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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

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

Enabling Partnership between South Carolina and NREL for Advancing Opportunities in Plastics Recycling Research (EPSCOR for Plastics Recycling)

Proposal Objectives: 1. Utilize depolymerization/fractionation techniques to recover highly processable and reactive feedstocks for polymer synthesis from lignin. 2. Synthesize lignin‐derived non‐isocyanate polyurethane, epoxy, and polyamide using non‐ toxic, biobased route designed for chemical recycling. Characterize resulting materials. 3. Design a high‐yielding chemical recycling process for as‐synthesized materials yielding usable building blocks for many generations of polymer synthesis. 4. Optimize chemical recycling of PET waste for the synthesis of lignin‐based polymers. Compare properties to commercial materials. 5. Optimize reaction conditions and recycling steps to facilitate enhanced sustainability of the synthetic steps and final properties of materials. 6. Complete a lifecycle assessment of lignin utilization and chemical recycling to compare their environmental performance to that of materials produced from virgin material. Identify hot spots and benefits using the chemical recycling process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermomechanical Processing for Improved Mechanical Properties of HT9 Steels

Thermomechanical processing (TMP) of ferritic–martensitic (FM) steels, such as HT9 (Fe–12Cr–1MoWV) steels, involves normalizing, quenching, and tempering to create a microstructure of fine ferritic/martensitic laths with carbide precipitates. HT9 steels are used in fast reactor core components due to their high-temperature strength and resistance to irradiation damage. However, traditional TMP methods for these steels often result in performance limitations under irradiation, including embrittlement at low temperatures (<~430 °C), insufficient strength and toughness at higher temperatures (>500 °C), and void swelling after high-dose irradiation (>200 dpa). This research aimed to enhance both fracture toughness and strength at high temperatures by creating a quenched and tempered martensitic structure with ultrafine laths and precipitates through rapid quenching and unconventional tempering. Mechanical testing revealed significant variations in strength and fracture toughness depending on the processing route, particularly the tempering conditions. Tailored TMP approaches, combining rapid quenching with limited tempering, elevated strength to levels comparable to nano-oxide strengthened ferritic alloys while preserving fracture toughness. For optimal properties in high-Cr steels for future reactor applications, this study recommends a modified tempering treatment, i.e., post-quench annealing at 500 °C or 600 °C for 1 h, possibly followed by a brief tempering at a slightly higher temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Toward systems metabolic engineering in cyanobacteria: Opportunities and bottlenecks

We recently assessed the metabolism of Synechocystis sp PCC6803 through a constraints-based reconstruction and analysis approach and identified its main metabolic properties. These include reduced metabolic robustness, in contrast to a high photosynthetic robustness driving the optimal autotrophic metabolism. Here, we address how these metabolic features affect biotechnological capabilities of this bacterium. The search for growth-coupled overproducer strains revealed that the carbon flux re-routing, but not the electron flux, is significantly more challenging under autotrophic conditions than under mixo- or heterotrophic conditions. We also found that the blocking of the light-driven metabolism was required for carbon flux re-routing under mixotrophic conditions. Overall, our analysis, which represents the first systematic evaluation of the biotechnological capabilities of a photosynthetic organism, paradoxically suggests that the light-driven metabolism itself and its unique metabolic features are the main bottlenecks in harnessing the biotechnological potential of Synechocystis.

genome-scale modeling↗
DOE OSTI2015

System and method of vehicle operating condition management

A vehicle operating condition profile can be determined over a given route while also considering imposed constraints such as deviation from time targets, deviation from maximum governed speed limits, etc. Given current vehicle speed, engine state and transmission state, the present disclosure optimally manages the engine map and transmission to provide a recommended vehicle operating condition that optimizes fuel consumption in transitioning from one vehicle state to a target state. Exemplary embodiments provide for offline and online optimizations relative to fuel consumption. The benefit is increased freight efficiency in transporting cargo from source to destination by minimizing fuel consumption and maintaining drivability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗
DOE OSTI2013

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need to capture uncertainty and risk using appropriate probabilistic, statistical and optimization concepts. The main difficulty arising in addressing these issues is the dramatic increase in the computational complexity of the resulting optimization problems. This project studied novel models and methodologies for risk-averse network optimization- specifically, network design, network flows and cluster detection problems under uncertainty. The approach taken was to incorporate a quantitative risk measure known as conditional value-at-risk that is widely used in financial applications. This approach presents a viable alternate modeling and optimization framework to chance-constrained optimization and mean-variance optimization, one that also facilitates the detection of risk-averse solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Watching the dynamics of electrons and atoms at work in solar energy conversion

