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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Soft-Shear-Aligned Vertically Oriented Lamellar Block Copolymers for Template-Free Sub-10 nm Patterning and Hybrid Nanostructures

The template-free unidirectional alignment of lamellar block copolymers (l-BCPs) for sub-10 nm high-resolution patterning and hybrid multicomponent nanostructures is important for technological applications. Here we demonstrate a modified soft-shear directed self-assembly (SDSA) approach for aligning pristine l-BCPs and l-BCPs with incorporated polymer grafted nanoparticles (PGNPs), as well as the l-BCPs conversion to aligned gold nanowires, and hybrid of metallic gold nanowire and dielectric silica nanoparticle in the form of line-dot nanostructures. The smallest patterns have a half-pitch as small as 9.8 nm. In all cases, soft-shear is achieved using a high molecular mass polymer topcoat layer, with support on a neutral bottom layer. We also show that the hybrid line-dot nanostructures have a red-shifted plasmonic response in comparison to the neat gold nanowires. These template-free aligned BCPs and nanowires have potential use in nanopatterning applications and the line-dot nanostructures should be useful in the plasmonic sensing of biomolecules and other molecular species based on the plasmonic response of the nanowires.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Surfactant-Mediated Growth and Patterning of Atomically Thin Transition Metal Dichalcogenides

The role of additives in facilitating the growth of conventional semiconducting thin films is well-established. Apparently, their presence is also decisive in the growth of two-dimensional transition metal dichalcogenides (TMDs), yet their role remains ambiguous. In this work, we show that the use of sodium bromide enables synthesis of TMD monolayers via a surfactant-mediated growth mechanism, without introducing liquefaction of metal oxide precursors. We discovered that sodium ions provided by sodium bromide chemically passivate edges of growing molybdenum disulfide crystals, relaxing in-plane strains to suppress 3D islanding and promote monolayer growth. To exploit this growth model, molybdenum disulfide monolayers were directly grown into desired patterns using predeposited sodium bromide as a removable template. In conclusion, the surfactant-mediated growth not only extends the families of metal oxide precursors but also offers a way for lithography-free patterning of TMD monolayers on various surfaces to facilitate fabrication of atomically thin electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Field-Driven Out-of-Equilibrium Collective Patterns for Swarm Micro-Robotics

Soft robotics has been rapidly advancing, offering significant improvements over traditional rigid robotic systems through the use of compliant materials that enhance adaptability and interaction with the environment. However, current approaches face critical challenges, including the reliance on complex “top-down” fabrication techniques and the difficulty of wireless powering and control at the microscale. Swarm robotics introduces a paradigm shift, leveraging collective dynamics to achieve cooperative and adaptable behaviors among multiple robotic units. Inspired by nature, this “bottom-up” approach enables swarm robots to execute task-specific reconfigurations, enhancing flexibility and robustness. Field-driven active colloids emerge as a promising platform for swarm microrobotics, capable of self-propulsion and self-organization into dynamic collective patterns under external field excitation and manipulation. These systems mimic biologically inspired swarm behaviors, such as flocking and vortex formation, providing a versatile foundation for designing innovative swarm microrobots. Here, this review discusses the principles of electric and magnetic field-driven collective self-organization, focusing on the particle dynamics, the emergence of collective swarm patterns, and illustrative examples of functional swarm microrobots. It concludes with future perspectives on harnessing these systems for adaptive, scalable, and multifunctional microrobotic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2017

Shape-Specific Patterning of Polymer-Functionalized Nanoparticles

Chemically and topographically patterned nanoparticles (NPs) with dimensions on the order of tens of nanometers have a diverse range of applications and are a valuable system for fundamental research. Recently, thermodynamically controlled segregation of a smooth layer of polymer ligands into pinned micelles (patches) offered an approach to nanopatterning of polymer-functionalized NPs. Control of the patch number, size, and spatial distribution on the surface of spherical NPs has been achieved, however, the role of NP shape remained elusive. Here, we report the role of NP shape, namely, the effect of the local surface curvature, on polymer segregation into surface patches. For polymer-functionalized metal nanocubes, we show experimentally and theoretically that the patches form preferentially on the high-curvature regions such as vertices and edges. An in situ transformation of the nanocubes into nanospheres leads to the change in the number and distribution of patches; a process that is dominated by the balance between the surface energy and the stretching energy of the polymer ligands. The experimental and theoretical results presented in this work are applicable to surface patterning of polymer-capped NPs with different shapes, which then enables the exploration of patch-directed self-assembly, as colloidal surfactants, and as templates for the synthesis of hybrid nanomaterials.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Pattern recognition with magnonic holographic memory device

