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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data for A Fluorescence-Based Transient Expression Assay for the Analysis of Upstream Open Reading Frames in Plants

Scripts for the manuscript "A fluorescence-based transient expression assay for the analysis of upstream open reading frames in plant" by Haas et al. Upstream open reading frames (uORFs) are regulatory elements present in the 5′ leaders of mRNA that can significantly impact downstream gene expression in eukaryotes. In crop engineering, editing of uORFs can provide an avenue to upregulate expression of native genes without the need to add persistent transgenic copies. Even with genome- wide methods to identify translated uORFs such as ribosome profiling, their functional characterization depends on validation through reporter gene assays and mutagenesis studies. Current screening methods for plants use luciferases or protoplasts to measure differential gene expression between wild- type and mutated transcript leaders, which requires tissue processing and/or substrate addition. Here, we present a time- and cost- efficient alternative to investigate transcript leaders by co- expression of two fluorescent proteins in Nicotiana benthamiana leaf tissue and test our assay on genes involved in photoprotection, editing of which could provide a pathway to increase CO2 assimilation during sun–shade transitions.

Gene Editing↗
DOE OSTI2023

Towards functionalized lignin and its derivatives for high-value material applications

In pursuit of low-carbon development, the production of diverse functional materials from renewable resources, especially lignocellulosic biomass, is of vital importance. Lignin is a major component of lignocellulose, and it is nature's only true high-volume aromatic polymer, which has the advantages of biodegradability, biocompatibility, and low acquisition cost. After modification by a variety of physicochemical strategies, it can be applied as an alternative to basic industrial materials, including polyurethanes, phenolic, and epoxy resins, which stands comparably to conventional synthetic polymers in terms of both performance and reduced cost. To further unlock the potential of lignin, an alluring opportunity is the exploitation of lignin for high-value materials, especially nanomaterials, that find extensive applications in energy and environment areas. This review provides a systematic summary and perspective of research that has been devoted to lignin transformation to high-value materials, ranging from industrially well-established engineering materials to the recently emerged nanomaterials that were used for energy and environment applications. Latest cutting-edge innovations on lignin modification, controlled depolymerization, and assembly during the last five years are summarized. Structure-function relationships of lignin materials in terms of their specific applications are analyzed. Furthermore, challenges and future opportunities for lignin conversion to high-value materials are also provided. We wish this review will stimulate further advances in lignin based high-value materials, and promote “waste” into “wealth”.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

Gautam, Mukesh↗
DOE OSTI2021

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

42 ENGINEERING↗
DOE OSTI2025

Processability and Material Behavior of NiTi Shape Memory Alloys Using Wire Laser-Directed Energy Deposition (WL-DED)

Utilizing additive manufacturing (AM) techniques with shape memory alloys (SMAs) like NiTi shows great promise for fabricating highly flexible and functionally superior 3D metallic structures. Compared to methods relying on powder feedstocks, wire-based additive manufacturing processes provide a viable alternative, addressing challenges such as chemical composition instability, material availability, higher feedstock costs, and limitations on part size while simplifying process development. This study presented a novel approach by thoroughly assessing the printability of Ni-rich Ni55.94Ti (Wt. %) SMA using the wire laser-directed energy deposition (WL-DED) technique, addressing the existing knowledge gap regarding the laser wire-feed metal additive manufacturing of NiTi alloys. For the first time, the impact of processing parameters—specifically laser power (400–1000 W) and transverse speed (300–900 mm/min)—on single-track fabrication using NiTi wires in the WL-DED process was examined. An optimal range of process parameters was determined to achieve high-quality prints with minimal defects, such as wire dripping, stubbing, and overfilling. Building upon these findings, we printed five distinct cubes, demonstrating the feasibility of producing nearly porosity-free specimens. Notably, this study investigated the effect of energy density on the printed part density, impurity pick-up, transformation temperature, and hardness of the manufactured NiTi cubes. The results from the cube study demonstrated that varying energy densities (46.66–70 J/mm3) significantly affected the quality of the deposits. Lower to intermediate energy densities achieved high relative densities (>99%) and favorable phase transformation temperatures. In contrast, higher energy densities led to instability in melt pool shape, increased porosity, and discrepancies in phase transformation temperatures. These findings highlighted the critical role of precise parameter control in achieving functional NiTi parts and offer valuable insights for advancing AM techniques in fabricating larger high-quality NiTi components. Additionally, our research highlighted important considerations for civil engineering applications, particularly in the development of seismic dampers for energy dissipation in structures, offering a promising solution for enhancing structural performance and energy management in critical infrastructure.

