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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

An ultra-tunable platform for molecular engineering of high-performance crystalline porous materials

Metal-organic frameworks are a class of crystalline porous materials with potential applications in catalysis, gas separation and storage, and so on. Of great importance is the development of innovative synthetic strategies to optimize porosity, composition and functionality to target specific applications. Here we show a platform for the development of metal-organic materials and control of their gas sorption properties. This platform can accommodate a large variety of organic ligands and homo- or hetero-metallic clusters, which allows for extraordinary tunability in gas sorption properties. Even without any strong binding sites, most members of this platform exhibit high gas uptake capacity. As a result, the high capacity is accomplished with an isosteric heat of adsorption as low as 20 kJ mol –1 for carbon dioxide, which could bring a distinct economic advantage because of the significantly reduced energy consumption for activation and regeneration of adsorbents.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A common assembly module in injectisome and flagellar type III secretion sorting platforms

Translocating proteins across the double membrane of Gram-negative bacteria, type III secretion systems (T3SS) occur in two evolutionarily related forms: injectisomes, delivering virulence factors into host cells, and the flagellar system, secreting the polymeric filament used for motility. While both systems share related elements of a cytoplasmic sorting platform that facilitates the hierarchical secretion of protein substrates, its assembly and regulation remain unclear. Here we describe a module mediating the assembly of the sorting platform in both secretion systems, and elucidate the structural basis for segregation of homologous components among these divergent T3SS subtypes sharing a common cytoplasmic milieu. These results provide a foundation for the subtype-specific assembly of T3SS sorting platforms and will support further mechanistic analysis and anti-virulence drug design.

Science & Technology - Other Topics↗
DOE OSTI2022

PlasmidMaker is a versatile, automated, and high throughput end-to-end platform for plasmid construction

Abstract Plasmids are used extensively in basic and applied biology. However, design and construction of plasmids, specifically the ones carrying complex genetic information, remains one of the most time-consuming, labor-intensive, and rate-limiting steps in performing sophisticated biological experiments. Here, we report the development of a versatile, robust, automated end-to-end platform named PlasmidMaker that allows error-free construction of plasmids with virtually any sequences in a high throughput manner. This platform consists of a most versatile DNA assembly method using Pyrococcus furiosus Argonaute ( Pf Ago)-based artificial restriction enzymes, a user-friendly frontend for plasmid design, and a backend that streamlines the workflow and integration with a robotic system. As a proof of concept, we used this platform to generate 101 plasmids from six different species ranging from 5 to 18 kb in size from up to 11 DNA fragments. PlasmidMaker should greatly expand the potential of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cross-platform comparison of arbitrary quantum states

As we approach the era of quantum advantage, when quantum computers (QCs) can outperform any classical computer on particular tasks, there remains the difficult challenge of how to validate their performance. While algorithmic success can be easily verified in some instances such as number factoring or oracular algorithms, these approaches only provide pass/fail information of executing specific tasks for a single QC. On the other hand, a comparison between different QCs preparing nominally the same arbitrary circuit provides an insight for generic validation: a quantum computation is only as valid as the agreement between the results produced on different QCs. Such an approach is also at the heart of evaluating metrological standards such as disparate atomic clocks. In this paper, we report a cross-platform QC comparison using randomized and correlated measurements that results in a wealth of information on the QC systems. We execute several quantum circuits on widely different physical QC platforms and analyze the cross-platform state fidelities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations

Solubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.

25 ENERGY STORAGE↗
DOE OSTI2025

A generalized platform for artificial intelligence-powered autonomous enzyme engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-fold improvement in substrate preference and 16-fold improvement in ethyltransferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds

Abstract Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Hybrid plasmonic Au–TiN vertically aligned nanocomposites: a nanoscale platform towards tunable optical sensing

Tunable plasmonic structure at the nanometer scale presents enormous opportunities for various photonic devices. In this work, we present a hybrid plasmonic thin film platform: i.e., a vertically aligned Au nanopillar array grown inside a TiN matrix with controllable Au pillar density. Compared to single phase plasmonic materials, the presented tunable hybrid nanostructures attain optical flexibility including gradual tuning and anisotropic behavior of the complex dielectric function, resonant peak shifting and change of surface plasmon resonances (SPRs) in the UV-visible range, all confirmed by numerical simulations. Lastly, the tailorable hybrid platform also demonstrates enhanced surface plasmon Raman response for Fourier-transform infrared spectroscopy (FTIR) and photoluminescence (PL) measurements, and presents great potentials as designable hybrid platforms for tunable optical-based chemical sensing applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Sharp-tip enhanced catalytic CO oxidation by atomically dispersed Pt 1 /Pt 2 on a raised graphene oxide platform

