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DOE OSTI2022

Minimum feature size control in level set topology optimization via density fields

A level set topology optimization approach that uses an auxiliary density field to nucleate holes during the optimization process and achieves minimum feature size control in optimized designs is explored. The level set field determines the solid-void interface and the density field describes the distribution of a fictitious porous material using the solid isotropic material with penalization. These fields are governed by two sets of independent optimization variables which are initially coupled using a penalty for hole nucleation. The strength of the density field penalization and projection is gradually increased during the optimization process to promote a 0-1 density distribution. In addition, a second penalty regulates the evolution of the density field in the void phase. The treatment of the density field combined with the second penalty mitigate the appearance of small design features. The minimum feature size of optimized designs is controlled by the radius of the linear filter applied to the density optimization variables. The structural response is predicted by the extended finite element method, the sensitivities by the adjoint method, and the optimization variables are updated by a gradient-based optimization algorithm. Numerical examples investigate the robustness of this approach with respect to algorithmic parameters and mesh refinement. The results show the applicability of the combined density level set topology optimization approach for both optimal hole nucleation and for minimum feature size control in 2D and 3D. This comes, however, at the cost of a more complex problem formulation and additional computational cost due to an increased number of optimization variables.

42 ENGINEERING↗

DOE OSTI2021

Cost and Time Effective Lithography of Reusable Millimeter Size Bone Tissue Replicas With Sub‐15 nm Feature Size on A Biocompatible Polymer

Abstract The ability to replicate the microenvironment of biological tissues creates unique biomedical possibilities for stem cell applications. Current fabrication methods are limited by either the control on feature size and shape, or by the throughput and size of the replicas. Here, a novel platform is reported that combines thermal scanning probe lithography (tSPL) with innovative methodologies for the low‐cost and high‐throughput nanofabrication of large area quasi‐3D bone tissue replicas with high fidelity, sub‐15 nm lateral precision, and sub‐2 nm vertical resolution. This bio‐tSPL platform features a biocompatible polymer resist that withstands multiple cell culture cycles, allowing the reuse of the replicas, further decreasing costs and fabrication times. The as‐fabricated replicas support the culture and proliferation of human induced mesenchymal stem cells, which display broad therapeutic and biomedical potential. Furthermore, it is demonstrated that bio‐tSPL can be used to nanopattern the bone tissue replicas with amine groups, for subsequent tissue‐mimetic biofunctionalization. The achieved level of time and cost‐effectiveness, as well as the cell compatibility of the replicas, make bio‐tSPL a promising platform for the production of tissue‐mimetic replicas to study stem cell‐tissue microenvironment interactions, test drugs, and ultimately harness the regenerative capacity of stem cells and tissues for biomedical applications.

Liu, Xiangyu↗

DOE OSTI2022

Hierarchical, Self-Assembled Metasurfaces via Exposure-Controlled Reflow of Block Copolymer-Derived Nanopatterns

Here, nanopatterning for the fabrication of optical metasurfaces entails a need for high-resolution approaches like electron beam lithography that cannot be readily scaled beyond prototyping demonstrations. Block copolymer thin film self-assembly offers an attractive alternative for producing periodic nanopatterns across large areas, yet the pattern feature sizes are fixed by the polymer molecular weight and composition. Here, a general strategy is reported that overcomes the limitation of fixed feature size by treating the copolymer thin film as a hierarchical resist, in which the nanoscale pattern motif is defined by self-assembly. Feature sizes can then be tuned by thermal reflow controlled locally by irradiative crosslinking or chemical alteration using lithographic ultraviolet light or electron beam exposure. Using blends of polystyrene-block-poly(methylmethacrylate) (PS-b-PMMA) with PS and PMMA homopolymer, we demonstrate both self-assembled PS grating and hexagonal hole patterns; exposure-controlled reflow is then used to reduce hole diameter by as much as 50% or increase PS grating linewidth by more than 180%. Transferring these nanopatterns, or their inverse obtained by a lift-off approach, into silicon yields structural colors that may be prescriptively controlled based on nanoscale feature size. Furthermore, patterned exposure enables area-selective feature size control, yielding uniform structural color patterns across centimeter square areas. Electron beam lithography is also used to show that the lithographic resolution of this selective-area control can be extended to the nanoscale dimensions of the self-assembled features. The exposure-controlled reflow approach demonstrated here takes a pivotal step towards fabricating complex, hierarchical optical metasurfaces using scalable self-assembly methods.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