Dabbaghi, Hediyeh↗
DOE OSTI2025

A high-order computational framework for particle-resolved simulations of disperse multiphase flows

This work presents a high-order numerical approach for particle-resolved simulations of disperse multiphase flows, where the Navier-Stokes equations for fluid flow are solved using a high-order spectral element method in the Eulerian framework, and the particle phase is directly simulated with a discrete element method. The coupling between particles and fluids is explicitly handled using an adapted direct-forcing immersed boundary method. Unlike the conventional schemes, a high-order barycentric Lagrange interpolation method and a Gaussian projection kernel are used to ensure accurate momentum exchange between local boundary points and surrounding fluid nodes in the framework of high-order fluid solver. Benchmark tests of increasing complexity are conducted to demonstrate the accuracy and efficiency of our method. Here, it is found that our approach exhibits an excellent convergence performance, as the fluid element/grid is refined and the number of boundary points increases. Compared to conventional low-order methods, the proposed high-order framework enables the use of substantially larger fluid elements while maintaining high accuracy in modeling fluid-particle interactions, owing to the enhanced resolution of high-order basis functions. Moreover, since the primary unknowns are stored at element or grid nodes, the high-order approach offers improved efficiency in both CPU memory usage and total computational cost.

42 ENGINEERING↗
DOE OSTI2022

Review of Multifunctional Separators: Stabilizing the Cathode and the Anode for Alkali (Li, Na, and K) Metal–Sulfur and Selenium Batteries

Alkali metal batteries based on lithium, sodium, and potassium anodes and sulfur-based cathodes are regarded as key for next-generation energy storage due to their high theoretical energy and potential cost effectiveness. However, metal–sulfur batteries remain challenged by several factors, including polysulfides’ (PSs) dissolution, sluggish sulfur redox kinetics at the cathode, and metallic dendrite growth at the anode. Functional separators and interlayers are an innovative approach to remedying these drawbacks. Here we critically review the state-of-the-art in separators/interlayers for cathode and anode protection, covering the Li–S and the emerging Na–S and K–S systems. The approaches for improving electrochemical performance may be categorized as one or a combination of the following: Immobilization of polysulfides (cathode); catalyzing sulfur redox kinetics (cathode); introduction of protective layers to serve as an artificial solid electrolyte interphase (SEI) (anode); and combined improvement in electrolyte wetting and homogenization of ion flux (anode and cathode). It is demonstrated that while the advances in Li–S are relatively mature, less progress has been made with Na–S and K–S due to the more challenging redox chemistry at the cathode and increased electrochemical instability at the anode. Throughout these sections there is a complementary discussion of functional separators for emerging alkali metal systems based on metal–selenium and the metal–selenium sulfide. The focus then shifts to interlayers and artificial SEI/cathode electrolyte interphase (CEI) layers employed to stabilize solid-state electrolytes (SSEs) in metal–sulfur solid-state batteries (SSBs). The discussion of SSEs focuses on inorganic electrolytes based on Li- and Na-based oxides and sulfides but also touches on some hybrid systems with an inorganic matrix and a minority polymer phase. The review then moves to practical considerations for functional separators, including scaleup issues and Li–S technoeconomics. The review concludes with an outlook section, where we discuss emerging mechanics, spectroscopy, and advanced electron microscopy (e.g. cryo-transmission electron microscopy (cryo-TEM) and cryo-focused ion beam (cryo-FIB))-based approaches for analysis of functional separator structure–battery electrochemical performance interrelations. Finally, throughout the review we identify the outstanding open scientific and technological questions while providing recommendations for future research topics.

