthesis in the rapid neutron capture process (the r-process). An emulator is built using a feed-forward artificial neural network (ANN). We train the ANN with nuclear data and relative abundance patterns. We take as input the β-decay half-lives and the one-neutron separation energy of the nuclei in the rare-earth region. The output is the final isotopic abundance pattern. In this work, we focus on the nuclear data and abundance patterns in the rare-earth region to reduce the dimension of the input and output space. We show that the ANN can capture the effect of the changes in the nuclear physics inputs on the final r-process abundance pattern in the adopted astrophysical conditions. We employ the deep ensemble method to quantify the prediction uncertainty of the neural network emulator. The emulator achieves a speed-up by a factor of about 20 000 in obtaining a final abundance pattern in the rare-earth region. The emulator may be utilized in statistical analyses such as uncertainty quantification, inverse problems, and sensitivity analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Probing the impact of oxygen negative ions on the self-organized pattern in 1 atm DC glow with liquid anode

In an atmospheric DC glow discharge with a liquid anode, the plasma anode glow attached to the grounded liquid surface under certain conditions self-organizes into coherent patterns. Optical emission spectroscopy revealed that the emission consists primarily of the second positive system of nitrogen, N 2 (C-B), whose excitation energy is low and sensitive to changes in the electron energy distribution. In addition to electrons, negative ions can accumulate in the anode sheath and affect the local space charge. It has been speculated that these negative ions play a role in pattern formation at the anode surface. In this work, the role of oxygen negative ions was explored. It was found that the formation of anode patterns requires at least a 7% volume fraction of oxygen in the ambient gas. Results showed that O 2 - is the dominant negative ion species in atmospheric DC glow discharge, with a density of ~10 12 cm -3 . While the presence of oxygen appears to be crucial for pattern formation, this study indicated that patterns still formed without geometric changes even when 62% of negative ions in the plasma were detached by a laser. This suggests that negative ions do not support the patterns, while oxygen's heating effect may induce instability at the anode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Surface deformation coupled with self-organized pattern on a liquid anode of 1 atm DC glow discharge

Intricate, self-organized plasma structures observed above the surface of a liquid anode of atmospheric DC glow discharge were found to give rise to coherent, organized surface deformation and mechanical wave formation at the plasma–liquid interface. This new phenomenon indicates that the liquid is closely coupled to the plasma by the anode sheath’s electrohydrodynamic (EHD) force. A scientific question then arises: Do surface perturbations, coupled with the nonuniform surface charge distribution, enhance the electric field and induce self-organization? Using the reflective background-oriented schlieren technique, the liquid surface profile under the plasma pattern was measured for the first time. The results show that surface distortions are driven by the repulsive Coulomb force of nonuniform net-negative surface charge acted by the anode sheath field. The impacts of various operating parameters on the patterns and surface waves were examined, revealing the significance of gas heating and liquid charge relaxation time in the pattern formation mechanism. Time-resolved dynamics of a pulsed DC discharge indicated that the surface deformation only appeared after the establishment of plasma patterns. Statistically, the surface wave under the plasma has high wave numbers (8000–16000 m −1 ) and small amplitudes ($<$ 10 µm), generally found in the capillary wave regime. Yet the motion of surface deformations is in tandem with the plasma pattern and exhibits a nondispersive nature of constant phase velocity (0.1–0.4 m s −1 ), suggesting the dominant role of EHD force over the surface tension in the observed surface wave. These results indicate that the deformed liquid surface is driven by the EHD force of the plasma sheath. Although they share a similar geometry, the deformation and wave dynamics of the liquid surface do not stimulate a plasma pattern. Importantly, the complex EHD coupling in the plasma–liquid system raises awareness and new challenges for plasma control engineering, and the quantitative characteristics of the nondispersive surface wave are informative for advancing relevant theory and modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Functional stimuli-responsive polymers on micro- and nano-patterned interfaces

Micro- and nano-patterned surfaces offer precise control over morphology and chemical composition, enhancing the stability, durability, and functionality of coating materials. When combined with stimuli-responsive polymers, these surfaces gain dynamic adaptability, enabling reversible binding, reusable sensing, and selective molecular capture. Furthermore, while recent review articles have explored various aspects of stimuli-responsive materials, from hydrogel patterns for bioanalytical applications to shape-morphing hydrogels for soft robotics and sensors, a comprehensive review focused on the integration of smart polymers with micro- or nano-patterned interfaces remains absent. This review addresses key surface patterning techniques, including soft lithography, colloidal lithography, and polymer brush photolithography, as well as advances in surface-initiated polymerization methods, such as surface-initiated controlled radical polymerization (SI-CRP). In addition, we discuss recent progress in integrating stimuli-responsive polymers with patterned surfaces to create advanced, functional materials.

Colloidal lithography↗
DOE OSTI2026

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