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DOE OSTI2026

Self-aligned heterogeneous quantum photonic integration

Integrated quantum photonics holds significant promise for scalable photonic quantum information processing, quantum repeaters, and quantum networks, but its development is hindered by the mismatch between materials hosting high-quality quantum emitters and those compatible with mature photonic technologies. Heterogeneous integration offers a potential solution to this challenge, yet practical implementations have been limited by inevitable insertion losses at material interfaces. Here, we present a self-aligned heterogeneous quantum photonic integration approach that enables near-unity coupling efficiency at the interface. To showcase our approach, we demonstrate Purcell enhancement of a silicon vacancy (SiV) center in diamond induced by a heterogeneous photonic crystal cavity defined by titanium dioxide (TiO 2 ), as well as optical spin control and readout via a TiO 2 photonic circuit. We further show that, when combined with inverse photonic design, our approach enables efficient and broadband collection of single photons from a color center into a heterogeneous waveguide. Our approach is not restricted to SiV centers or TiO 2 ; it has the potential to be broadly applied to integrate diverse solid-state quantum emitters with thin-film photonic devices where conformal deposition is possible. Together, these results establish a practical route to scalable quantum photonic integrated circuits that combine high-quality quantum emitters with technologically mature photonic platforms.

36 MATERIALS SCIENCE↗

NASA NTRS1990

Experimental Investigations of Low-Energy (4 to 40 eV) Collisions of O - ( 2 P) Ions and O( 3 P) Atoms With Surfaces

Using a newly-developed, magnetically confined source, low-energy, ground state oxygen negative ions and neutral atoms are generated. The energy range is variable, and atom and neutrals have been generated at energies varying from 2 eV to 40 eV and higher. It was found that the interaction of these low-energy species with a solid magnesium fluoride target leads to optical emissions in the (at least) visible and infrared regions of the spectrum. Researchers describe y details of the photodetachment source, and present spectra of the neutral and ion glows in the wavelength range 250 to 850 nm (for O - ) and 600 to 850 nm (for O), and discuss the variability of the emissions for incident energies between 4 and 40 eV.

A Chutjian↗

DOE OSTI2026

Interfacial Adhesion Mechanism of Anionic Polyelectrolyte Brushes Induced by Oppositely Charged Macromolecular Counterions

Abstract Polyelectrolyte brushes are widely used as model systems for investigating electrostatic interactions at soft interfaces and to achieve exceptional lubrication properties. Previous studies have primarily focused on their behavior in the presence of multivalent counterions, which induce brush collapse, ionic crosslinking, and pronounced changes in interfacial structures. However, interactions between polyelectrolyte brushes and oppositely charged macromolecular counterions, such as polycations, remain poorly understood. Here, we prepare well-defined polystyrene sulfonate (PSS) brushes fabricated via surface-initiated grafting and employ surface forces apparatus measurements to investigate their interactions with oppositely charged polycations. In contrast to multivalent ions, polycations do not induce noticeable brush collapse, but instead generate significant adhesion between symmetric PSS brush layers. This adhesion increases with both contact time and applied load, eventually reaching a steady plateau, indicating that the interaction is governed not simply by electrostatic screening but by the gradual formation of polycation-mediated bridging under confinement. Furthermore, the introduction of monovalent Na+ ions disrupts the adhesive interaction even at very low concentrations, suggesting that the bridging function of the adsorbed polycation is highly sensitive to competitive ionic screening. In comparison, measurements with trivalent counterions reveal the expected brush collapse behavior but minimal dependence of adhesion on contact time, highlighting a clear mechanistic distinction from the polymeric counterion case. Collectively, these results demonstrate that molecular size, configurational restriction, and confinement-induced rearrangement, rather than charge valency alone, govern the interaction behavior of macromolecular counterions at brush interfaces. This work provides new insight into the molecular origins of adhesion and the regulation of interfacial interactions in charged polymer brush systems.