Machine learning insights into microstructural origins of transport and mechanical properties in porous microstructures

Multifunctional porous materials are increasingly needed across various fields, but their complex microstructures create significant challenges due to the intricate microstructure-property relationships. This complexity, combined with limitations of traditional analysis methods, hinders efforts to understand and optimize microstructure–property relationships. Here, to address this, we integrate physics-based mesoscale modeling with interpretable machine learning (ML) to uncover how microstructural features govern effective diffusivity and elastic modulus. At constant porosity, we show diffusivity varies by over 150 × and modulus by ∼50 ×, highlighting the power of microstructure engineering. Statistical analysis reveals bimodal behavior in diffusivity and unimodal in modulus. ML identifies connectivity as the dominant factor, while modulus is also sensitive to domain size and feature interactions. Controlled simulations further highlight domain shape as a critical feature for modulus. This framework enables efficient exploration of microstructure-property correlations, offering new insights to guide the design of advanced porous materials.

Bicontinuous microstructure↗

DOE OSTI2024

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Direct Ink Write and Processing of Complex 3D Marine Compatible Structures with Calcium Carbonate Slurries

Ocean acidification heavily impacts marine ecosystems by reducing calcification. Many coral-algae symbiotic relationships are in jeopardy due to the destruction of coral reefs. Here, a ceramic ink compatible with the direct ink write additive manufacturing technique was formulated and used to print marine compatible structures that could grow algae and restore that relationship. A diacrylate polymer was mixed with calcium carbonate, a material that comprises a coral skeleton, to create a slurry with shear thinning properties. Rheology studies were conducted to confirm printing properties and characterize the slurry. Printed parts demonstrated strong control over print features, including size and infill design. Various infill patterns and percentages were attempted to optimize printability and potential algae growth. Thermogravimetric analysis helped determine a logical burnout and sintering procedure to avoid large cracking. This project developed a printable and sinter-able calcium carbonate ceramic slurry for complex marine-compatible structures and algae growth. This research was conducted in the support of the Eco Reef project.

36 MATERIALS SCIENCE↗

DOE OSTI2022

An Energetic Diagnostic of Tropical Cyclone Size in f –Plane Simulations

As a major feature of tropical cyclones (TCs), controlling factors of TC outer size or size scaling remains a fundamental scientific question. The Rossby deformation radius and a natural extent associated with potential intensity have been proposed as two scalings of TC size. But neither of them satisfactorily captures the sensitivity of TC size to sea surface temperature (SST) in idealized f-plane simulations. Inspired by the studies of the Hadley circulation, here we proposed a new TC scaling based on an energetic diagnostic scaling. TC size is primarily a ratio of the secondary circulation strength to subsidence velocity, further determined by the total atmospheric heating in the ascending area, the gross moist stability, the diabatic cooling, and the dry static stability. The former two is based on the moist energetic budget applied to the whole storm structure, while the latter two is based on the dry thermodynamic budget applied to the subsidence areas. The new scaling well captured the sensitivity of TC size to SST in idealized f-plane simulations, partly resulted from expanded ascending area, increased surface moisture deficit, and weakened subsidence with increased SST.

