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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Development & Validation of Low-Cost, Highly-Durable, Spinel-Based Materials for SOFC Cathode-Side Contact (Final Report)

A cathode-side contact layer is required to provide and maintain stable electrical conduction paths between the interconnect and cathode in a solid oxide fuel cell (SOFC) stack assembly and thus minimize the ohmic resistance and stack power loss. Current cathode-interconnect contact materials are based on noble metals, electrically-conductive perovskites, their composite materials, etc. These materials are either too expensive or do not possess the overall balanced performance required for the cathode-side contact application. To achieve the DOE SOFC system cost and performance stability goals, a new generation of low-cost, high-performance contact materials needs to be developed. In this project, spinel-based materials thermally converted from the Fe-Ni and Co-Mn based alloy precursors were developed and validated for the cathode-side contact application. The precursor alloy compositions were optimized via a combination of composition screening in the (Ni,Fe) 3 O 4 and (Mn,Co) 3 O 4 spinel system, alloy design using physical metallurgy principles, and cost considerations. The alloy powders with the desired composition and particle size were manufactured via gas atomization. The optimal process parameters for thermal conversion of these alloy precursor layers to a spinel-based layer were identified, i.e., 900°C x 2h in air, which is close to the initial stack firing condition. The area-specific resistances (ASRs) of the interconnect/contact/cathode test assemblies with the developed contact layer were determined for various durations (up to 5000 h) under simulated cathodic operation conditions. Some of the alloy-derived spinel contacts exhibited the lowest ASR and ASR degradation rate. The in-stack performance of the most promising alloy-derived contact layer is currently being evaluated via stack testing. To reduce the stack cost, the Co-Mn based alloy powders were utilized as the precursor for synthesis of dense spinel-based interconnect coating. By optimizing both the initial powder size/distribution and the alloy powder composition, a dense (Mn,Co) 3 O 4 -based spinel coating was achieved. Furthermore, co-sintering of the coating/contact dual-layer structure under the initial stack firing condition was realized by utilizing the tailored Co-Mn alloy precursors. Cost analysis of the developed technology indicated a total stack cost reduction of around 10.6% with the implementation of co-sintering of the interconnect coating and the contact layer during initial stack firing. Since low-cost processes such as screen printing is utilized in the precursor application and no reduction heat treatment is needed for the coating formation, the developed technology can be readily implemented at the industrial partner’s manufacturing facilities with no additional capital investment needed.

08 HYDROGEN↗
DOE OSTI2021

Nanoscale cooperative adsorption for materials control

Abstract Adsorption plays vital roles in many processes including catalysis, sensing, and nanomaterials design. However, quantifying molecular adsorption, especially at the nanoscale, is challenging, hindering the exploration of its utilization on nanomaterials that possess heterogeneity across different length scales. Here we map the adsorption of nonfluorescent small molecule/ion and polymer ligands on gold nanoparticles of various morphologies in situ under ambient solution conditions, in which these ligands are critical for the particles’ physiochemical properties. We differentiate at nanometer resolution their adsorption affinities among different sites on the same nanoparticle and uncover positive/negative adsorption cooperativity, both essential for understanding adsorbate-surface interactions. Considering the surface density of adsorbed ligands, we further discover crossover behaviors of ligand adsorption between different particle facets, leading to a strategy and its implementation in facet-controlled synthesis of colloidal metal nanoparticles by merely tuning the concentration of a single ligand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Techno-economic prospects for producing Fischer-Tropsch jet fuel and electricity from lignite and woody biomass with CO 2 capture for EOR

