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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 OSTI2025

Commodity Thermoplastic Elastomer-Enabled Templated Synthesis of Large-Pore Ordered Mesoporous Materials

Fabrication of ordered mesoporous materials (OMMs) has predominantly relied on templating-based methods. However, these methods are constrained by several limitations, especially the limited pore sizes attainable with commercially available surfactants used as structure-directing agents. To unlock the full potential of the OMMs, it is essential to develop synthetic strategies that facilitate the production of large-pore OMMs using scalable processes and cost-effective precursors. This work demonstrates the use of thermoplastic elastomer (TPE)-derived carbon replicas for synthesizing ordered mesoporous silica (OMS) and metal oxides (OMMOs) via precursor infiltration and template removal. The nanostructural evolution of the resulting inorganic materials was systematically investigated. Specifically, using tetraethyl orthosilicate (TEOS) as a silica precursor, this method can produce an OMS with relatively large pores. To establish the generalizability of this process, the fabrication approach was extended to other commercially available TPEs with varied chemical compositions and molecular weights while consistently resulting in ordered structures. Additionally, this synthetic strategy can be successfully applied to the production of OMMOs, including tin and titanium oxide matrix chemistries, yielding pore sizes of 16.0 and 19.2 nm, respectively. By developing a general method and using low-cost precursors, this work presents a scalable approach for fabricating large-pore OMMs with tunable pore textures and matrix chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chapter 14: Chemical Recycling of Commodity Plastics

Global plastic production is at an all-time high and shows little signs of slowing down. Less than 10% of all plastic produced is recycled, with approximately 90% entering landfills, incinerators, and oceans. This has led to a rapid accumulation of single-use plastic waste across the planet. Mechanical recycling has been executed at the industrial level to manage plastic waste for decades. However, mechanically recycled plastic products are significantly limited by contamination and low performance. Chemical recycling technologies offer another pathway for achieving plastic circularity. This chapter highlights the current state-of-the-art chemical recycling technologies for plastic decomposition into monomers, fuels, or other petrochemical feedstocks. A brief description of recyclability of plastics and the waste sorting process is provided followed by a high-level overview of chemical recycling technologies. Products, key barriers, and limitations are also discussed as well as a brief overview of techno-economics.

chemical recycling↗
DOE OSTI2016

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A Stochastic Multi-Commodity Logistic Model for Disaster Preparation in Distribution Systems

In this paper, we propose a stochastic optimization approach for disaster preparation in distribution systems. For an upcoming storm, utilities should have a preparation plan that includes warehousing restoration supplies, securing staging sites (depots), and prepositioning crews and equipment. Pre-storm planning enables faster and more efficient post-disaster deploy ment of crews and equipment resources to damage locations. To assist utilities in making this important preparation, this paper develops a two-stage stochastic mixed integer linear program. The first stage determines the depots, number of crews in each site, and the amount of equipment. The second stage is the recourse action that deals with acquiring new equipment and assigning crews to repair damages in realized scenarios. The objective of the developed model is to minimize the costs of depots, crews, equipment, and penalty costs associated with delays in obtain ing equipment and restoration. We consider the uncertainties of damaged lines, number and type of equipment required, and expected repair times. The model is validated on modified IEEE 123-bus distribution test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

'Strategy is a commodity, implementation is an art' - 2 years of implementation of the UK national LLW strategy

The Low Level Waste Repository (LLWR) is the primary facility for disposal of Low Level Waste (LLW) in the United Kingdom (UK), serving the UK nuclear industry and a diverse range of other sectors. Management of LLW in the UK historically was dominated by disposal to the LLWR. The value of the LLWR as a national asset was recognised by the 2007 UK Governmental Policy on management of solid LLW. At this time, analysis of the projected future demand for disposal at LLWR against facility capacity was undertaken identifying a credible risk that the capacity of LLWR would be insufficient to meet future demand if existing waste management practices were perpetuated. To mitigate this risk a National Strategy for the management of LLW in the UK was developed by the Nuclear Decommissioning Authority (NDA), partnered with LLW Repository Ltd. (the organisation established in 2008 to manage the LLWR on behalf of NDA). This strategy was published in 2010 and identified three mechanisms for protection of the capacity of LLWR - application of the Waste Hierarchy by waste producers; optimised use of existing assets for LLW management; and opening of new waste treatment and disposal routes to enable diversion of waste away from the LLWR. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

