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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A machine learning Automated Recommendation Tool for synthetic biology

Abstract Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, fatty acids, and tryptophan. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The living interface between synthetic biology and biomaterial design

Recent far-reaching advances in synthetic biology have yielded exciting tools for the creation of new materials. Conversely, advances in the fundamental understanding of soft-condensed matter, polymers and biomaterials offer new avenues to extend the reach of synthetic biology. The broad and exciting range of possible applications have substantial implications to address grand challenges in health, biotechnology and sustainability. Despite the potentially transformative impact that lies at the interface of synthetic biology and biomaterials, the two fields have, so far, progressed mostly separately. This Perspective provides a review of recent key advances in these two fields, and a roadmap for collaboration at the interface between the two communities. Here we highlight the near-term applications of this interface to the development of hierarchically structured biomaterials, from bioinspired building blocks to 'living' materials that sense and respond based on the reciprocal interactions between materials and embedded cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mixed and membrane-separated culturing of synthetic cyanobacteria-yeast consortia reveals metabolic cross-talk mimicking natural cyanolichens

Metabolite exchange mediates crucial interactions in microbial communities, significantly impacting global carbon and nitrogen cycling. Understanding these chemically-mediated interactions is essential for elucidating natural community functions and developing engineered synthetic communities. This study investigated membrane-separated bioreactors (mBRs) as a novel tool to identify transient metabolites and their producers/consumers in mixed microbial communities. We compared three co-culture methods (direct mixed, 2-chamber mBR, and 3-chamber mBR) to grow a synthetic binary community of the cyanobacterium Synechococcus elongatus PCC 7942 and the fungus Rhodotorula toruloides NBRC 0880, as well as axenic S. elongatus. Despite not being natural lichen constituents, these organisms exhibited interactions resembling those in cyanolichens. S. elongatus fixed CO 2 into sugars as the primary shared metabolite, while R. toruloides secreted various biochemicals, predominantly sugar alcohols, mirroring the metabolite exchange observed in natural lichens. The mBR systems successfully captured metabolite gradients and revealed rapidly consumed compounds, including TCA cycle intermediates and amino acids. Our approach demonstrated that the 2-chamber mBR optimally balanced metabolite exchange and growth dynamics. This study provides insights into cross-species metabolic interactions and presents a valuable tool for investigating and engineering synthetic microbial communities with potential applications in biotechnology and environmental science.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Generating synthetic occupants for use in building performance simulation

Occupant behaviour simulation frameworks can employ synthetic populations to characterize occupancy and behavioural patterns in buildings based on observed demographic data at a certain geographical location. For buildings, very few synthetic occupant populations have been generated. This paper uses a Bayesian Networks (BN) structural learning approach to synthesize populations of occupants in a multi-family housing case study. Two additional cases of office occupants and senior housing residents are considered as a cross-case comparison. Furthermore, we draw upon the extended version of drivers-needs-actions-systems (DNAS) framework to guide the selection of variables and data imputation. Our results show that the BN approach is powerful in learning the structure of data sets. The synthetic data sets successfully match the joint distributions of the underlying combined data sets. Experiments on the multi-family housing particularly show better performance than the office and senior housing cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Development of a synthetic phase contrast imaging diagnostic for turbulence studies at Wendelstein 7-X