This work explores the prospective techno-economic performance of facilities that produce low- and net-negative-carbon liquid transportation fuels and electricity with CO 2 capture for enhanced oil recovery. The lignite and biomass-to-jet fuel process is based on KBR’s TRIG gasifier, Rectisol (for sulfur removal and CO 2 capture), fixed-bed low temperature Fischer-Tropsch synthesis of liquid fuels, and Brayton/Rankine combined cycles to convert synthesis/refining off-gases and waste heat to electricity. This work leverages a recent, highly-detailed assessment of a prospective first-of-a-kind (FOAK) demonstration facility to develop highly detailed Aspen Plus process simulations for nine prospective N th -of-a-kind (NOAK) plant equipment configurations. Component-level capital costs from the FOAK study are scaled and adjusted to reflective prospective learning-by-doing to estimate capital costs for the NOAK designs. NOAK plant economic performance is found to be largely insensitive to variations in plant configurations and electricity output fraction, but biomass input fraction significantly affects profitability. Facilities that consume only carbon–neutral biomass, with no lignite co-feed, have significantly net-negative carbon emissions and the most favorable prospective economics when carbon emissions are priced. For these facilities, the crude oil price required for plant economic viability falls rapidly from $\$$100/bbl as carbon emission prices increase above $\$$120/tonne CO 2eq . In general, plants that co-fire lignite with biomass are less profitable (than 100% biomass plants) due to their higher net greenhouse gas emissions.

09 BIOMASS FUELS↗
DOE OSTI2022

Observation of formation and local structures of metal-organic layers via complementary electron microscopy techniques

Abstract Metal-organic layers (MOLs) are highly attractive for application in catalysis, separation, sensing and biomedicine, owing to their tunable framework structure. However, it is challenging to obtain comprehensive information about the formation and local structures of MOLs using standard electron microscopy methods due to serious damage under electron beam irradiation. Here, we investigate the growth processes and local structures of MOLs utilizing a combination of liquid-phase transmission electron microscopy, cryogenic electron microscopy and electron ptychography. Our results show a multistep formation process, where precursor clusters first form in solution, then they are complexed with ligands to form non-crystalline solids, followed by the arrangement of the cluster-ligand complex into crystalline sheets, with additional possible growth by the addition of clusters to surface edges. Moreover, high-resolution imaging allows us to identify missing clusters, dislocations, loop and flat surface terminations and ligand connectors in the MOLs. Our observations provide insights into controllable MOL crystal morphology, defect engineering, and surface modification, thus assisting novel MOL design and synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Biomass Gasification for Chemicals Production Using Chemical Looping Techniques (Final Report)

The Ohio State University (OSU) is investigating the Biomass to Syngas (BTS) chemical looping technology to produce syngas for chemical production applications from biomass under US Department of Energy (DOE) Award #DE-EE0007530. The BTS process aligns with the programmatic area of interest of “Conversion, via biological, thermal, catalytic or chemical means, of acceptable feedstocks into advanced biofuels and/or biobased products including intermediate and end-use products”. Compared to conventional biomass gasification processes, the BTS process eliminates the need for air separation units and tar reforming reactors, which leads to energy efficiency improvement and capital cost reduction. The overall objective is to ascertain the potential of biomass gasification based on the chemical looping technique through mitigation of the possible techno-economic challenges in the steps of scale up for commercialization. The scope of work consists of 1) designing, constructing and operating a 10 kWth commercially scalable sub-pilot BTS system and; 2) completing a comprehensive techno-economic analysis (TEA) of the BTS process using methanol production as an example. Over the course of the project, the project team completed the design, fabrication, and operation of a 10 kWth sub-pilot scale test unit for the BTS process. Corn cob and wood pellets were successfully tested in the unit for high purity syngas generation in extended test campaigns that totals over 200 hours. Syngas purity (H2 and CO) of >70% was achieved with a CH 4 concentration of <6%. The H 2 /CO ratio was greater than 1.8. A comprehensive techno-economic analysis was performed to compare the BTS process and a reference indirectly heated gasification process for methanol synthesis. The result, updated with experimental results for BTS process performance, shows a methanol required selling price (MSP) of $\$ $1.15/gal, compared to $1.28/gal for the reference case.