25 ENERGY STORAGE↗
DOE OSTI2024

Detailed Characterization of Vitrinite-Rich Subbituminous and Bituminous Coals for Utilization in Carbon Fiber Precursor Production

Chemical structures of candidate coals (one subbituminous coal from the Powder River Basin and three bituminous Eastern US coals) were examined for potential low-cost carbon fiber precursor production. Here, the structural evaluation examined the carbon skeleton ( 13 C nuclear magnetic resonance (NMR) and high-resolution transmission electron microscopy (HRTEM)), the heteroatom functionality (X-ray photoelectron spectroscopy (XPS) Fourier transform infrared spectroscopy (FTIR) and NMR), the structural ordering and distribution of PAH sizes (HRTEM), and an estimation of the molecular weight distribution (laser desorption ionization mass spectrometry, LDIMS). The molecular compositional distributions were also evaluated for a mixed solvent extract (atmospheric pressure photoionization, 21 T Fourier transform ion cyclotron resonance mass spectrometry, FT-ICR MS). Significant structural differences existed between the subbituminous and bituminous coals, as expected with coalification (with the bituminous coals having a higher carbon content, lower oxygen content, higher aromaticity values, larger cluster sizes, and so forth). While the bituminous coals were similar in structure (close in rank with Blue Gem being hvAb and the rest being hvBb), structural differences were still evident. Specifically, structural similarities were evident for the average properties of Herrin and Springfield coals: same rank, similar moisture, and volatile matter yields, along with similar aromaticity and carbon and hydrogen content. However, significant structural differences were observed at the molecular level by 21 T FT-ICR MS, which showed that the Springfield coal was structurally more complex. Specifically, 21740, 16931, 30190, and 12982 unique elemental compositions were identified for the Monarch, Herrin, Springfield, and Blue Gem coals, further illustrating the complexity of the coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

UiO-66 Metal–Organic Framework as an Anode for a Potassium-Ion Battery: Quantum Mechanical Analysis

The natural abundance of potassium in the earth’s crust is 1000 times higher than that of lithium, so energy technologies built on potassium are more sustainable. Potassium-ion batteries have attracted considerable attention because of their relatively low cost and high operating potential, but questions remain about the best anode material for such batteries. Here, in this paper, we report first-principles computations based on density functional theory to investigate the performance of the UiO-66 metal–organic framework as an anode material for potassium-ion batteries; the goal is to provide a fundamental understanding of metal–organic framework (MOF)-based electrodes to guide the design and development of high-performance potassium-ion batteries. Our study includes the stability and electronic properties of potassiated structures and the mechanisms of potassium intercalation and diffusion in the framework. The results indicate that UiO-66 has a maximum specific capacity of 644 mAh/g as the anode of a potassium-ion battery. During potassiation, we observe charge transfer from potassium to carbon or oxygen of UiO-66 near the intercalated K. During K diffusion, the K migrates along the UiO-66 framework with a maximal migration energy barrier of 0.377 eV in the optimal pathway, which is much lower than the barriers for Li and Na diffusion in UiO-66. The diffusion coefficient of K in the anode is several orders of magnitude larger than those of Li and Na. This favors potassium ions over lithium ions or sodium ions when UiO-66 is the anode.

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

Single-Ion Conducting Polymer Electrolyte Enabled via Aza-Michael Addition

Single-ion conducting polymer electrolytes present a possible route for achieving high energy density next-generation batteries due to their flexible nature and high cation transport number. The trifluoromethanesulfonimide (TFSI) functional group represents one of the most efficient tethered anions for Li-ion conductivity. However, the covalent attachment of TFSI groups into polymer electrolytes has been challenging and costly due to its synthetic difficulty and limited commercial availability of building blocks. Here, we present a new polymer electrolyte synthesized by the Michael addition reaction between poly(allylamine) (PAA) and a vinyl TFSI anion under mild reaction conditions. The resulting PAATFSI exhibits a lower glass transition temperature and several orders of magnitude higher Li-ion conductivity than similar TFSI-based single-ion conducting homopolymers in the dry state. Moreover, PAATFSI exhibits excellent Li-ion conductivity (2.7 × 10 –4 S/cm at 30 °C) with the addition of a plasticizer (60 wt % of carbonate solvent), which enables stable lithium–metal battery performance. In conclusion, this study demonstrates a facile route for the synthesis of new single-ion conducting polymer electrolytes that opens a library of possibilities to enable the realization of polymer-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Origins of the Pressure-Induced Phase Transition and Metallization in the Halide Perovskite (CH 3 NH 3 )PbI 3

