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Results for “programmable synthesis”

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 OSTI2026

Effect of Thermodynamic and Environmental Factors on Crystallization of DNA‐Origami Superlattices

The directed self‐assembly of nanoscale materials into ordered superlattices presents a powerful strategy for creating next‐generation materials with programmable mechanical, optical, and photonic properties. Deoxyribonucleic acid (DNA) origami has emerged as a versatile scaffold for encoding nanoscale geometry and guiding the crystallization of complex 3D architectures. However, a systematic understanding of the parameters that govern the efficiency and quality of superlattice formation remains limited. In this study, we utilize octahedral DNA nanoscale frames as a model system to investigate the relative influence of key factors, including buffer composition, ionic strength, frame concentration, and thermal annealing protocols, on the size, order, and reproducibility of the resulting superlattices. Our findings provide a quantitative framework to rationally optimize DNA‐based assembly pathways. Structural characterization via small‐angle x‐ray scattering (SAXS), scanning electron microscopy (SEM), and optical microscopy validates the quality and fidelity of the assembled lattices. Moreover, by templating these DNA frameworks into inorganic replicas, we establish general design principles that extend beyond biomolecular systems, providing a foundation for the synthesis of programmable materials in broader nanofabrication contexts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Programmable Phase Selection between Altermagnetic and Noncentrosymmetric Polymorphs of MnTe on InP via Molecular Beam Epitaxy

Phase selecting nearly degenerate crystalline polymorphs during epitaxial growth can be challenging yet critical to targeting physical properties for specific applications. Here, we establish how phase selectivity of altermagnetic and noncentrosymmetric polymorphs of MnTe can be programmed by subtle changes to the surface of lattice-matched InP substrates in molecular beam epitaxy growth. Bulk altermagnetic MnTe is thermodynamically stable in the hexagonal NiAs-structure and is synthesized here on the polar (111)A surface (In-terminated) of InP, while the noncentrosymmetric, cubic ZnS-structure with wide band gap (>3 eV), which epitaxially matches III–V materials, is stabilized on the (111)B surface (P-terminated). Electron microscopy, X-ray photoemission spectroscopy, and reflection high-energy electron diffraction indicate that phase selection is triggered at the interface and proceeds along the growing surface. First-principles calculations suggest that interfacial termination and strain have a significant effect on the interfacial energy; stabilizing the NiAs polymorph on the In-terminated surface and the ZnS structure on the P-terminated surface. Here, selectively grown, high-quality, phase pure films of both MnTe polymorphs will enable our understanding of the novel properties of these materials, thereby facilitating their use in new applications ranging from spintronics to microelectronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Programmed synthesis of mesoporous protein crystals in cellular reactors

Protein crystals are naturally derived mesoporous materials with versatile structures and physicochemical properties. Here we introduce an intracellular synthesis platform that enables controllable and programmable protein crystallization. In live cells, we show that, after initial nucleation, steady protein expression governs crystal growth, yielding predictable, tunable dynamics in live cells. Exploiting this feature, we combined HaloTag and click chemistries to achieve modular, programmable immobilization of diverse guest materials with spatial patterning down to ~100 nm resolution. We further demonstrated the sequential release of immobilized materials in physiologically relevant fluids. As a proof of concept, we programmed particles to carry human fibroblast growth factors in distinct layers, which elicited designed oscillatory Akt signalling patterns in cell culture. Finally, this work outlines a programmable method for producing mesoporous materials, with possible applications in catalysis and biomedicine.

Yang, Hongru [Johns Hopkins Univ., Baltimore, MD (↗
DOE OSTI2025

Genetic control of morphological transitions in a coacervating protein template

Nature routinely exploits liquid–liquid phase separation (LLPS) of proteins to control the assembly and mineralization of hybrid materials. Here, we show that fusion of the Car9 silica-binding peptide to an elastin-like polypeptide (ELP) yields temperature- and sequence-programmable soft matter templates for the synthesis of silicified architectures ranging in size from nanometers to micrometers. Specifically, we demonstrate unprecedented control over the diameter of silica nanoparticles (SiNP) in the 30–60 nm range with 4 nm precision, show that a single arginine residue (R4) in the Car9 sequence underpins the transition from micelles to proteinosomes, and find that substitutions in other basic residues modulate electrostatic repulsion and solvation to enable access to kinetically trapped species. These structures, which include interconnected micelles, small (∼200 nm) and large (>5 µm) vesicles, are readily visualized by SEM imaging following silicification. Molecular dynamics (MD) simulations and AlphaFold predictions reveal that mutations in positively charged residues alter interfacial packing, hydration, and conformational freedom of the silica-binding segments. Overall, our results establish sequence and thermal energy as synergistic levers for morphological control across length scales using solid-binding ELPs and establish mineralization as a powerful tool to visualize the structure of dynamic soft matter assemblies.

hierarchy↗
DOE OSTI2025

Code Generators for Floating-Point Unit Design in Integrated Circuits (OpenFloat) v1.0

This IP provides a comprehensive set of code generators for various floating-point units (FPUs) essential for integrated circuit design and integration, targeting a broad spectrum of applications, including machine learning and scientific computing. The suite includes FP adders, multipliers, subtractors, dividers, reciprocals, exponentials, square roots, trigonometric functions (sine, cosine, arctangent), and more. It supports customizable hardware design parameters, such as precision (16, 32, 64, and 128 bits) and pipeline depths, offering users enhanced flexibility and productivity. The generated code is in an industry-standard hardware description language, ensuring compatibility with standard design flows, including simulation, verification, synthesis, and implementation on both field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs).

