Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “technical report”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Investigation of Defect Physics for Efficient, Durable and Ubiquitous Perovskite Solar Modules (Final Technical Report)

Organometal halide perovskite solar cells have experienced eye-catching improvements in its recent few years. It serves as one of the most promising candidates to replace the currently widely used silicon-based solar modules. To implement its final step to the real application, functional longevity becomes the dernier continent to conquer. As a polycrystalline material, defect plays critical role in the efficiency and stability of the perovskite solar cells. Thus, the investigation of the defect physics of the perovskite layer is indispensable in this research field. However, hard evidence and a consensus are still lacking in terms of the specific nature of the defects and their effects on performance and hysteresis, and perhaps even more importantly, there is absence of fundamental understanding of the correlations between the defects and long-term operational stability of the device. A more fundamental understanding of the nature of defects in perovskite materials is of paramount importance to progress their efficiency and durability. In this work we propose in-depth studies of correlations of defects with performance and stability of perovskite solar cells. Our project aimed 1) to investigate the defects physics in perovskite solar cells, and 2) to develop a comprehensive understanding and physical model of defects and its influence on performance and stability of perovskite solar cells. With the support from program manager, Peter Lobaccaro, and the Solar Energy Technologies Office of U.S. Department of Energy, the project ends with impact achievements. Our research results have systematically provided strategies to analyze the influences of constructive molecular configurations to the charged defects in the perovskite lattices and developed in-depth understanding of chemical additive approach to improve the perovskite solar cell performance and stability. As history has shown us, control over defect properties of semiconductor materials is the key to achieving high performance and low cost devices. Therefore, the potential impact of unlocking the understanding and manipulation of defects in perovskites is great, enabling this technology to realize SETO goals. The research project is highly productive with 18 published papers in three years in top-level journals such as Science, Nature, Nature Materials, Nature Communications, Journal of American Chemistry Society, Joule, Advanced Materials, and Nano Letters. These works have drawn great attention nationwide with notable total citations over 700 times from 2020 to 2022.

14 SOLAR ENERGY↗
DOE OSTI2024

Low-cost, high-efficiency III-V photovoltaics enabled by remote epitaxy through graphene (Final Technical Report)

One of the most important outcomes of this project was that the team developed a method to directly grow graphene layer in wafer-scale on III-V substrates. Conventionally, graphene had to be transferred for remote epitaxy, which has imposed significant challenges in scalability, film quality, and substrate recycling, due to the transfer-related issues. The newly developed method of directly forming 2D layers by Metal-Organic Chemical Vapor Deposition (MOCVD) has realized wafer-scale, defect-free graphene formation for remote epitaxy, which has huge implications not only for solar cells but also in expanding the scalability and the possibility for heterointegration with dissimilar material platforms. Another important outcome was on better understanding of remote epitaxy mechanism. The growth of III-V on graphene is vastly different from directly growing films on III-V substrates, because the surface energy of graphene is very small, meaning that the nucleation density on graphene will be much lower than exposed III-V surfaces. Also, the graphene and the interface properties critically affect remote interaction through graphene. With this obtained knowledge regarding III-V remote epitaxy, we were able to achieve wafer-scale single-crystalline remote epitaxy, 100% exfoliation of the remote epitaxial films, as well as multiple times of GaAs wafer reusability demonstration. The general rule of thumbs found during this project will be a stepping stone for the growth and fabrication of various high-performance devices by remote epitaxy. Lastly, because remote epitaxy and 2DLT offer a pathway to isolate single-crystal membranes from the host wafers, the wafer-scale remote epitaxy processes developed in this project could open up pathways for new functionality and multi-functionality by heterointegration of remote epitaxially formed membranes.

14 SOLAR ENERGY↗
DOE OSTI2024

One-pot hydrodeoxygenation (HDO) of lignin monomers to C9 hydrocarbons co-catalyzed by Ru/C and Nb 2 O 5 (Final Technical Report)

Non-edible lignocellulosic biomass represents the most abundant source of renewable carbon on Earth. To harness its potential for producing valuable fuels and building blocks for renewable plastics, it is essential to undergo a process that involves the removal of oxygen atoms from its components. This report outlines various methodologies aimed at converting biomass components into fuels and building blocks suitable for renewable plastics. The primary emphasis of the described research lies in leveraging sustainable chemistry and catalysis to valorize biomass into fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2024