Hybrid halide perovskites are promising for applications because of their favorable optoelectronic properties and low cost. Here we investigate the effects of hydrostatic pressure on the structural and electronic properties of (MA)PbI 3 (MA = CH 3 NH 3 + ) using first-principles density functional theory calculations. Our calculations predict that at a pressure of 0.23 GPa, the orthorhombic Fmmm phase becomes unstable with respect to a cubic Im$\bar{3}$ phase, in good agreement with room-temperature experiments (~0.3 GPa). At higher pressures, about 6 GPa, we predict the onset of pronounced intra- and interoctahedral distortions. This symmetry lowering leads to the introduction of I 5p–I 5p* antibonding and Pb 6p–Pb 6p bonding character into the valence band maximum (VBM) and the conduction band minimum (CBM) states, respectively. We find this change in bond character explains the evolution of the VBM and CBM states under compression, trends that ultimately lead to metallization at significantly higher pressures.

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

Introducing bioderived solvents for safer and more sustainable 19 F benchtop NMR analysis of pyrolysis oils

The development of increasingly sustainable analytical chemistry techniques is a growing area of research. Detailed knowledge of bio-oil composition is crucial for the wider use of this alternative, sustainable fuel product, whether by guiding and optimising the pyrolysis processes or for indicating appropriate upgrading methods. The oxygen-containing species in the oil are most important to analyse as they are key to the long-term stability and further processing of the oil. A common analytical method is derivatisation, inserting 19 F nuclei only into specific compounds in the sample, so that a sparser NMR spectrum of a subset of the compounds present can be acquired with even a benchtop NMR spectrometer. However, the derivatisation reactions themselves are not benign, with the most commonly used method relying on DMF throughout. While DMF is highly effective in facilitating the derivatisation reaction, it is not only harmful but increasingly restricted in use. By substituting DMF with ethyl lactate, the reaction is rendered safer and more sustainable. The change in solvent does not affect the NMR results, with estimates of total carbonyl content comparable with those produced by titration. The spectra acquired are detailed enough to also allow the quantification of the different carbonyl functional groups present. By switching to ethyl lactate, it is possible to increase the amount of water in the solvent mixture, further reducing the environmental impact, user risks and cost of the analytical method. By replacing harmful solvents with greener alternatives, benchtop NMR analyses of pyrolysis oils are increasingly safer to run, increasingly cheaper to run, and increasingly more accessible to a wide range of different users.

Tang, Bridget [Aston University, Birmingham (Unite↗
DOE OSTI2025

Thoroughly testing and integrating hundreds of Pull Requests per month: ROOT’s new Cost-efficient and Feature Rich GitHub-based CI

ROOT is an open source framework, freely available on GitHub, at the heart of data acquisition, processing and analysis of HE(N)P experiments, and beyond. It is developed collaboratively: contributions are not authored only by ROOT team members, but also by the user community at large: developers and scientists from universities, labs as well as the private sector. More than 1500 GitHub Pull Requests are merged on average per year. It is in this context that code integration acquires a primary role. The review of code contributions isn’t enough: not only they need to be thoroughly reviewed, they also need to be thoroughly tested through a powerful CI infrastructure on several different platforms to comply with the high code quality standards of the project. Since the end of 2023, ROOT moved its continuous integration system from Jenkins to GitHub Actions. In this contribution, we characterise the transition to the GitHub CI, focussing on our strategy, its implementation and the lessons learned, as well as the advantages the new system offers with respect to the previous one. Particular emphasis will be given to the evaluation of the cost-benefit ratio for Jenkins and GitHub Actions for the ROOT project. We also describe how we manage to run in less than one hour thousands of unit, integration, functional and end-to-end tests on different flavours of Windows, four versions of macOS, as well as about ten of the most used Linux distributions, taking advantage of the CERN computing infrastructure.