Park, Jinwoo [Argonne National Laboratory , , , ,;↗

NASA NTRS1999

Fifth International Microgravity Combustion Workshop

On behalf of the NASA Headquarters Microgravity Research Division and the Microgravity Combustion Science Discipline Working Group, we are pleased to present these proceedings of the Fifth International Microgravity Combustion Workshop. At the time we go to press we expect to welcome to the workshop over 250 presenters and participants from U.S. academia, industry, and government; and from at least 8 international partner countries. We come together for this workshop at the beginning of the International Space Station era, where the future of microgravity combustion science programs will unfold over the next few years. As we accelerate our preparations for the ISS, this book and the growing literature base cited herein provide a summary of the accomplishments of approximately forty space-flight experiment-missions (plus nearly countless drop tests and aircraft parabolas) and a valuable resource for the new experiment ideas of the future.

Kurt R Sacksteder↗

NASA NTRS2026

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗

DOE OSTI2024

RMCProfile7 : reverse Monte Carlo for multiphase systems

This work introduces a completely rewritten version of the programRMCProfile(version 7), big-box, reverse Monte Carlo modelling software for analysis of total scattering data. The major new feature ofRMCProfile7is the ability to refine multiple phases simultaneously, which is relevant for many current research areas such as energy materials, catalysis and engineering. Other new features include improved support for molecular potentials and rigid-body refinements, as well as multiple different data sets. An empirical resolution correction and calculation of the pair distribution function as a back-Fourier transform are now also available.RMCProfile7is freely available for download at https://rmcprofile.ornl.gov/.

Chemistry↗

DOE OSTI2024

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗

DOE OSTI2025

High-Fidelity Building Emulator for Integrated Comfort and Energy Analysis using EnergyPlus and Radiance

The growing need for smart, energy-efficient, and occupant-centric buildings has created a demand for advanced control systems that can optimize building operations to balance energy savings, demand flexibility, and comfort. However, current building energy simulation tools, such as EnergyPlus, have limitations that hinder the development and evaluation of these complex control systems. To address this challenge, we introduce a high-fidelity building emulator that dynamically couples EnergyPlus with Radiance for enhanced daylight modeling. The introduced workflow allows researchers and practitioners to rapidly develop and evaluate innovative control solutions. An example study looking at a south-facing office zone revealed up to 67% deviation in predicted light levels, which can significantly impact building assessment.

Yu, Tammie↗

DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗

DOE OSTI2025

First multi-institutional systematic comparison of the neutron ambient dose equivalent produced by proton therapy systems

Objective. Isochronous cyclotrons, synchrocyclotrons, and synchrotrons are used to accelerate protons for proton therapy. An accurate measurement of neutron doses generated by these accelerators and associated delivery systems and its clinical relevance requires systematic protocols and proper neutron dosimetry for a meaningful assessment. We present the first comprehensive comparison of neutron ambient dose equivalent (H*(10)) produced by clinically operational proton therapy systems. Approach. Treatment plans with 10 cm modulation-depth and ranges of 10 cm (R10M10) and 25 cm (R25M10) were created to cover a 10 × 10 × 10 cm 3 water target. The pencil beam scanning proton therapy machines studied were: two gantry-mounted synchrocyclotrons (Hyperscan, Mevion, half-gantry), two isochronous cyclotrons (ProBeam, Varian, full-gantry), one isochronous cyclotron (Proteus, IBA, full-gantry), and two synchrotrons (PROBEAT, Hitachi, full- and half-gantry). Proton beams were delivered to 30 × 30 × 40 cm 3 plastic water phantoms. WENDI-II and LUPIN-BF3-NP neutron rem-meters were positioned at three angles (0°, 45°, 90°) relative to the beam direction to measure the neutron H*(10) at distances between 50–300 cm from the isocenter. Main results. H*(10) showed dependence on beam energy, machine type, and measurement location. The highest reading was for the gantry-mounted synchrocyclotron, whereas other systems produced approximately comparable neutron doses. In all cases, the H*(10) reduced with distance from the isocenter. The H*(10) drop at 2 m distance compared to that at 0.5 m was a factor of ∼5 for the gantry-mounted synchrocyclotron whereas in other systems the decrease was a factor of 10. The WENDI-II device suffered from dead-time-associated under-estimation of the dose by a factor of ∼2–3 under the synchrocyclotron beam due to its high dose-per-pulse. However, WENDI-II and LUPIN-BF3-NP results were within reasonable agreement in isochronous cyclotron and synchrotron beams, indicating that both devices are suitable for those systems. Significance. Neutron H*(10) is dependent on various parameters including beam energy, measurement location, as well as machine design. Caution must be exercised in choosing the appropriate neutron-dose-measurement device to be used for low-duty-factor, particularly in high-instantaneous-rate proton delivery systems. By delivering the same volumetric proton dose across different machines, this work provides a benchmark for inter-system comparisons and serves as a foundation for future studies.