Abstract We present a synthetic phase contrast imaging (PCI) diagnostic for studying turbulence at the Wendelstein 7-X (W7-X) stellarator. We first describe the implemented instrument response model, which captures diffraction effects, detector noise, and the long-wavelength cutoff due to the phase plate of the PCI system. To verify the instrument response model, we show that it is capable of reproducing the PCI signal generated by the sound wave speaker used for calibration at W7-X. Next, we discuss the calculation of synthetic PCI signals based on the global, nonlinear gyrokinetic codes GENE-3D and EUTERPE, including results from some of the first stellarator simulations of this type with kinetic electrons (KEs) in GENE-3D. While the simulations used in this work lack a neoclassical radial electric field, which is crucial for reproducing experimental PCI signals, they do indicate that the dominant rotation direction and velocities of the turbulent fluctuations can be inferred from the wave number-frequency spectra of the PCI signals, as expected. The synthetic PCI wave number spectra are further shown to be similar to those of the line-integrated fluctuating electron density, with distinct differences between adiabatic and KE simulations, explainable by previously published turbulence models. For example, the wave number spectra of all adiabatic electron simulations analyzed here follow a power law with an exponent close to −5 for sufficiently large wave numbers. This indicates that universal features of electron density turbulence at W7-X may be studied using the PCI system.

EUTERPE↗
DOE OSTI2022

Bose-Einstein Condensate on a Synthetic Topological Hall Cylinder

The interplay between matter particles and gauge fields in physical spaces with nontrivial geometries can lead to novel topological quantum matter. However, detailed microscopic mechanisms are often obscure, and unconventional spaces are generally challenging to construct in solids. Highly controllable atomic systems can quantum simulate such physics, even those inaccessible in other platforms. Here, we realize a Bose-Einstein condensate (BEC) on a synthetic cylindrical surface subject to a net radial synthetic magnetic flux. We observe a symmetry-protected topological band structure emerging on this Hall cylinder but disappearing in the planar counterpart. BEC’s transport observed as Bloch oscillations in the band structure is analogous to traveling on a Möbius strip in the momentum space, revealing topological band crossings protected by a nonsymmorphic symmetry. We demonstrate that breaking this symmetry induces a topological transition manifested as gap opening at band crossings, and further manipulate the band structure and BEC’s transport by controlling the axial synthetic magnetic flux. Our work opens the door for using atomic quantum simulators to explore intriguing topological phenomena intrinsic in unconventional spaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

2021 Smoky Mountains Conference Data Challenge Synthetic-to-Real Domain Adaptation for Autonomous Driving Dataset

The dataset is comprised of both real and synthetic images from a vehicle's forward-facing camera. Each camera image is accompanied by a corresponding pixel-level semantic segmentation image (all files are .png files). In total, the dataset contains 5600 images in the training/validation set and 1400 images in the testing set. The training dataset contains mostly synthetic RGB images collected with a wide range of weather and lighting conditions using the CARLA simulator [1]. In addition, the training data also includes a small pre-selected subset of data from the Cityscapes training dataset – which is comprised of RGB-segmentation image pairs from driving scenarios in various European cities [2]. The testing data is split into three sets. The first set contains synthetic CARLA images with weather/lighting conditions that were not present in the training set. The second set is a subset of the Cityscapes testing dataset. Finally, the third set is an unknown testing set which will not be revealed to the participants until after the submission deadline. [1] Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017, October). CARLA: An open urban driving simulator. In Conference on robot learning (pp. 1-16). PMLR. [2] Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., ... and Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213-3223).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Creation Synthetic Data to Train a Digital Twin to Predict Reactor Operations

Understanding techniques to strengthen the nuclear safeguards regime is crucial in preventing nuclear proliferation due to recent advancements in the nuclear energy industry such as Generation IV reactors and microreactors. Prior to the construction of a nuclear power plant, it is necessary to understand the proliferation potential of the plant's reactor. Digital twins serve as a unique solution to recognizing reactor behavior indicative of nuclear proliferation. A digital twin is defined as a virtual model that works in unison to represent a physical asset, with a transference of data between the virtual and physical assets [1]. This work serves as validation for training a digital twin on synthetic data fabricated via means of Serpent reactor physics and point kinetics equations simulations. In this case this work is based on parameters of Idaho State University's AGN-201 reactor. The synthetic data can then be utilized to train machine learning models in the future to further investigate the utility of these methods. The accuracy of the predicted data is measured against real operational data to verify the reliability of the synthetic data creation methods and decide whether these methods should be used in the future to inform inspectors of a reactor's proliferation potential.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Error-Level-Controlled Synthetic Forecasts for Renewable Generation

Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the importance of short-term (hours ahead) renewable generation forecasting in power systems operation, it becomes crucial to address the potential inaccuracies in these forecasts. To systematically evaluate the performance of controllers in the presence of imperfect forecasts, we generate synthetic forecasts using actual renewable generation profiles (one from solar and one from wind). These synthetic forecasts incorporate different levels of statistical error, allowing us to control and manipulate the accuracy of the predictions. The primary objective is to employ synthetic forecasts with controlled yet realistic error levels to systematically investigate how controllers adapt to variations in forecast accuracy, providing valuable insights into their robustness and effectiveness under real-world conditions.

Array↗
DOE OSTI2021

Utilizing Plant Synthetic Biology to Improve Human Health and Wellness

Plants offer a vast source of bioactive chemicals with the potential to improve human health through the prevention and treatment of disease. However, many potential therapeutics are produced in small amounts or in species that are difficult to cultivate. The rapidly evolving field of plant synthetic biology provides tools to capitalize on the inventive chemistry of plants by transferring metabolic pathways for therapeutics into far more tenable plants, increasing our ability to produce complex pharmaceuticals in well-studied plant systems. Plant synthetic biology also provides methods to enhance the ability to fortify crops with nutrients and nutraceuticals. In this review, we discuss (1) the potential of plant synthetic biology to improve human health by generating plants that produce pharmaceuticals, nutrients, and nutraceuticals and (2) the technological challenges hindering our ability to generate plants producing health-promoting small molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Synthetic Streamflow Datasets to Support Emulation of Water Allocations via LSTM

This archive is the data companion to the bonney_et-al_2026_erc metarepo which generates synthetic data, trains an LSTM model, and generates performance metrics on the trained model. While the generation of the synthetic data is fully reprodicible, it is a computationally expensive process. This data archive contains the synthetic datasets needed for training and testing an LSTM model and reproduction of figures and tables. In addition, supplemenatary data products generating and visualizing results is also included, such as geospatial data for the basin. Contents There are two high level directories: `WRAP_archive/` and `repo_data/`. The `WRAP_archive` directory contains compressed intermediate dataproducts from the dataset generation workflow (marked as "I_Dataset_Generation" in the metarepo). These data products are not required by any scripts in the metarepo, but they are archived as they are expensive to generate and may have useful information for other analyses. The `repo_data` directory contains the necessary data for reproducing the workflow in the metarepo and should be decompressed and moved into the top level of the metarepo. Additional details are provided in README.md.

drought↗
DOE OSTI2025

Nuclear Reactor Heat Extraction for Synthetic Fuel Plants

This report looks at the viability and best approach when producing synthetic fuels using heat and power supplied by advanced nuclear energy systems. The report looks at a low temperature integration pathway with four types of advanced reactors: a pressurized water reactor (PWR), an advanced light water reactor (A-LWR), a sodium fast reactor (SFR), and a high-temperature gas-cooled reactor (HTGR). A failure modes and effects analysis (FMEA) of the coupling system between the nuclear plant and the synthetic fuel systems is performed with the goal of identifying the reliability of such a thermal delivery system. Furthermore, a high temperature pathway is investigated for synfuel coupling to determine if this is more efficient and more cost effective as a coupling approach.