Shalf, JohnM. [Lawrence Berkeley National Laborato↗
NASA NTRSDate not supplied

Leveraging High-Level Synthesis to Migrate Motor Control Algorithms From Microcontroller to FPGA

As motor control algorithms become increasingly complex, traditional microcontroller-based implementations are reaching computational limits that prevent the controller from operating at the required speed. This paper presents a novel workflow leveraging High-Level Synthesis (HLS) to migrate motor control algorithms from a microcontroller implementation to a Field-Programmable Gate Array (FPGA) implementation. The proposed approach utilizes the free Vitis HLS software to automatically convert Embedded Coder-generated C code from a Simulink model into Hardware Description Language (HDL) code suitable for FPGA deployment.

FPGA↗
NASA NTRSDate not supplied

Leveraging High-Level Synthesis to Migrate Motor Control Algorithms From Microcontroller to FPGA

As motor control algorithms become increasingly complex, traditional microcontroller-based implementations are reaching computational limits that prevent the controller from operating at the required speed. This paper presents a novel workflow leveraging High-Level Synthesis (HLS) to migrate motor control algorithms from a microcontroller implementation to a Field-Programmable Gate Array (FPGA) implementation. The proposed approach utilizes the free Vitis HLS software to automatically convert Embedded Coder-generated C code from a Simulink model into Hardware Description Language (HDL) code suitable for FPGA deployment.

FPGA↗
DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗
DOE OSTI2025

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

Schulte, Jan-Frederik [Purdue U.] (ORCID:000000034↗
DOE OSTI2025

Two-Dimensional Silk Crystal Films as Matrix Layer for High-Performance Microelectronics

This study explores a bio-inspired approach for memristive devices by combining Keggin-type polyoxometalates (POMs)-[SiW 12 O 40 ] 4 (POM-T) and [PW 12 O 40 ] 3 (POM-P), with silk fibroin (SF) to create 2D SF–POM layers on highly ordered pyrolytic graphite (HOPG) as resistive switching layers for memristors. We propose that the ordered SF layer template 0D POMs facilitate the formation of conductive filaments, thereby enhancing the variability of the manufactured memristors. AFM analysis revealed that both SF and SF–POM layers shared similar morphologies, while SF–POM–T formed larger aggregates, likely due to the stronger acidity of POM-T, which probably caused SF to aggregate and alter its secondary structure. Scanning Kelvin probe microscopy (SKPM) revealed that POMs reduced the contact potential difference of HOPG, resulting in lower work functions. Compared to an SF device, the SF–POM–P device showed improved memristive behavior, with a larger current gap and good repeatability over multiple sweeps; whereas the SF–POM–T device did not exhibit memristor activity, likely due to acidity-induced disruption of the SF template’s order and CF formation. More importantly, SF–POM–P devices also demonstrated programmable memristive states. Finally, combining simulation-driven memristor modeling, we showcase a co-design workflow for advancing bioinspired memristors through new materials design, synthesis, and device modeling and development.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Alumina–Titania Nanolaminate Condensers for Hot Programmable Catalysis

Nanolaminates composed of thin alternating layers of Al2O 3 and TiO 2 (ATO) were engineered by using atomic layer deposition as the dielectric material for a Pt-on-carbon catalytic condenser. Investigation assessed synthesis parameters including the deposition temperature, Al 2 O 3 and TiO 2 layer thicknesses, total number of layers, and a capping Al 2 O 3 layer on the maximum charge accumulation in the Pt catalyst. The highest capacitance ATO configuration demonstrated a specific capacitance of ∼1200 nF/cm 2 with working voltages of ±5 V, enabling the storage of 4 × 10 13 electrons or holes per cm 2 at room temperature. The ATO devices exhibited enhanced capacitance at elevated temperatures of up to 400 °C, suggesting the suitability of these materials for high-temperature applications. Adsorption of carbon monoxide on the Pt/C-ATO device characterized by grazing incidence infrared spectroscopy showed changes in the surface binding energy of 13.1 ± 0.8 kJ/mol for an applied external voltage bias of ±1 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Polymer-Grafted Nanoparticles as All-in-One Nanoplatforms