In this work, we present experimental data demonstrating the possibility of using magnonic holographic devices for pattern recognition. The prototype eight-terminal device consists of a magnetic matrix with micro-antennas placed on the periphery of the matrix to excite and detect spin waves. The principle of operation is based on the effect of spin wave interference, which is similar to the operation of optical holographic devices. Input information is encoded in the phases of the spin waves generated on the edges of the magnonic matrix, while the output corresponds to the amplitude of the inductive voltage produced by the interfering spin waves on the other side of the matrix. The level of the output voltage depends on the combination of the input phases as well as on the internal structure of the magnonic matrix. Experimental data collected for several magnonic matrixes show the unique output signatures in which maxima and minima correspond to specific input phase patterns. Potentially, magnonic holographic devices may provide a higher storage density compare to optical counterparts due to a shorter wavelength and compatibility with conventional electronic devices. The challenges and shortcoming of the magnonic holographic devices are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Microstencils to generate defined, multi-species patterns of bacteria

Microbial communities are complex heterogeneous systems that are influenced by physical and chemical interactions with their environment, host, and community members. Techniques that facilitate the quantitative evaluation of how microscale organization influences the morphogenesis of multispecies communities could provide valuable insights into the dynamic behavior and organization of natural communities, the design of synthetic environments for multispecies culture, and the engineering of artificial consortia. In this work, we demonstrate a method for patterning microbes into simple arrangements that allow the quantitative measurement of growth dynamics as a function of their proximity to one another. The method combines parylene-based liftoff techniques with microfluidic delivery to simultaneously pattern multiple bacterial species with high viability using low-cost, customizable methods. Furthermore, quantitative measurements of bacterial growth for two competing isolates demonstrate that spatial coordination can play a critical role in multispecies growth and structure.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Helicon antenna radiation patterns in a high-density hydrogen linear plasma device

Antenna radiation patterns in the vicinity of a helicon antenna are investigated in hydrogen plasmas produced in the MAGPIE linear plasma device. Using a uniform cold-plasma full-wave code, we model the wave physics in MAGPIE and find good agreement with experimental wave measurements. We show for the first time which antenna elements in a helicon device couple most strongly to the plasma and discuss the physical mechanism that determines this effect. Helicon wavefields in the near field of the antenna are best described in terms of the group velocity and ray direction, while far from the antenna, helicon wavefields behave like plane waves and are best described in terms of eigen-modes. In addition, we present recent 2D axis-symmetric full-wave simulations of the 120 kW helicon source in ProtoMPEX [Rapp et al., IEEE Trans. Plasma Sci. 44(12), 3456–3464 (2016); Caughman et al., J. Vac. Sci. Technol. Vac. Surf. Films 35, 03E114 (2017); and Goulding et al., Fusion Sci. Technol. 72(4), 588–594 (2017)] (ne∼ 5 × 1019 m−3, B0∼ 70 mT, and f= 13.56 MHz) where the antenna radiation patterns are evident, and we provide an interpretation of the numerical results using the ideas developed in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Interfacial electroneutrality controls transport of asymmetric salts through charge-patterned mosaic membranes

Membranes that selectively enhance target solute permeation while rejecting competing species are essential for precision separations. This study introduces charge-patterned mosaic membranes (CMMs) that selectively transport divalent asymmetric salts by leveraging a net-neutral membrane–solution interface. This mechanism, dictated by the charge ratio of positive and negative domains on the membrane surface and the balance of cations and anions in the salt, is supported by analytical, numerical, and experimental results. Analytical solutions identified cationic domain coverages (f + ) of 33%, 50%, and 66% as optimal for the selective transport of +2:−1 salts, +1:−1 salts, and +1:−2 salts, respectively, under conditions where the pattern size (L) is significantly larger than the Debye length. Numerical simulations and experiments using CMMs with alternating charged-stripes inkjet-printed onto nanostructure copolymer substrates confirmed these findings. By varying stripe widths to control f + , pressure-driven filtration experiments demonstrated selective enrichment of MgCl 2 and K 2 SO 4 at the predicted f + values, with deviations from these values leading to salt rejection. These results highlight the pivotal role of a net-neutral interface in enabling asymmetric salt enrichment. This study positions CMMs as a versatile platform for tuning ion selectivity, addressing challenges in resource recovery, water treatment, and precision separations.