58 GEOSCIENCES↗

DOE OSTI2023

Transforming layered 2D mats into multiphasic 3D nanofiber scaffolds with tailored gradient features for tissue regeneration

Abstract Multiphasic scaffolds with tailored gradient features hold significant promise for tissue regeneration applications. Herein, this work reports the transformation of two‐dimensional (2D) layered fiber mats into three‐dimensional (3D) multiphasic scaffolds using a ‘solids‐of‐revolution’ inspired gas‐foaming expansion technology. These scaffolds feature precise control over fiber alignment, pore size, and regional structure. Manipulating nanofiber mat layers and Pluronic F127 concentrations allows further customization of pore size and fiber alignment within different scaffold regions. The cellular response to multiphasic scaffolds demonstrates that the number of cells migrated and proliferated onto the scaffolds is mainly dependent on the pore size rather than fiber alignment. In vivo subcutaneous implantation of multiphasic scaffolds to rats reveals substantial cell infiltration, neo tissue formation, collagen deposition, and new vessel formation within scaffolds, greatly surpassing the capabilities of traditional nanofiber mats. Histological examination indicates the importance of optimizing pore size and fiber alignment for the promotion of cell infiltration and tissue regeneration. Overall, these scaffolds have potential applications in tissue modeling, studying tissue‐tissue interactions, interface tissue engineering, and high‐throughput screening for optimized tissue regeneration.

Shahriar, S. M. Shatil↗

DOE OSTI2021

Meso-scale modelling of compressive fracture in concrete with irregularly shaped aggregates

This paper presents a meso-scale modelling framework to investigate the fracture process in concrete subjected to uniaxial and biaxial compression accounting for its mesostructural characteristics. 3D mesostructure of concrete consisting of coarse aggregates, mortar and interfacial transition zone between them was developed using an in-house code based on the Voronoi tessellation and splining method, which enables to generate the realistic-look aggregates with controllable structural features such as content, location, size and shape. Based on the generated 3D mesostructure, the concrete damage plasticity approach was employed to simulate the compressive fracture behaviour of concrete in terms of crack morphology and stress-strain response against the shape parameters of aggregate. Results indicate that the shape of aggregate has a negligible effect on compressive strength of concrete, which is highly associated with the random location and size distribution of aggregate. The aggregate irregularity has a significant influence on crack initiation and growth of concrete.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A coarse-grained simulation model for colloidal self-assembly via explicit mobile binders

Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet–droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed ‘colloidomers’, which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. Further, we explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Bimetallic Metal–Organic Framework Fe/Co-MIL-88(NH 2 ) Exhibiting High Peroxidase-like Activity and Its Application in Detection of Extracellular Vesicles

Metal–organic frameworks (MOFs) have many attractive features, including tunable composition, rigid structure, controllable pore size, and large specific surface area, and thus are highly applicable in molecular analysis. Depending on the MOF structure, a high number of un-saturated metal sites can be exposed to catalyze chemical reactions. In the present work, we report that by using both Co(II) and Fe(III) to prepare the MIL-88(NH 2 ) MOF, we can produce the bimetallic MOF that can catalyze the conversion of 3,3', 5,5"-tetramethylbenzidine (TMB) to a color product through reaction with H 2 O 2 at a higher reaction rate than the monometallic Fe-MIL-88(NH 2 ). The Michaelis constants (K m ) of the catalytic reaction for TMB and H 2 O 2 are 3-5 times smaller, and the catalytic constants (k cat ) are 5-10 times higher than those of the horse-radish peroxidase (HRP), supporting ultrahigh peroxidase-like activity. These values are also much more superior to those of the HRP-mimicking MOFs reported previously. Interestingly, the bimetallic MOF can be coupled with glucose oxidase (GOx) to trigger the cascade enzymatic reaction for highly sensitive detection of extracellular vesicles (EVs), a family of important biomarkers. Through conjugation to the aptamer that recognizes the marker protein on EV surface, the MOF can help isolate the EVs from biological matrices, which are subsequently labeled by GOx via antibody recognition. The cascade enzymatic reaction between MOF and GOx enables detection of EVs at a concentration as low as 7.8 × 10 4 particles/ml. Further, the assay can be applied to monitor EV secretion by cultured cells, and also can successfully detect the different EV quantities in the sera samples collected from cancer patients and healthy controls. Overall, we prove that the bimetallic Fe/Co-MIL-88(NH 2 ) MOF, with its high peroxidase-activity and high biocompatibility, is a valuable tool deployable in clinical assays to facility disease diagnosis and prognosis.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Biogeochemical fingerprinting of magnetotactic bacterial magnetite