Polymer-grafted nanoparticles (PGNPs) represent a versatile class of hybrid nanomaterials, in which nanoparticle cores and tethered polymer coronas are integrated into structurally programmable building blocks. Rapid advances in nanoparticle surface functionalization and surface-initiated polymerization have enabled increasingly precise control over the nanoparticle core composition and brush architecture, greatly expanding the accessible structural and functional landscape of PGNPs. This review summarizes recent progress in the modular design and structural regulation of PGNPs, with an emphasis on nanoparticle platforms and associated surface functionalization strategies, polymer brush synthesis and architectural control, and the structure−property relationships that govern PGNP behavior. Emerging applications are further highlighted, including additive manufacturing, self-healing materials, membrane-based gas separations, and battery-related systems, where PGNPs provide unique opportunities to couple nanoscale interfacial design with macroscopic performance. Finally, future opportunities are discussed for extending PGNP concepts to increasingly complex, multifunctional, and application-oriented hybrid materials.

functional nanocomposites↗
DOE OSTI2025

Assembly of Metalloporphyrin Peptoids into Crystalline Nanomaterials as a Multifunctional System for Biomimetic Catalysis and Sensing

While natural enzymes excel at catalysis and sensing, they often suffer from high cost and low stability in applications outside living systems. Among tremendous efforts made toward the design and synthesis of catalytic biomimetic materials, the approach of using crystalline nanomaterials assembled from sequence-defined polymers has emerged as a promising strategy. Herein, we report the assembly of metalloporphyrin peptoids into crystalline nanomaterials as a multifunctional system for biomimetic catalysis and sensing. The precise spatial positioning of covalently attached porphyrins within crystalline peptoid nanomaterials enables the mimicry of several enzyme active sites, including phosphotriesterase and horseradish peroxidase, for efficient catalytic hydrolysis and oxidation reactions. Additionally, the high programmability of these peptoid crystalline materials enables the creation and tuning of the active site microenvironment for enhanced catalytic activity. We further demonstrate the integration of responsive organic dyes into catalytic peptoid assemblies to achieve both detection and degradation of chemical warfare agent (CWA) mimics, even in the vapor phase. In conclusion, we expect this multifunctional system to provide tremendous opportunities in biomimetic catalysis and sensing, including the detoxification and detection of CWAs.

Catalysts↗
DOE OSTI2024

Self-Assembling Cell-Free Systems for Scalable Bioconversion

This project focused on developing cell-free systems to directly express multi-enzyme catalysts and perform CO2 bioconversions for industrial chemical production. The use of cell-free expression (CFE) systems derived from bacterial lysates is emerging as a promising approach for biomanufacturing. CFEs are genetically programmable, permit the expression of toxic enzymes, and allow for rapid prototyping of metabolic pathways. Research Contributions: 1. Understanding the Area Investigated: This research advances the understanding of cell-free systems by demonstrating their capability to perform complex multi-enzyme reactions. By directly expressing multi-gene systems, CFEs avoid the high costs and inefficiencies associated with producing and purifying enzymes for multi-step pathways. 2. Technical Effectiveness and Economic Feasibility: The project successfully engineered a CFE-based multienzyme biocatalyst for the de novo synthesis of serine and glycine from CO2 equivalents (formate and bicarbonate) and ammonia. This method achieved a 30% conversion rate of formate into these industrially important amino acids. Additionally, an 8-gene CFE biocatalyst was developed to produce malate, conserving 43% of carbon that would otherwise be lost as CO2. This approach has the potential to reach higher carbon efficiency than microbial production. 3. Public Benefit: The cell-free production of chemicals like serine, glycine, and malate using electrochemically generated formate could significantly reduce CO2 emissions. For example, satisfying the global malate market with this method could avoid approximately 400,000 tons of CO2 emissions annually. This work demonstrates the potential of CFE systems to produce platform chemicals, contributing to environmental sustainability and reducing reliance on petrochemicals. Future Prospects: The CFE-based biocatalyst process could be extended to produce a variety of chemicals, including other industrial di-acids, aromatics, terpenes, alcohols, and polymers. This project showcases the capabilities of cell-free expression systems for prototyping carbon-conserving pathways and sustainably bioproducing platform chemicals, marking a significant step towards economically-viable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Understanding the structural mechanics of ligated DNA crystals via molecular dynamics simulation

DNA self-assembly is a highly programmable method to construct arbitrary architectures based on sequence complementarity. Among various constructs, DNA crystals are macroscopic crystalline materials formed by assembling motifs via sticky end association. Due to their high structural integrity and size ranging from tens to hundreds of micrometers, DNA crystals offer unique opportunities to study the structural properties and deformation behaviors of DNA assemblies. For example, enzymatic ligation of sticky ends can selectively seal nicks resulting in more robust structures with enhanced mechanical properties. However, the research efforts have been mostly on experiments involving different motif designs, structural optimization, or new synthesis methods, while their mechanics are not yet fully understood. The complex properties of DNA crystals are difficult to study via experiments alone, and numerical simulation can complement and aid the experiments. The coarse-grained molecular dynamics (MD) simulation is a powerful tool that can probe the mechanics of DNA assemblies. Here, we investigate DNA crystals made of four different motif lengths with various ligation patterns (full ligation, major directions, connectors, and in-plane) using oxDNA, an open-source, coarse-grained MD platform. We found that several distinct deformation stages emerge in response to mechanical loading and that the number and the location of ligated nucleotides can significantly modulate structural behaviors. These findings should be useful for predicting crystal properties and thus improving the design.

DNA crystal↗