Tokamak Disruption Simulation (Final Technical Report)

This was a multi-institutional project concerned with simulation of tokamak disruption – rapid termination of the plasma and confining magnetic field in a tokamak fusion reactor – with the aim of quantifying the physics associated with disruption mitigation. The PI’s role is as one of a group of computational scientists concerned with development of effective solution algorithms for the underlying models of magnetohydrodynamics and transport that represent the physical processes, and to develop techniques of uncertainty quantification for treating unknown aspects of the model such as boundary conditions and effects of impurities in plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PHILMS) (Technical Report)

The research work at University of California Santa Barbara (UCSB) resulted in several new developments in the areas of scientific machine learning, numerical analysis, and practical methods for data-driven modeling, prediction, reductions, and simulation. Many of the projects were carried out in collaboration with members of the national laboratories at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and other institutions. Results included developing new scientific machine learning methods, related theory and mathematical frameworks for analysis and training, data-driven numerical solvers, and related tools and software for scientific computation. During the support period, over 16+ papers were submitted for publication, and 4 open-source software packages were developed and released (available at http://atzberger.org/). In addition, 7+ students and 2 post-docs were mentored in collaboration with the laboratory staff for future careers in academia, government labs, and industry.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Collaborative Research: Vlasov–Maxwell Simulations to resolve electron heating and dissipation, in quasiperpendicular shocks (Final Technical Report)

The project is to study electron heating at quasi-perpendicular shocks. We have analyzed measurements from the Magnetosphere Multiscale (MMS) spacecraft and particle-in-cell simulations to address the question. One key discovery is that waves and are excited in the shock transition region, which further develop into complicated structures and thin current layers, which contribute to accelerate and heat electrons. We further investigated the excitation and evolution of these waves and structures, and their association with ion and electron dynamics. In addition, the analysis technique of Vlasov equation terms is further applied to study electron dynamics at the dayside magnetopause, to understand the effect of density, velocity and temperature variations on electron distributions and kinetics.

58 GEOSCIENCES↗
DOE OSTI2024

Development of 211 At production at Crocker Nuclear Laboratory (Final Technical Report)

The focus of this effort was the development of the capability to produce and recover 211 At via the process 209 Bi(α, 2n) 211 At at the cyclotron at the Crocker Nuclear Laboratory at UC Davis. This effort required the design and fabrication of an internal production target, the development of a separation and processing area, and upgrades to the cyclotron to increase its reliability. There was a significant delay due to the pandemic lockdown, but ultimately we were able to produce and recover 211 At at the tens of µCi level using a wet chemistry method. Results of the project were presented at conference, but publication of a refereed article has been delayed by some discrepancies in understanding the calibration of total 211 At produced. We plan to repeat the production using internal funding, but first we want to revise our recovery to use a different technique, developed at the Texas A& M Cyclotron Institute.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Extension of Local Helicity Injection Startup Studies to the Urania Experiment (Final Technical Report)

Initiating high-current plasma in a spherical tokamak (ST) without a central solenoid is a critical issue for the development of the ST configuration. The goal of the research funded through this grant was focused on addressing this challenge by demonstrating scalable startup to high plasma current (I p ), while developing a physical understanding and predictive models for non-solenoidal tokamak plasma startup using Local Helicity Injection (LHI). A major objective of this research and development activity was to use scaling experiments to validate a physics understanding that will support deployment of high-current (~1 MA) startup techniques to fusion-scale facilities such as NSTX-U and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Technical Report for SMART task 3.3.4

To implement the Fourier Neural Operator (FNO) (Li et al., 2021) as well as the U-Shaped Fourier Neural Operator (U-NO) (Rahman et al., 2022) to forecast the pressure distribution in the subsurface. Furthermore, to test out approaches to work on larger-scale as well as adding physics-based constraints.