Biominerals are important archives of the presence of life and environmental processes in the geological record. However, ascribing a clear biogenic nature to minerals with nanometer-sized dimensions has proven challenging. Identifying hallmark features of biologically controlled mineralization is particularly important for the case of magnetite crystals, resembling those produced by magnetotactic bacteria (MTB), which have been used as evidence of early prokaryotic life on Earth and in meteorites. In this work, we show that magnetite produced by MTB displays a clear coupled C–N signal that is absent in abiogenic and/or biomimetic (protein-mediated) nanometer-sized magnetite. We attribute the presence of this signal to intracrystalline organic components associated with proteins involved in magnetosome formation by MTB. These results demonstrate that we can assign a biogenic origin to nanometer-sized magnetite crystals, and potentially other biominerals of similar dimensions, using unique geochemical signatures directly measured at the nanoscale. This finding is significant for searching for the earliest presence of life in the Earth’s geological record and prokaryotic life on other planets.

58 GEOSCIENCES↗

DOE OSTI2024

Benchmarking of X‐Ray Fluorescence Microscopy with Ion Beam Implanted Samples Showing Detection Sensitivity of Hundreds of Atoms

Abstract Single impurities in insulators are now often used for quantum sensors and single photon sources, while nanoscale semiconductor doping features are being constructed for electrical contacts in quantum technology devices, implying that new methods for sensitive, non‐destructive imaging of single‐ or few‐atom structures are needed. X‐ray fluorescence (XRF) can provide nanoscale imaging with chemical specificity, and features comprising as few as 100 000 atoms have been detected without any need for specialized or destructive sample preparation. Presently, the ultimate limits of sensitivity of XRF are unknown – here, gallium dopants in silicon are investigated using a high brilliance, synchrotron source collimated to a small spot. It is demonstrated that with a single‐pixel integration time of 1 s, the sensitivity is sufficient to identify a single isolated feature of only 3000 Ga impurities (a mass of just 350 zg). With increased integration (25 s), 650 impurities can be detected. The results are quantified using a calibration sample consisting of precisely controlled numbers of implanted atoms in nanometer‐sized structures. The results show that such features can now be mapped quantitatively when calibration samples are used, and suggest that, in the near future, planned upgrades to XRF facilities might achieve single‐atom sensitivity.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Printed Targets with Micron-Scale Feature Patterns for the Study of Ablator Defects on OMEGA

As per present models, laser imprint and implosion symmetry are insufficient to account for observed performance degradation of direct-drive cryogenic fusion implosions. More and better data are needed on ablator defects as a source of hydrodynamic instability and mix. To investigate this, a series of OMEGA experimental campaigns is underway to study isolated target defects. Key requirements are systematic variation of the laser intensity and pulse shape at shot, with highly controlled defect type, geometry, and location. Here, given the need for sub-micron resolution and precise registration of multiple features, two-photon polymerization (TPP) printing was identified as an ideal method to fabricate these targets. TPP printing has enabled controlled formation of designed domes, divots, and vacuoles for studying the combined effect of size and proximity of these features on the hydro performance.