LUPIN↗

DOE OSTI2026

Selectivity mechanisms of ion intercalation in Prussian blue analogs

Prussian blue analogs (PBAs) are a family of materials with facile, reversible, and selective ion transport capability for various ions via electrochemical intercalation, owing to their vacancy structure. The large tunable compositional space of PBAs allows for manipulation of intercalation behavior and selectivity by controlling structural vacancy level through choice of transition metal centers and modifications to the synthesis process. However, a lack of understanding of the mechanisms of ion selectivity hinders the material’s design process. Here, for this work, we investigated the origins of ion selectivity using a model PBA, copper hexacyanoferrate, and focused on eight technologically and biologically prominent ions, for which we determined a sequence of selectivity: Rb + > K + > Na + > Ba 2+ > Sr 2+ ≈ Ca 2+ > Mg 2+ > Li + . We provide electrochemical, structural, and redox evidence of strong correlation between the ion identity, the dominant charge-compensating redox, and preferred occupancy site. Specifically, using synchrotron anomalous X-ray diffraction (AXRD), we reveal that monovalent ions exhibit significant association with the corner sites of the unit cell and iron redox, whereas divalent ions display affinity toward the center site with higher ratios of copper redox. Informed by selectivity results, we applied CuHCFe to Li purification and achieved 99.9% purity. Our findings demonstrate an approach to elucidating ion intercalation behavior in order to distinguish and manipulate material properties to optimize separation performance.

Prussian blue analog↗

DOE OSTI2026

Improved nylon polymerization using amide diads

Nylons, a major class of synthetic polyamides, are widely used due to their excellent mechanical strength, thermal stability, and chemical resistance. Conventional nylon production relies on the polymerization of lactams or stoichiometric nylon salts. However, applying these approaches to unconventional precursors such as bio-derived glutaric acid produces polymers with low molecular weight and limited applications. To address these challenges, we demonstrated that chemically-synthesized nylon diads enable the production of higher-molecular-weight polyamides compared with traditional salts. We then identified a biosynthetic approach using amide synthetases to convert unprotected bifunctional substrates into nylon-relevant diads. Using a cofactor regeneration system, enzymatic diad synthesis was scaled to produce sufficient material for laboratory-scale characterization and solid-state polymerization. Amide synthetases demonstrated broad substrate scope, catalyzing the regioselective assembly of diverse nylon-relevant diacids, diamines, and ω-amino acids. This strategy offers a novel route to synthesize challenging nylon monomers and advances production of bioderived nylons.

Qian, Liangyu [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2026

Validating a Dynamic PWR Safety and Security Model?

Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

DOE OSTI2025

Dynamic nanodomains dictate macroscopic properties in lead halide perovskites

Lead halide perovskites have emerged as promising materials for solar energy conversion and X-ray detection owing to their remarkable optoelectronic properties. However, the microscopic origins of their superior performance remain unclear. Here we show that low-symmetry dynamic nanodomains present in the high-symmetry average cubic phases, whose characteristics are dictated by the A-site cation, govern the macroscopic behaviour. We combine X-ray diffuse scattering, inelastic neutron spectroscopy, hyperspectral photoluminescence microscopy and machine-learning-assisted molecular dynamics simulations to directly correlate local nanoscale dynamics with macroscopic optoelectronic response. Our approach reveals that methylammonium-based perovskites form densely packed, anisotropic dynamic nanodomains with out-of-phase octahedral tilting, whereas formamidinium-based systems develop sparse, isotropic, spherical nanodomains with in-phase tilting, even when crystallography reveals cubic symmetry on average. We demonstrate that these sparsely distributed isotropic nanodomains present in formamidinium-based systems reduce electronic dynamic disorder, resulting in a beneficial optoelectronic response, thereby enhancing the performance of formamidinium-based lead halide perovskite devices. By elucidating the influence of the A-site cation on local dynamic nanodomains, and consequently, on the macroscopic properties, we propose leveraging this relationship to engineer the optoelectronic response of these materials, propelling further advancements in perovskite-based photovoltaics, optoelectronics and X-ray imaging.