58 GEOSCIENCES↗
DOE OSTI2023

Integrating Microtransit with Public Transit for Coordinated Multi-Modal Movement of People (Final Technical Report)

This project focused on potential benefits of mobility service providers and transit agencies cooperating to offer fully integrated, seamless multi-modal mobility services for commuters. Specifically, we aimed at developing a first/last mile microtransit and micromobility services tightly integrated with fixed-route transit to achieve the “point-to-point” service capability. Our goal was to provide fixed-route transit customers with two convenient and compelling options for accessing public transit that are also operational efficient.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Final Technical Report

The Department of Energy is interested in technologies that support the sustainable production of fuels, chemicals, and other bioproducts from plant biomass, to offset the nation’s reliance on fossil resources. The plant cell wall of energy crops provides the largest reservoir of raw materials for bioproducts. However, the widespread use of plant cell walls is hampered by their complexity and resistance to breakdown. To improve the productivity and cost-effectiveness of using energy crops to generate bioproducts, the fundamental problem of deconstructing plant cell walls must be addressed. This project developed and evaluated an innovative genetic modification technology to produce strategically designed enzymes that specifically accumulate in the plant cell wall. The resulting enzyme-engineered energy crops are expected to grow normally under natural conditions but break down more quickly and easily under high temperature during the production of biobased products. As such, this plant cell wall targeting enzyme engineering effort will reduce the cost of plant cell wall deconstruction and ultimately improve the economics of bioproducts. The overall objective of this project is to develop and evaluate the in-planta enzyme engineering technology to reduce lignocellulose deconstruction cost. The concept was first validated using tobacco plant, a model plant system that is typically used in lab testing for initial concept validation. Then the enzyme optimization was validated using switchgrass, the energy crop to be used to produce bioproducts. There are three specific objectives in this Phase I project: (1) validate the enzyme optimization concept using tobacco plant, a model plant system. (2) validate the enzyme optimization concept using switchgrass. (3) techno-economic analysis (TEA) for further scale-up application. By the end of this project, in-planta enzyme engineering was validated in both tobacco and switchgrass plants, with improved enzyme activity and saccharification efficiency. The in-planta enzyme engineering in Tabacco didn’t have a significant impact on plant growth and development. Transgenic tobacco plants with in-planta cellulose degrading enzymes showed higher biomass digestibility than wild type. Gene construction and transformation in switchgrass was much longer than expected, which delayed the research progress. Besides, in-planta engineering of lignin degrading enzyme is more challenging than cellulose degrading enzyme, in terms of expression detection. Expression of lignin degrading enzyme and cellulose degrading enzyme improved biomass yield and saccharification efficiency of switchgrass, respectively. It is promising to express both genes in switchgrass for optimized overall performance. According to the results of TEA, switchgrass biomass production cost is mainly attributed to by fertility and harvesting. Biomass production profit can increase up to 10-fold depending on biomass price. The PHA production profit is also sensitive to the biomass price. The proposed technology could potentially reduce the biomass deconstruction cost from 33% to 9% of PHA revenue, making the biomass-based PHA competitive to petroleum-based polymers even in case of relatively high biomass price of biomass. Therefore, cultivation of the genetically engineered self-deconstruction switchgrass for Polyhydroxyalkanoate (PHA) production could benefit switchgrass grower and PHA producer with attractive profits for both sectors. This new enzyme optimization approach will be beneficial for bioindustries that use energy crops as feedstocks. It will improve the economic viability of converting energy crops to renewable products that support a sustainable society and helps address the Nation’s long-term strategic needs for renewable products and reduction of reliance on fossil resources.

42 ENGINEERING↗
DOE OSTI2024

Metal-Organic Frameworks: Structure, Function and Design via Hyperpolarized NMR Spectroscopy: Collaborative Proposal (Final Technical Report)

Nuclear magnetic resonance is a powerful tool to shed light on the properties of a vast range of materials but its use is affected by detection sensitivity. Throughout this work, we investigated new routes to dynamic nuclear spin polarization with an eye on applications to the study of metal-organic frameworks (MOFs). Work at the Meriles group focused on extending our understanding of the mechanisms governing the optical generation of spin order via photo-active electronic spin species and the subsequent transfer of spin polarization throughout the solid-state host.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Universality of Collective Density Fluctuations in Liquids at and away from Equilibrium – An Integrated Neutron Scattering, Theoretical, and Computational Study (Final Technical Report)