Revealing structure–activity relationships of graphene-supported atomically dispersed transition metal catalysts is of key importance in catalysis chemistry and materials science. In this work, we report a first-principles theoretical study on O 2 activation and CO oxidation catalyzed by atomically dispersed Pt 1 /Pt 2 anchored on a raised graphene (Gr) platform. The unique sharp-tip structure of the protuberant graphene platform (carbon-tip) can collect extra polarization electrons on the Pt-tip, promoting electron transfer between the catalyst and adsorbates, and greatly enhancing the chemical activity. Higher carbon-tips on defective graphene oxide with a carbon vacancy (Gr-V) produce more polarization electrons, a more localized electric field, and a larger up-shift of the d-orbital center of the Pt-tip, resulting in better catalytic performance. The carbon-tip enhancement reduces the energy barrier for the CO oxidation on Pt 1 O 2 /Gr-V from 1.19 eV to 0.56 eV compared with Pt 1 on planar Gr. In addition, CO poisoning is significantly alleviated, with the CO poisoning rate Γ θ reduced from 2.00 eV to 0.52 eV. Moreover, a linear relationship between the activation barrier and the binding energy of adsorbates is found for various atomically dispersed Pt-tip catalysts on the raised graphene oxide platform. Importantly, the order of catalytic activity is consistent with the carbon-tip enhancement, i.e., Pt 1 O 2 /Gr-V > Pt 2 O 4 /Gr-V > Pt 1 O 2 /Gr > Pt 2 O 4 /Gr. These findings provide important guidance for rational design of atomically dispersed catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Go with the flow: modeling unique biological flows in engineered in vitro platforms

Interest in recapitulating in vivo phenomena in vitro using organ-on-a-chip technology has grown rapidly and with it, attention to the types of fluid flow experienced in the body has followed suit. These platforms offer distinct advantages over in vivo models with regards to human relevance, cost, and control of inputs (e.g., controlled manipulation of biomechanical cues from fluid perfusion). Given the critical role biophysical forces play in several tissues and organs, it is therefore imperative that engineered in vitro platforms capture the complex, unique flow profiles experienced in the body that are intimately tied with organ function. In this review, we outline the complex and unique flow regimes experienced by three different organ systems: blood vasculature, lymphatic vasculature, and the intestinal system. Here, we highlight current state-of-the-art platforms that strive to replicate physiological flows within engineered tissues while introducing potential limitations in current approaches.

42 ENGINEERING↗
DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
DOE OSTI2025

Active learning path-dependent properties using a cloud-based materials acceleration platform

Solid state materials are central to many modern technologies in which a given material may be exposed to a variety of environments. The material properties often vary with the sequence of environments in an irreversible manner, resulting in a quintessential path-dependency in experimental observables. While sequential learning techniques have been effectively deployed for accelerating learning of state properties of materials, they often use a consistent environment path in all experiments. To elevate such techniques for making optimal decisions in experimental investigations of path-dependent properties, we introduce an iterated expected information gain acquisition function that optimizes over entire experimental trajectories. This approach is implemented within a cloud-based Materials Acceleration Platform architecture utilizing an event-driven stateful broker coupled with remote HELAO (Hierarchical Experimental Laboratory Automation and Orchestration) instances and an AI science manager. The platform's efficacy was demonstrated through a case study optimizing multi-step spectro-electrochemical experiments to identify optically stable potential windows in (Co–Ni–Sb)O z metal oxides. The system successfully integrated AI-driven experiment design, remote laboratory automation, and cloud-based data infrastructure, validating the platform's capability for managing complex, adaptive, path-dependent workflows in materials discovery.

Guevarra, Dan [California Institute of Technology ↗
DOE OSTI2014

An in-flight radiography platform to measure hydrodynamic instability growth in inertial confinement fusion capsules at the National Ignition Facility

A new in-flight radiography platform has been established at the National Ignition Facility (NIF) to measure Rayleigh–Taylor and Richtmyer–Meshkov instability growth in inertial confinement fusion capsules. The platform has been tested up to a convergence ratio of 4. An experimental campaign is underway to measure the growth of pre-imposed sinusoidal modulations of the capsule surface, as a function of wavelength, for a pair of ignition-relevant laser drives: a “low-foot” drive representative of what was fielded during the National Ignition Campaign (NIC) [Edwards et al., Phys. Plasmas 20, 070501 (2013)] and the new high-foot [Dittrich et al., Phys. Rev. Lett. 112, 055002 (2014); Park et al., Phys. Rev. Lett. 112, 055001 (2014)] pulse shape, for which the predicted instability growth is much lower. We present measurements of Legendre modes 30, 60, and 90 for the NIC-type, low-foot, drive, and modes 60 and 90 for the high-foot drive. The measured growth is consistent with model predictions, including much less growth for the high-foot drive, demonstrating the instability mitigation aspect of this new pulse shape. We present the design of the platform in detail and discuss the implications of the data it generates for the on-going ignition effort at NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Nanogram calorimetry using microscale suspended SiN{sub x} platforms fabricated via focused ion beam patterning