Two-photon polymerization printing↗

DOE OSTI2022

Investigation of the OECD/NEA PWR MOX/UO{sub 2} core transient benchmark using a coupled whole core pin-by-pin route in WIMS

This paper investigates the new CAMELOT coupling route developed in WIMS, which uses prepared tabulated cross-sections combined with the flux solver MERLIN module and the integrated sub-channel thermal hydraulics solver ARTHUR module to solve for the coupled core state. This coupling route is applied to the OECD/NEA pressurized water reactor (PWR) core transient benchmark exercise, involving 3-D neutronics and thermal-hydraulics analysis of a full-sized PWR core featuring MOX fuel at various core states, as well as simulating a control rod ejection transient. Analysis of the results for each part of the benchmark demonstrate that the high-resolution pin-by-pin analysis used in WIMS closely matches the other participants in the benchmark, with differences of between 20-200 pcm for k-effective, 1-2.5% RMS difference for assembly-averaged powers, 2-8% difference in rod worth calculations, < 200 ppm for calculations of critical boron concentration, zero difference in delayed neutron fraction calculation and a very close match for power response to the rod ejection transient. This is the first application of the WIMS-CAMELOT approach for the transient analysis of a full-sized reactor and as such further improvements such as reducing computational cost through parallelization, optimisation and memory reduction, are currently in active development. This paper demonstrates the accuracy and flexibility of the CAMELOT coupling route, providing a straightforward and consistent user image that can be easily used for a variety of modelling problems involving coupled neutronics and thermal-hydraulics. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2026

Structural Design of Bismuth Telluride Nanoplates through Process Variables

Binary pnictogen chalcogen compounds, primarily bismuth tellurides and selenides, are of great interest due to their applications in emerging quantum devices, as well as thermoelectric generators. The performance of bismuth telluride in these roles depends on its structure at the nanoscale, particularly the size, shape, and crystallinity of its nanocrystalline forms. However, current methods for controlling these features are often slow, inconsistent, or difficult to scale. Here, we demonstrate that through a solvothermal synthesis and hot injection process, precise control over the morphology of bismuth telluride nanoplates is possible with independent tuning of process variables, such as temperature and reaction time. We find that the nanoplate shape and internal porosity vary systematically with synthesis temperature and that the same morphological outcomes can be rapidly achieved at a fixed temperature by adjusting reaction duration. These results reveal that both the temperature and time can independently direct bismuth telluride morphological features, allowing for rapid, tunable synthesis strategies. Our approach offers a scalable framework, not only for bismuth telluride but also for related layered chalcogenides used in energy harvesting and quantum technologies.

Ackley, Jordan [Boise State Univ., ID (United Stat↗

DOE OSTI2023

EXPERIMENTAL AND MODELING STUDY OF MOLECULAR TRANSPORT PHENOMENA IN COMPLEX LIQUID MIXTURES USING COVALENT ORGANIC FRAMEWORK MEMBRANES

Currently, 10-15% of the world’s energy is consumed by chemical separations, and more than 80% of that is used to purify organic liquids and recover rare earth elements and critical minerals. Membrane nanofiltration presents an energy-efficient, cost-effective, and eco-friendly alternative to current separation technologies. These complex liquid environments require high- performance, chemically-resistant membrane materials. Recently discovered Covalent Organic Frameworks (COFs) possess desirable properties as membrane materials for complex liquid separations. COFs are highly crystalline, chemically and thermally stable, with tunable size and charge. COFs, especially two-dimensional highly crystalline COFs, possess narrow pore-size distribution and controlled porous structures. Two-dimensional COFs are also resistant to swelling, another feature beneficial in complex liquid separations. Molecular interactions in complex liquid systems often dictate final membrane performance, resulting in a discrepancy between designed and apparent COF properties. Understanding and resolving this discrepancy is critical in utilizing COF membranes as a viable alternative to energy-intensive separations. The primary objective of this thesis was to use a commercially available COF TpPa-1 as a platform to investigate how mixed solvent environment affects COF membrane performance via experimental and molecular modeling studies. Specifically, the effects of solution pH, solvent- solvent-solute interactions in mixed solvents, and COF chemistry were carefully examined on apparent TpPa-1 pore size and permeability and targeted solute rejection of COF membranes for neat and mixed solvents. Experimental COF filtration performance was compared and corroborated with modeling predication. Findings from this study will provide guidance for future COF design, synthesis, and desired functional COF membrane performance.

Barnes, Anastasia↗