Materials Science↗

NASA NTRS1978

ITOS Power System Design

A brief description of the ITOS power systems is presented. The descriptions are from viewgraphs shown to the participants of the Workshop. A block diagram of ITOS power supply subsystem is presented along with graphs representing: ITOS voltage limit versus temperature; and battery charge-discharge current profiles over an orbit period.

A F Obenschain↗

DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Solvent-Free Preparation of High Energy, Binder-Free Electrodes Enabled by Dry Compressible Holey Graphene

Graphene is an atomically thick sheet consisting of a graphitic carbon network with excellent mechanical strength, electrical and thermal conductivity, and chemical stability. Holey graphene, a structural derivative of graphene, has an array of through-the-thickness holes across the lateral surface of the nanosheet. The presence of these holes has minimal detrimental effect on the graphene properties and leads to enhanced performance in applications such as electronics, sensors, and energy storage. For example, these holes allow more facile cross-plane ion and gas transport than intact graphene, making holey graphene an ideal electrode material for electrochemical energy storage. This presentation will focus on the ability of holey graphene to be compression molded into robust articles or architectures under solvent-free conditions without the need for potentially parasitic binders. The unique dry compressibility of holey graphene has enabled facile fabrication of high mass loading electrodes with both high density and high porosity, which have found use in supercapacitors and various high-energy battery systems such as lithium-oxygen, lithium-sulfur, and lithium-selenium batteries.

Yi Lin↗

DOE OSTI2025

Physicochemical and biological characterization of a bispecific antibody in a CrossMab/KIH format that targets EGFR and VEGF-A

Introduction Bispecific antibodies (BsAbs) are a class of antibody therapeutics engineered in various molecular formats to bind two distinct antigens and potentially mediate multiple biological effects. These molecular formats are tailored to mediate specific mechanisms of action and possess unique physicochemical and biological properties that are necessary to assure product quality. In ovarian cancer (OC), both EGFR- and VEGF-A-mediated signaling pathways are often upregulated and cooperate to promote tumor growth and angiogenesis. Thus, inhibiting of EGFR- and VEGF-A pathways with a BsAb may provide synergistic anti-tumor activity. Methods Using publicly available sequences and applying immunoglobulin domain crossover (CrossMab) and knobs-into-holes (KIH) technologies, we generated a BsAb to simultaneously bind EGFR and VEGF-A (designated as anti-EGFR/VEGF-A BsAb). This BsAb served as a model for physiochemical and biological characterization of quality attributes that would be critical for the BsAb’s mechanisms of action. Our goal was to gain fundamental insights into BsAbs designed to target a receptor with one arm and a soluble ligand with the other, to support bioassay development and inform quality control strategies. Results Our data demonstrated that the CrossMab/KIH platform successfully produced a correctly assembled BsAb during cell culture. Characterization confirmed that the anti-EGFR/VEGF-A BsAb bound both EGFR and VEGF-A with comparable activity and affinity to the respective parental monoclonal antibodies. Functionally, the BsAb disrupted both EGF/EGFR and VEGF-A/VEGFR2 signaling pathways in OC and human umbilical vein endothelial cell (HUVEC) models. Furthermore, the BsAb effectively blocked angiogenic signaling driven by VEGF-A secreted from OC cells in a paracrine manner. Discussion Based on the combinatorial mechanism of action and our characterization findings, we concluded that two or more bioassays may be needed to accurately assess the activity of both arms of this type of BsAb.

Immunology↗