Comprehensive characterization of thermal properties in nanoscale heterostructures requires microscale thermally isolated platforms combined with sensitive thermometry in order to measure small heat accumulations. Amorphous SiN{sub x} membranes are often used for these measurements due to their low thermal conductivity and compatibility with standard fabrication techniques. The total thermal conductance of such SiN{sub x} membranes is typically microwatts per kelvin or higher. Here, we further reduce this thermal coupling to 120 nW/K by using a focused ion beam (FIB) to remove large portions of commercially available amorphous SiN{sub x} membranes, leaving a 100 μm × 100 μm square platform suspended by 10 μm wide by 325 μm long support legs. We demonstrate the capability of these platforms by measuring the heat capacity of a 6.2 ng Au sample and show that it matches well with established specific heat of bulk Au.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Nanotag-enabled photonic crystal fiber as quantitative surface-enhanced Raman scattering optofluidic platform

Core-shell nanotags that are active in surface-enhanced Raman scattering (SERS) and entrapped with thiocyanate (SCN) label molecules were immobilized in the air channels of suspended-core photonic crystal fiber (PCF) to impart quantitative capacity to SERS-based PCF optofluidic sensing platform. The Raman intensity of Rhodamine 6G increases with concentration, whereas the intensity of SCN remains constant when measured using this platform. The signal from the SCN label can be used as an internal reference to establish calibration for quantitative measurements of analytes of unknown concentrations. The long optical path-length PCF optofluidic platform integrated with SERS-active core-shell nanotags holds significant promise for sensitive quantitative chem/bio measurements with the added benefit of small sampling volume. The dependence of SERS intensity on the nanotag coverage density and PCF length was interpreted based on numerical-analytical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A nanowaveguide platform for collective atom-light interaction

We propose a nanowaveguide platform for collective atom-light interaction through evanescent field coupling. We have developed a 1 cm-long silicon nitride nanowaveguide can use evanescent fields to trap and probe an ensemble of {sup 87}Rb atoms. The waveguide has a sub-micrometer square mode area and was designed with tapers for high fiber-to-waveguide coupling efficiencies at near-infrared wavelengths (750 nm to 1100 nm). Inverse tapers in the platform adiabatically transfer a weakly guided mode of fiber-coupled light into a strongly guided mode with an evanescent field to trap atoms and then back to a weakly guided mode at the other end of the waveguide. The coupling loss is −1 dB per facet (∼80% coupling efficiency) at 760 nm and 1064 nm, which is estimated by a propagation loss measurement with waveguides of different lengths. The proposed platform has good thermal conductance and can guide high optical powers for trapping atoms in ultra-high vacuum. As an intermediate step, we have observed thermal atom absorption of the evanescent component of a nanowaveguide and have demonstrated the U-wire mirror magneto-optical trap that can transfer atoms to the proximity of the surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A 3D-printed microbial cell culture platform with in situ PEGDA hydrogel barriers for differential substrate delivery

Additive manufacturing, or 3D-printing techniques have recently begun to enable simpler, faster, and cheaper production of millifluidic devices at resolutions approaching 100–200 μ m. At this resolution, cell culture devices can be constructed that more accurately replicate natural environments compared with conventional culturing techniques. A number of microfluidics researchers have begun incorporating additive manufacturing into their work, using 3D-printed devices in a wide array of chemical, fluidic, and even some biological applications. In this work, we describe a 3D-printed cell culture platform and demonstrate its use in culturing Pseudomonas putida KT2440 bacteria for 44 h under a differential substrate gradient. Polyethylene glycol diacrylate (PEGDA) hydrogel barriers are patterned in situ within a 3D-printed channel. Transport of the toluidine blue tracer dye through the hydrogel barriers is characterized. Nutrients and oxygen were delivered to cells in the culture region by diffusion through the PEGDA hydrogel barriers from adjacent media or saline perfusion channels. Expression of green fluorescent protein by P. putida KT2440 enabled real time visualization of cell density within the 3D-printed channel, and demonstrated cells were actively expressing protein over the course of the experiment. Cells were observed clustering near hydrogel barrier boundaries where fresh substrate and oxygen were being delivered via diffusive transport, but cells were unable to penetrate the barrier. The device described here provides a versatile and easy to implement platform for cell culture in readily controlled gradient microenvironments. By adjusting device geometry and hydrogel properties, this platform could be further customized for a wide variety of biological applications.

42 ENGINEERING↗