additive manufacturing↗

DOE OSTI2021

Quantum pattern recognition algorithms for charged particle tracking

High-energy physics is facing a daunting computing challenge with the large datasets expected from the upcoming High-Luminosity Large Hadron Collider in the next decade and even more so at future colliders. A key challenge in the reconstruction of events of simulated data and collision data is the pattern recognition algorithms used to determine the trajectories of charged particles. The field of quantum computing shows promise for transformative capabilities and is going through a cycle of rapid development and hence might provide a solution to this challenge. This article reviews current studies of quantum computers for charged particle pattern recognition in high-energy physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Collective effects and pattern formation for directional locking of disks moving through obstacle arrays

We examine directional locking effects in an assembly of disks driven through a square array of obstacles as the angle of drive rotates from 0° to 90°. For increasing disk densities, the system exhibits a series of different dynamic patterns along certain locking directions, including one-dimensional or multiple-row chain phases and density-modulated phases. For nonlocking driving directions, the disks form disordered patterns or clusters. Here, when the obstacles are small or far apart, a large number of locking phases appear; however, as the number of disks increases, the number of possible locking phases drops due to the increasing frequency of collisions between the disks and obstacles. For dense arrays or large obstacles, we find an increased clogging effect in which immobile and moving disks coexist.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Modeling the formation of double rolls from heterogeneously patterned gels

Both stimuli-responsive gels and growing biological tissue can undergo pronounced morphological transitions from two-dimensional (2D) layers into 3D geometries. We derive an analytical model that allows us to quantitatively predict the features of 2D-to-3D shape changes in polymer gels that encompasses different degrees of swelling within the sample. We analyze a particular configuration that emerges from a flat rectangular gel that is divided into two strips (bistrips), where each strip is swollen to a different extent in solution. The final configuration yields double rolls that display a narrow transition layer between two cylinders of constant radii. To characterize the rolls' shapes, we modify the theory of thin incompatible elastic sheets to account for the Flory-Huggins interaction between the gel and the solvent. This modification allows us to derive analytical expressions for the radii, the amplitudes, and the length of the transition layer within a given roll. Furthermore, our predictions agree quantitatively with available experimental data. In addition, we carry out numerical simulations that account for the complete nonlinear behavior of the gel and show good agreement between the analytical predictions and the numerical results. Our solution sheds light on a stress focusing pattern that forms at the border between two dissimilar soft materials. Moreover, models that provide quantitative predictions on the final morphology in such heterogeneously swelling hydrogels are useful for understanding growth patterns in biology as well as accurately tailoring the structure of gels for various technological applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Nanoporous gold: a hierarchical and multiscale 3D test pattern for characterizing X-ray nano-tomography systems

Full-field transmission X-ray microscopy (TXM) is a well established technique, available at various synchrotron beamlines around the world as well as by laboratory benchtop devices. One of the major TXM challenges, due to its nanometre-scale resolution, is the overall instrument stability during the acquisition of the series of tomographic projections. The ability to correct for vertical and horizontal distortions of each projection image during acquisition is necessary in order to achieve the effective 3D spatial resolution. The effectiveness of such an image alignment is also heavily influenced by the absorption properties and strong contrast of specific features in the scanned sample. Here it is shown that nanoporous gold (NPG) can be used as an ideal 3D test pattern for evaluating and optimizing the performance of a TXM instrument for hard X-rays at a synchrotron beamline. Unique features of NPG, such as hierarchical structures at multiple length scales and high absorbing capabilities, makes it an ideal choice for characterization, which involves a combination of a rapid-alignment algorithm applied on the acquired projections followed by the extraction of a set of both 2D- and 3D-descriptive image parameters. This protocol can be used for comparing the efficiency of TXM instruments at different synchrotron beamlines in the world or benchtop devices, based on a reference library of scanned NPG samples, containing information about the estimated horizontal and vertical alignment values, 2D qualitative parameters and quantitative 3D parameters. The possibility to tailor the ligament sizes of NPG to match the achievable resolution in combination with the high electron density of gold makes NPG an ideal 3D test pattern for evaluating the status and performance of a given synchrotron-based or benchtop-based TXM setup.