High Performance Data Analytics on a Commodity Private Cloud

Sandia is researching novel methods of analysis for large datasets. The term “Big Data” has been used frequently in recent years to describe a discipline of computer science that attempts to distil an increasing quantity of data into a result or meaningful subset that can be easily visualized and acted upon by human consumers. These data are frequently characterized by one or more of the following: high volume, velocity, variety, and veracity. Sandia scientists and researchers are no strangers to large datasets, which often typify the result of high-performance computing workloads. The challenge for Sandia data scientists, however, comes at the arrival of exascale computing, which has become mandated by executive order for national computing centers. Because of power and networking limitations, exascale computing precludes the movement of datasets at exascale from data production to data analysis. Such analysis must be done in-situ, to mitigate the time and power costs of network transport. Currently, many of Sandia’s data analytics environments exist as independent entities, often specialized for individual use cases, interconnected to other data analytics, high-performance computing, and storage systems. Sandia is procuring, installing, and researching future platforms for such data analytics. A memory footprint of 256 GB per node, fourteen data rate (FDR) InfiniBand networking, PCIe connected non-volatile memory (NVMe) data storage, and an object data store will characterize the coming institutional data analytics platforms. The combined systems will contain 300 compute nodes. A cloud-inspired software stack resulting from collaboration between the Sandia centers will allow the systems to support a flexible mix of user and system-facing workloads and use cases including code development and testing in R and Python, Apache Hadoop and Spark, distributed in-memory databases, graph analytics, emulytics, system log and predictive analytics, and data visualization for institutional and mission customers. These systems will arrive at the end of FY 2015 and production is planned by the spring of FY 2016.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Development of Bio-Oil Commodity Fuel as a Refinery Feedstock from High Impact Algae Biomass

A two-stage hydrothermal liquefaction (HTL) process was developed to 1) reduce nitrogen levels in algal oil, 2) generate a nitrogen rich stream with limited inhibitors for recycle and algae cultivation, and 3) improve downstream catalytic hydrodenitrogenation and hydrodeoxygenation of the algal oil to refinery intermediates. In the first stage, low temperature HTL was conducted at 125, 175, and 225°C at holding times ranging from 1 to 30 min (time at reaction temperature). A consortium of three algal strains, namely Chlorella sorokiniana, Chlorella minutissima, and Scenedesmus bijuga were used to grow and harvest biomass in a raceway system – this consortium is called the UGA Raceway strain throughout the report. Subsequent analysis of the final harvested product indicated that only two strains predominated in the final harvest - Chlorella sorokiniana and Scenedesmus bijuga. Two additional strains representing a high protein (Spirulina platensis) and high lipid algae (Nannochloropsis) strains were also used in this study. These strains were purchased from suppliers. S. platensis biomass was provided by Earthrise Nutritionals LLC (Calipatria, CA) in dry powder form with defined properties, and was stored in airtight packages at 4°C prior to use. A Nannochloropsis paste from Reed Mariculture was purchased and used in the two-stage HTL/HDO experiments. The solids and liquids from this low temperature HTL pretreatment step were separated and analyzed, leading to the following conclusions. Overall, these results indicate that low temperature HTL (200-250°C) at short residence times (5-15 min) can be used to lyse algae cells and remove/separate protein and nitrogen before subsequent higher temperature HTL (for lipid and other polymer hydrolysis) and HDO. The significant reduction in nitrogen when coupled with low protein/high lipid algae cultivation methods at scale could significantly improve downstream catalytic HDO results. However, significant barriers and knowledge gaps exist that must be overcome and understood. The ability of the separated protein/nitrogen rich aqueous stream to support algae cultivation needs to be verified (and the kinetics of growth measured). The kinetics of algae hydrothermal liquefaction on a mechanistic basis needs to be measured and understood. A better understanding of Maillard reactions during algae HTL is needed. And the impact of Maillard reaction products and incompletely hydrolyzed cell wall components on catalyst deactivation during HDO needs to be understood. Finally, an inexpensive HDO process and associated catalyst capable of converting the algal oil to hydrocarbons needs to be developed.

09 BIOMASS FUELS↗
DOE OSTI2022

Co-production of Clean and Low Cost Hydrogen and Other Commodity Chemicals (CRADA Final Report)

We worked on the production of hydrogen and sulfuric acid electrochemically. We did this by building an electrolyzer and performing techno-economic analysis for which we published a paper (documented above). We also performed many leaching reactions with acid similar to the acid that we would have produced. We found that it was not commercially viable to cogenerate hydrogen and sulfuric acid because the technical problems would take too long to solve under the constraints of venture capital.

08 HYDROGEN↗
DOE OSTI2016

Evaluating Opportunities to Improve Material and Energy Impacts in Commodity Supply Chains.

When evaluated at the process level, next-generation technologies may be more energy and emissions intensive than current technology. However, many advanced technologies have the potential to reduce material and energy consumption in upstream or downstream processing stages. In order to fully understand the benefits and consequences of technology deployment, next-generation technologies should be evaluated in context, as part of a supply chain. This work presents the Material Flows through Industry (MFI) scenario modeling tool. The MFI tool is a cradle-to-gate linear network model of the U.S. industrial sector that can model a wide range of manufacturing scenarios, including changes in production technology, increases in industrial energy efficiency, and substitution between functionally equivalent materials. The MFI tool was developed to perform supply chain scale analyses in order to quantify the impacts and benefits of next-generation technologies and materials at that scale. For the analysis presented in this paper, the MFI tool is utilized to explore a case study comparing a steel supply chain to the supply chains of several functionally equivalent materials. Several of the alternatives to the baseline steel supply chain include next-generation production technologies and materials. Results of the case study show that aluminum production scenarios can out-perform the steel supply chain by using either an advanced smelting technology or an increased aluminum recycling rate. The next-generation material supply chains do not perform as well as either aluminum or steel, but may offer additional use phase reductions in energy and emissions that are outside the scope of the MFI tool. Future work will combine results from the MFI tool with a use phase analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