08 HYDROGEN↗
DOE OSTI2020

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge

Nanomaterials of varying compositions and morphologies are of interest for many applications from catalysis to optics, but the synthesis of nanomaterials and their scale-up are most often time-consuming and Edisonian processes. Information gleaned from the scientific literature can help inform and accelerate nanomaterials development, but again, searching the literature and digesting the information are time-consuming manual processes for researchers. To help address these challenges, here we developed scientific article-processing tools that extract and structure information from the text and figures of nanomaterials articles, thereby enabling the creation of a personalized knowledgebase for nanomaterials synthesis that can be mined to help inform further nanomaterials development. Starting with a corpus of ~35k nanomaterials-related articles, we developed models to classify articles according to the nanomaterial composition and morphology, extract synthesis protocols from within the articles’ text, and extract, normalize, and categorize chemical terms within synthesis protocols. We demonstrate the efficiency of the proposed pipeline on an expert-labeled set of nanomaterials synthesis articles, achieving 100% accuracy on composition prediction, 95% accuracy on morphology prediction, 0.99 AUC on protocol identification, and up to a 0.87 F1-score on chemical entity recognition. In addition to processing articles’ text, microscopy images of nanomaterials within the articles are also automatically identified and analyzed to determine the nanomaterials’ morphologies and size distributions. To enable users to easily explore the database, we developed a complementary browser-based visualization tool that provides flexibility in comparing across subsets of articles of interest. We use these tools and information to identify trends in nanomaterials synthesis, such as the correlation of certain reagents with various nanomaterial morphologies, which is useful in guiding hypotheses and reducing the potential parameter space during experimental design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adaptive Computing and Multi-Fidelity Strategies for Control, Design and Scale-Up of Renewable Energy Applications

We describe our ongoing research in adaptive computing and multi-fidelity modeling strategies. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. These strategies are being implemented into a software framework with a generalized API allowing its application to a broad range of applications, from power grid stability and buildings control to material synthesis and biofuels processing. We will discuss a few examples from these applications that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.

adaptive computing↗
DOE OSTI2020

Atomically Precise Membranes for the Separation of Gases

Industrial separations require enormous amounts of energy, accounting for approximately half the industrial energy use and 10–15% of the total energy consumption. Distillation alone accounts for about half the energy demand for industrial separations. If these processes could be replaced by an energy-efficient membrane separation process, this energy demand could be reduced by 90%. However, although some membrane processes have made inroads into thermal distillation, for membrane-based separations to replace the distillation process to a far more significant and practical level, new membranes with higher robustness, selectivity, and flux still need be developed. In this membrane development program, we leveraged Temple University’s prior work in spiroligomers to develop robust membrane structures. These structures can be formed into atomically precise pores by controlling the chemical synthesis and the oligomer building blocks to first build precisely controlled macrocycles and then subsequently crosslinking these macrocycles to produce a membrane. Furthermore, through the highly controllable chemistry of our molecular building blocks, not only can we integrate pores with highly controllable and reproducible size and morphology, but we can also target internal functionalization. By using a range of scalable membrane synthesis approaches, combined with control of each and every pores internal chemistry and molecular conformation we can achieve membrane structures that can display the ultimate in high selectivity and permeance. The Mainstream-Temple University membranes can be designed to achieve ultra-selective separations based on the key factors of molecular size, shape, and functionality. In our approach to fabricate scalable atomically precise membranes, we used our molecular Lego nanostructures. We demonstrated an approach to create atomically precise pores within the membrane with pores that are the dimensions of the molecule we are trying to separate. Moreover, in addition to controlling the morphology of the membrane structure by controlling the size of every pore, we can also decorate every pore with precisely targeted and placed functional groups. These accurately placed functional groups can provide selective binding to molecules and provide enhanced selectivity via a facilitated transport mechanism. In Phase II, the Mainstream-Temple University team demonstrated the scalable synthesis of oligomers and the ability to control the pore internal and external functionality, or chemistry, to allow the fabrication of a thin-film membrane. The initial steps of the spiroligomer synthesis to produce the two key bis-amino enantiomer building blocks were scaled from the gram scale to the kilogram scale, obtaining 25 kg of the materials by transferring the procedure to a toll manufacturer. Finally, we successfully optimized the fabrication of these macrocycles into robust membranes. We successfully transitioned from a laboratory based, hard-to-scale Langmuir trough synthesis to a highly scalable, roll-to-roll applicable, interfacial polymerization process. During this Phase II program, we established a platform of atomically precise membranes where our highly controllable, atomically precise macrocycles served as a scaffold with precisely and uniformly controlled pores. Furthermore, this layer can be tailored to accommodate a diverse range of functional groups, which both further controlled the pore size to enhance the sieving effect as well as imparting precisely controlled targeted selectivity through biomimetic molecular interactions. In this Phase II, we established and scaled up a platform approach to both tune the pore size and chemistry as well as scale it to produce membranes that can be applied to a wide range of industries. In future development, the project team expects to scale up both the macrocycle building block production and interfacial polymerization process to produce the atomically precise membrane with targeted pore sizes and pore chemistries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Glycerol-based sustainably sourced resin for volumetric printing