The photochemical reactions performed by transition metal complexes have been proposed as viable routes towards solar energy conversion and storage into other forms that can be conveniently used in our everyday applications. In order to develop efficient materials, it is necessary to identify, characterize and optimize the elementary steps of the entire process on the atomic scale. To this end, we have studied the photoinduced electronic and structural dynamics in two heterobimetallic ruthenium–cobalt dyads, which belong to the large family of donor–bridge–acceptor systems. Using a combination of ultrafast optical and X-ray absorption spectroscopies, we can clock the light-driven electron transfer processes with element and spin sensitivity. In addition, the changes in local structure around the two metal centers are monitored. These experiments show that the nature of the connecting bridge is decisive for controlling the forward and the backward electron transfer rates, a result supported by quantum chemistry calculations. More generally, this work illustrates how ultrafast optical and X-ray techniques can disentangle the influence of spin, electronic and nuclear factors on the intramolecular electron transfer process. Finally, some implications for further improving the design of bridged sensitizer-catalysts utilizing the presented methodology are outlined.

14 SOLAR ENERGY↗
DOE OSTI2026

Correlated Noise Estimation with Quantum Sensor Networks

We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and “classical” correlations of the noises. Here, we determine optimal entangled probe states and identify a sensing protocol—reminiscent of a many-body echo—that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route toward entanglement-enhanced metrology of correlated many-body phenomena.

Quantum metrology↗
DOE OSTI2024

Identifying and Amplifying the Spontaneously Formed Photo‐Charge Contribution in Opaque and Semitransparent Organic Photovoltaics

Abstract Spontaneous photo‐charge (SP) generation within the non‐fullerene (NFA) bulk helps avoid exciton (EX) related loss as compared to the traditional heterojunction route in organic solar cells (OSCs). Unfortunately, the promising SP utilization attracts little attention at this time due to the lack of knowledge on its specific contribution to the photovoltaic performance and rational optimization in high‐efficiency devices. To fill the gap, the NFAs’ SP characteristics are related with their photocurrent loss and power conversion efficiency (PCE) in state‐of‐the‐art materials. Though higher SP population is good for efficient EX utilization, it simultaneously acts as an additional photo‐charge recombination channel. The former can be further enhanced by increasing the NFAs’ crystallinity with preferred lamellar growth, and the latter can be suppressed via electric doping. With the aid of the two‐step optimization strategy, the total photocurrent loss is reduced from 14.4% to 4.8%, accompanying with PCE increment from 16.9% to 18.5%. The SP utilization strategy is finally applied in the semitransparent OSCs (ST‐OSCs), due to its less heterojunction area sensitive photo‐charge generation characteristic. A light utilization efficiency (LUE) is then increased from 3.21% to 3.77%. The findings highlight the pursue of efficient SP utilization as a new design philosophy in future OSCs’ progresses.

Chemistry↗
DOE OSTI2019

Synthesis of Biomass-Derived Ethers for Use as Fuels and Lubricants

Ethers synthesized from biomass-derived compounds have exceptional properties as fuels, lubricants, and specialty chemicals and can serve as replacements for petroleum-derived products. Recent efforts have identified heterogeneous catalysts for the selective synthesis of ethers from alcohols, aldehydes, ketones, furans, esters, olefins, carboxylic acids, and other molecules derived from biomass. This Review highlights the scope of etherification reactions and provides insights into the choice of catalysts and reaction conditions best suited for producing targeted ethers from the available starting materials. First, the properties of ethers for specific applications and the methods by which synthons for ether synthesis can be obtained from biomass are discussed. Then the progress that has been made on the synthesis of ethers via the following methods is summarized: direct etherification of alcohols; reductive etherification of alcohols with aldehydes or ketones; etherification of furanic compounds, esters, and carboxylic acids; and the addition of alcohols to olefins. Next, the mechanisms of these reactions and catalyst properties required to promote them are discussed, with the goal of understanding how reaction conditions can be tuned to optimize catalyst activity and selectivity towards desired ethers. Finally, the Review closes by examining the tradeoffs between catalyst selectivity, activity, stability, and reaction conditions required to achieve the most economically and environmentally favorable routes to biomass-derived ethers.