10 - SYNTHETIC FUELS↗
DOE OSTI2023

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Abstract Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy‐efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

Hu, Jiyun↗
DOE OSTI2023

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Abstract Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy‐efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

Hu, Jiyun↗
DOE OSTI2021

Synthetic Lubricants Derived from Plastic Waste and their Tribological Performance

The energy efficiency, mechanical durability, and environmental compatibility of all moving machine components rely heavily on advanced lubricants for smooth and safe operation. Herein an alternative family of high-quality liquid (HQL) lubricants was derived by the catalytic conversion of pre- and post-consumer polyolefin waste. The plastic-derived lubricants performed comparably to synthetic base oils such as polyalphaolefins (PAOs), both with a wear scar volume (WSV) of 7.5×10 -5 mm -3 . HQLs also performed superior to petroleum-based lubricants such as Group III mineral oil with a WSV of 1.7×10 -4 mm -3 , showcasing a 44% reduction in wear. Furthermore, a synergistic reduction in friction and wear was observed when combining the upcycled plastic lubricant with synthetic oils. Additionally, life cycle and techno-economic analyses also showed this process to be energetically efficient and economically feasible. This novel technology offers a cost-effective opportunity to reduce the harmful environmental impact of plastic waste on our planet and to save energy through reduction of friction and wear-related degradations in transportation applications akin to synthetic oils.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A synthetic strategy for the preparation of alkoxy‐functionalized bis‐1,2,4‐triazinyl‐2,6‐pyridines

Heteroaryl-1,2,4-triazine complexants are commonly utilized in separation science for the selective chelation of minor An from Ln in simulated high-level waste. Furthermore, to facilitate access to relevant chemical entities for hypothesis-driven inquiry toward improved separations performance, a synthetic method to construct various alkoxy-complexant derivatives was required. In this work, a convergent synthetic strategy for the production of 3,3′- and 4,4′-tetraalkoxy-bis-1,2,4-triazinyl-2,6-pyridines from readily available starting materials via a dealkylation/alkylation/condensation approach is described. Synthetic method development, substrate scope, preliminary solubility, and hydrolytic stability data in various process-relevant diluents are reported herein.

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

Post synthetic amine functionalization of MOF-808 for CO 2 sorption via ligand exchange and Michael addition

Post synthetic modification of metal organic frameworks presents a viable route for amine functionalization which can significantly enhance CO 2 sorption capacity. We present a facile means of amine incorporation using limited synthetic steps and low-cost reagents that results in a high density of primary alkyl amines distributed through a zirconium-based metal organic framework (MOF). Both the MOF synthesis and the post synthetic modification take place under aqueous conditions and result in strongly bound molecular amines available for sorbate interaction throughout the MOF pores. Furthermore, this amine incorporation protocol results in a significantly increased CO 2 capacity compared with the unmodified MOF-808. Specifically, CO 2 isotherms collected at 298 K for the unmodified MOF-808 show uptakes of 0.06, 0.2, and 1.2 mmol/g at 4, 15, and 100 kPa, respectively, which can be compared with 0.3, 0.7, and 2.5 mmol/g for the glycine grafted MOF-808 and 0.5, 0.9, and 2.3 mmol/g for ethylenediamine grafted MOF-808.

Amine sorbent↗
DOE OSTI2021

An ontology to represent synthetic building occupant characteristics and behavior

Since the introduction of the occupant behavior Drivers-Needs-Actions-Systems (DNAS) framework in 2013, researchers have used the framework or further developed it based on their case studies, which include efforts to collect new data on occupant behaviors. The effort is often costly for the relatively few new data points added. Problems emerge when the already collected data do not meet the modelers' interoperability requirements. Previous studies addressed this issue by developing more sophisticated ontologies that enable integration with other datasets and synthetic data methodologies that would meet unique research applications. This paper presents an extension of the DNAS framework for the representation of synthetic occupant data to support various applications and use cases across the building life cycle. An agent-based modeling application is one of our motivations that requires more elaborate characteristics of an occupant-agent or a group-of-agent. The extension, built upon a review of the literature, introduces new elements to the framework that fall into five categories, including socio-economic, geographical location, activities, subjective values, and individual and collective adaptive actions. On-going research includes identifying occupant datasets and developing data fusion methods to generate synthetic occupants, as well as to demonstrate its applications in agent-based modeling coupled with building performance simulation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