36 MATERIALS SCIENCE↗

DOE OSTI2017

An approach to online network monitoring using clustered patterns

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regard to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Integrating Nano-patterned Ferromagnetic and Ferroelectric Thin Films for Electrically Tunable RF Applications

Tunable radio frequency (RF) components are pivotal elements in frequency-agile and multifunctional systems. However, there is a technical barrier to achieve miniaturized fully electrically tunable RF components. This paper provides and demonstrates the efficacy of a first unique design methodology in developing fully electrically tunable RF components by integrating ferromagnetic (e.g., Permalloy) and ferroelectric (e.g., Lead Zirconate Titanate: PZT) thin films patterns. Permalloy thin film has been patterned in nanometer scale to improve its ferromagnetic resonance frequency (FMR) for RF applications. Tunable inductors are developed with the utilization of different thickness of Permalloy thin film, which show over 50% increment in inductance and over 4% in tunability with DC current. More tunability can be achieved with multiple layers of Permalloy thin film and optimized thickness. A fully electrically tunable slow wave RF transmission line with simultaneously variable inductance and capacitance density has been implemented and thoroughly investigated for the first time. Measured results show that a fixed phase shift of 90° can be achieved from 1.5 GHz to 1.85 GHz continuously by applying external DC current from 0 to 200 mA and external DC voltage from 0 to 15 Volts, respectively.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2020

An Analytical Model for the Tension-Shear Coupling of Woven Fabrics with Different Weave Patterns under Large Shear Deformation

It is essential to accurately describe the large shear behavior of woven fabrics in the composite preforming process. An analytical model is proposed to describe the shear behavior of fabrics with different weave patterns, in which tension-shear coupling is considered. The coupling is involved in two parts, the friction between overlapped yarns and the in-plane transverse compression between two parallel yarns. By introducing the concept of inflection points of a yarn, the model is applicable for fabrics with different weave patterns. The analytical model is validated by biaxial tension-shear experiments. A parametric study is conducted to investigate the effects of external load, yarn geometry, and weave structure on the large shear behavior of fabrics. The developed model can reveal the physical mechanism of tension-shear coupling of woven fabrics. Moreover, the model has a high computational efficiency due to its explicit expressions, thus benefiting the material design process.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Deep Learning Modeling Framework to Capture Mixing Patterns in Reactive-Transport Systems

Prediction and control of chemical mixing are vital for many scientific areas such as subsurface reactive transport, climate modeling, combustion, epidemiology, and pharmacology. Due to the complex nature of mixing in heterogeneous and anisotropic media, the mathematical models related to this phenomenon are not analytically tractable. Numerical simulations often provide a viable route to predict chemical mixing accurately. However, contemporary modeling approaches for mixing cannot utilize available spatial-temporal data to improve the accuracy of the future prediction and can be compute-intensive, especially when the spatial domain is large and for long-term temporal predictions. To address this knowledge gap, in this work we will present in this paper a deep learning (DL) modeling framework applied to predict the progress of chemical mixing under fast bimolecular reactions. This framework uses convolutional neural networks (CNN) for capturing spatial patterns and long short-term memory (LSTM) networks for forecasting temporal variations in mixing. By careful design of the framework—placement of non-negative constraint on the weights of the CNN and the selection of activation function, the framework ensures non-negativity of the chemical species at all spatial points and for all times. Our DL-based framework is fast, accurate, and requires minimal data for training. The time needed to obtain a forecast using the model is a fraction (≈ O(-6)) of the time needed to obtain the result using a high-fidelity simulation. To achieve an error of 10% (measured using the infinity norm) for capturing local-scale mixing features such as interfacial mixing, only 24% to 32% of the sequence data for model training is required. To achieve the same level of accuracy for capturing global-scale mixing features, the sequence data required for model training is 64% to 70% of the total spatial-temporal data. Hence, the proposed approach—a fast and accurate way to forecast long-time spatial-temporal mixing patterns in heterogeneous and anisotropic media—will be a valuable tool for modeling reactive-transport in a wide range of applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Linking basin-scale and pore-scale gas hydrate distribution patterns in diffusion-dominated marine hydrate systems: DIFFUSION-DRIVEN HYDRATE GROWTH IN SANDS

The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1 to 20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two- dimensional and basin-scale three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. As a result, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial.

03 NATURAL GAS↗