09 BIOMASS FUELS↗
DOE OSTI2016

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Biosynthesis of monoethylene glycol in Saccharomyces cerevisiae utilizing native glycolytic enzymes

Monoethylene glycol (MEG) is an important commodity chemical with applications in numerous industrial processes, primarily in the manufacture of polyethylene terephthalate (PET) polyester used in packaging applications. In the drive towards a sustainable chemical industry, bio-based production of MEG from renewable biomass has attracted growing interest. Recent attempts for bio-based MEG production have investigated metabolic network modifications in Escherichia coli, specifically rewiring the xylose assimilation pathways for the synthesis of MEG. In the present study, we examined the suitability of Saccharomyces cerevisiae, a preferred organism for industrial applications, as platform for MEG biosynthesis. Here, based on combined genetic, biochemical and fermentation studies, we report evidence for the existence of an endogenous biosynthetic route for MEG production from D-xylose in S. cerevisiae which consists of phosphofructokinase and fructose-bisphosphate aldolase, the two key enzymes in the glycolytic pathway. Further metabolic engineering and process optimization yielded a strain capable of producing up to 4.0 g/L MEG, which is the highest titer reported in yeast to-date.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Oxidative Functionalization of Long-Chain Liquid Alkanes by Pulsed Plasma Discharges at Atmospheric Pressure

In this work, we introduce the oxidation of long aliphatic alkanes using non-thermal, atmospheric plasma processing as an eco-friendly route for organic synthesis. A pulsed dielectric barrier discharge in He/O 2 gas mixtures was employed to functionalize n-octadecane. C 18 secondary alcohols and ketones were the main products, with an optimal molar yield of ~29.2%. Prolonged treatment resulted in the formation of dialcohols, diketones, and higher molecular weight oxygenates. Lighter hydrocarbon products and decarboxylation to CO 2 were also observed at longer treatment times and higher power inputs. A maximum energy yield of 5.48 × 10 –8 mol/J was achieved at short treatment times and high powers, associated with higher selectivity to primary oxygenates. Direct hydroxylation of alkyl radicals, as well as disproportionation reactions, are proposed as the main pathways to alcohols and ketones. The results hold promise for functionalizing long hydrocarbon molecules at ambient conditions using catalyst-free plasma discharges.

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

Genetically engineered oleaginous yeast Lipomyces starkeyi for sesquiterpene a-zingiberene production

In this study we demonstrate that transgenic Lipomyces starkeyi strains expressing a ?-zingiberene synthase gene from Lemon basil or Hall’s panicgrass can produce up to 17 mg/l of ?-zingiberene in yeast extract peptone dextrose (YPD) medium containing 4% glucose. Following these findings, the transgenic strain was examined in 8% glucose media with C/N ratios of 20 or 80, and YPD. YPD medium resulted in 59.2 mg/l??-zingiberene accumulation. We further improved ?-zingiberene production by over-expression of selected genes from mevalonate pathway and achieved 145% improvement in ?-zingiberene synthesis. The growth medium was optimized for ?-zingiberene production, which resulted in 14.9% higher titer than YPD medium. The final transgenic strain produced 700 mg/l ?-zingiberene in fed-batch bioreactor culture. This study opens a new synthetic route to produce ?-zingiberene or other terpenoids in the oleaginous yeast L. starkeyi and establishes this yeast as a platform for jet fuel biosynthesis.

Dai, Ziyu↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗
DOE OSTI2019

Optimal placement of data concentrators for expansion of the smart grid communications network

Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high‐performing, reliable, and resilient power system. Three network design formulations based on mixed‐integer linear and non‐linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much‐improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality‐of‐service in the event of an outage. Analysis of multi‐period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

The coastal streamflow flux in the Regional Arctic System Model

The coastal streamflow flux from the Arctic drainage basin is an important driver of dynamics in the coupled ice-ocean system. Comprising more than one third of the total freshwater flux into the Arctic Ocean, streamflow is a key component of the regional and global freshwater cycle. To better represent the coupling of the streamflow flux to the ocean, we have developed and applied the RVIC streamflow routing model within the Regional Arctic System Model (RASM). The RASM is a high-resolution regional Earth System Model whose domain includes all of the Arctic drainage basin. Here in this paper, we introduce the RVIC streamflow routing model, detailing its application within RASM and its advancements in terms of representing high-resolution streamflow processes. We evaluate model simulated streamflow relative to in situ observations and demonstrate a method for improving model performance using a simple optimization procedure. We also present a new, spatially and temporally consistent, high-resolution data set of coastal freshwater fluxes for the Arctic drainage basin and surrounding areas that is based on a fully coupled RASM simulation and intended for use in Arctic Ocean modeling applications. This data set is evaluated relative to other coastal streamflow data sets commonly used by the ocean modeling community. We demonstrate that the RASM-simulated streamflow flux better represents the annual cycle than existing data sets, especially in ungauged areas. Finally, we assess the impact that streamflow has on the coupled ice-ocean system, finding that the presence of streamflow leads to reduced sea surface salinity, increased sea surface temperatures, and decreased sea ice thickness.

54 ENVIRONMENTAL SCIENCES↗