Liquids, ubiquitous on earth, are prototypical disordered condensed matter. As the mediate phase between non-structured gases and ordered solids, liquids p ossess intriguing complexities that are absent on either extreme counter phase, especially when they are driven away from equilibrium. Despite decades of studies, the physics of liquids still keeps surprising us and challenges our understanding of condensed matter, emergent phenomena, and complex systems. Among the many interesting properties, the nature of collective dynamics in liquids remains elusive because of both the presence of strong interactions and the absence of translational invariance. This project studied the universal features of collective density fluctuations (or collective modes), which include both phonon-like excitations and collective relaxations, in the Q-dependent generalized hydrodynamic regime in liquids and liquid-like matter both at and away from equilibrium. We performed systematic studies of the fast collective dynamics (including both phonon-like excitations and collective relaxations) of four classes of liquids characterized by different fragilities and interactions using synergistically integrated coherent neutron scattering experiments (Inelastic Neutron Scattering (INS), Quasi-Elastic Neutron Scattering (QENS), and Neutron Spin Echo (NSE)), a ViscoElastic Hydrodynamics theory we have been developing, andMolecular Dynamics (MD) simulations and our analysis package LiquidLib. The transformative knowledge of the collective dynamics in liquids is important to understand and ultimately control the transport of mass, energy, and charge in liquids, both at and away from thermal equilibrium, which may will likely impact a wide range of disciplines.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep Image Prior Enabled Full Waveform Inversion (Final Technical Report)

MS Student Naveen Gupta worked on the problem of full waveform inversion (FWI) using neural networks as shown in Figure 1. Our goal was to learn a neural network to represent the subsurface velocity model, which when fed into the FWI module (implemented using a numerical forward model of wave equations) produces amplitude estimates that match with ground-truth observations of amplitude. We used neural networks to solve the inverse problem of estimating velocity distributions for a given seismic amplitude data such that, once trained, our neural network model can generate a distribution of velocity profiles for different random vectors fed as inputs to the neural network model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Identifying Hydropower Operational Flexibilities in Presence of Streamflow and Net-load Uncertainty (Final Technical report)

In the existing operations, hydropower contributions to future system flexibility are generally modeled while maintaining traditional operating rules and constraints in supporting grid operation, such as the balancing of variable renewable energy production. Moreover, operation of large scale hydropower systems on major rivers has been investigated for decades, utilizing various systems engineering approaches, with the evolving electric grid, as the result of renewable resources integration, compounded by the changing climate (variability of river flows, intensification of hydrologic cycle resulting in more frequent extreme events) affecting water availability, the need for more advanced stochastic modeling and effective uncertainty analysis approaches have become necessary. The research results supported by this funding and presented in this report provide a new look at hydropower operational flexibility enforced by the changes identified above. Understanding how hydropower operates in response to the underlying uncertainties with respect to the system constraints is crucial in identifying its operational flexibility potentials. In this project, the flexibility of the operating hydropower facility is described by capturing uncertainties in both water and power system and formulating the operations as a multistage stochastic optimization problem. The proposed approach supports short- to seasonal-term operations and planning decision horizons.

13 HYDRO ENERGY↗
DOE OSTI2024

Elucidating mechanisms of Photosystem I assembly and repair (Final Technical Report)

Oxygenic photosynthesis generates the carbohydrates and oxygen that support life on earth. Central to this process are photosystems I and II (PSI and PSII), large protein-pigment complexes that are among the most complex macromolecular structures in nature. Impressive advances have been made in understanding the structure and photochemical mechanisms of PSI and PSII. However, less is known about the mechanisms underlying their biogenesis. The overarching goal of this project was to elucidate mechanisms of photosystem assembly. Several proteins that are not found in mature PSI or PSII are essential for their assembly, but the assembly pathways and the role of each assembly factor are just starting to emerge. During the course of this project, we advanced understanding of this problem in several ways. First, we addressed the spatial organization of photosystem assembly by localizing many known assembly factors to specific subdomains of thylakoid membranes in plant chloroplasts. This work revealed that the "curvature" domain - the highly curved periphery of stacked granal membrane disks - is a center of photosystem assembly. However, whereas some PSI assembly factors localized exclusively to the curvature domain, another was found exclusively in granal margins and unstacked membranes. This spatial partitioning suggests an assembly line along which different assembly intermediates are physically segregated. Most assembly factors localized similarly in dark-adapted and illuminated plants, but one PSII assembly factor shifted from the curvature domain to unstacked membranes upon illumination, suggesting an unanticipated role in the repair of light-induced PSII damage. Whereas most PSII subunits were found primarily in grana stacks (as expected), one PSII subunit, PsbP, was prominent also in the curvature fraction, suggesting that PsbP has functions beyond its role in mature PSII, possibly in biogenesis or repair.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