Piparo, Danilo [CERN]↗
DOE OSTI2022

Piecewise interaction picture density matrix quantum Monte Carlo

The density matrix quantum Monte Carlo (DMQMC) set of methods stochastically samples the exact N-body density matrix for interacting electrons at finite temperature. We introduce a simple modification to the interaction picture DMQMC (IP-DMQMC) method that overcomes the limitation of only sampling one inverse temperature point at a time, instead allowing for the sampling of a temperature range within a single calculation, thereby reducing the computational cost. At the target inverse temperature, instead of ending the simulation, we incorporate a change of picture away from the interaction picture. The resulting equations of motion have piecewise functions and use the interaction picture in the first phase of a simulation, followed by the application of the Bloch equation once the target inverse temperature is reached. We find that the performance of this method is similar to or better than the DMQMC and IP-DMQMC algorithms in a variety of molecular test systems.

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

Accurate numerical simulations of open quantum systems using spectral tensor trains

Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. Here, the spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

This study focuses on a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture to aid in the discovery and mitigation of compromised Human Machine Interface (HMI)/Instrumentation & Control (I&C) based systems for modifying a prototypical reactor condition test facility called the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). This is achieved through a three-layered combination of network security solutions, hash-based algorithms, and blockchain technologies. Hash algorithms are mathematical functions used to generate a predetermined set of fixed-length values. They are widely used in computer security to verify the integrity of system information and data, both on a local network and the wider internet. Even small amounts of unauthorized system modification will cause the hash algorithm to output a set of characters that deviate significantly from its original value. Assisting secure hash functions, blockchain technology is a secure and distributed technology used to provide an immutable set of records replicated on all devices within a decentralized network. Blockchain offers a cost-effective solution to detect system compromise by providing a traceable breadcrumb trail of all network activity and data modification happening on a system. If both are used in conjunction with network monitoring tools, the integration of this three-pronged approach can become an asset in detecting suspected system compromises before any real damage can occur.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Editorial: Lignocellulose valorization: Fractionation, conversion and applications

Lignocellulosic biomass is the most abundant form of renewable feedstock on the Earth. Chemicals, energies, and materials derived from lignocellulosic biomass are renewable and sustainable, and have the potential to replace fossil feedstocks. Biorefinery, a process to fractionate lignocellulose into the three major components, is considered the most pivotal step for bioenergy, biomaterials and biochemicals. However, due to the complex hierarchy and chemical structures, only limited lignocellulose is valorized into value-added products, and most of them are burnt or just discarded. Therefore, there is a need to investigate the heterogeneous structure of lignocellulose, improve its efficient fractionation into cellulose, hemicelluloses and lignin, and develop the technology that can convert the lignocellulose into high-value chemical products and high-performance functional materials in a sustainable and promising configuration. In short, the ultimate goal of biomass utilization is that the production of biofuels and biomaterials in industrial applications must be cost-, and performance-competitive with petroleum-derived equivalents.

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

Oscilloscope Data Push Program

This paper details the development of a Python program designed to automate the data acquisition and conversion for an oscilloscope for the purposes of a one-off/temporary data acquisition system for users that readily need data, and do not have the option of obtaining a Data Acquisition (DAQ) solution. Creating DAQ systems for analyzing a system requires expensive electronics and a dedicated team of engineers for support. Traditionally, manual data collection and processing are time consuming and prone to error. By automating these processes, the cost, efficiency and accuracy of data handling are improved upon. This project involves the creation of a program that interacts with the oscilloscope. During this interaction, there are various functions being performed such as the acquisition of waveform data via floating points, generating plots with the acquired wave points, and storing of floating points in a CSV file format for future reference and plotting purposes. While the initial aim of the project included continuous logging to a cloud database, this was deferred due to time constraints. The results portrayed an almost-instant rate of data collection with a buffer time, showcasing the potential for further integration and real-time data processing.

Osei-Tutu, Jason↗