Volumetric Additive Manufacturing (VAM) represents a revolutionary advancement in the field of Additive Manufacturing, as it allows for the creation of objects in a single, cohesive process, rather than in a layer-by-layer approach. This innovative technique offers unparalleled design freedom and significantly reduces printing times. A current limitation of VAM is the availability of suitable resins with the required photoreactive chemistry and from sustainable sources. To support the application of this technology, we have developed a sustainable resin based on polyglycerol, a bioderived (e.g., vegetable origin), colourless, and easily functionisable oligomer produced from glycerol. To transform polyglycerol-6 into an acrylate photo-printable resin we adopted a simple, one-step, and scalable synthesis route. Polyglycerol-6-acrylate fulfils all the necessary criteria for volumetric printing (transparency, photo-reactivity, viscosity) and was successfully used to print a variety of models with intricate geometries and good resolution. The waste resin was found to be reusable with minimal performance issues, improving resin utilisation and minimising waste material. Furthermore, by incorporating dopants such as poly(glycerol) adipate acrylate (PGA-A) and 10,12-pentacosadyinoic acid (PCDA), we demonstrated the ability to print objects with a diverse range of functionalities, including temperature sensing probes and a polyester excipient, highlighting the potential applications of these new resins.

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

Performance of a Natural Gas Solid Oxide Fuel Cell System With and Without Carbon Capture

The fuel cell program at the United States Department of Energy (DOE) National Energy Technology Laboratory (NETL) is focused on the development of low-cost, highly efficient, and reliable fossil-fuel-based solid oxide fuel cell (SOFC) power systems that can generate environmentally-friendly electric power with at least 90 percent carbon capture. NETL’s SOFC technology development roadmap is aligned with near-term market opportunities in the distributed generation sector to validate and advance the technology while paving the way for utility-scale natural gas (NG)- and coal-derived synthesis gas-fueled applications via progressively larger system demonstrations. The present study represents a part of a series of system evaluations being carried out at NETL to aid in prioritizing technological advances along research pathways to the realization of utility-scale SOFC systems, a transformational goal of the fuel cell program. In particular, the system performance of utility-scale NG fuel cell (NGFC) systems with and without carbon dioxide (CO2) capture is presented. The NGFC system analyzed features an external auto-thermal reformer (ATR) feeding the fuel to the SOFC system consisting of planar anode-supported SOFC with separated anode and cathode off-gas streams. In systems with CO2 capture, an air separation unit (ASU) is used to provide the oxygen for the ATR and for the combustion of unutilized fuel in the SOFC anode exhaust along with a CO2 purification unit to provide a nearly pure CO2 stream suitable for transport for usage in enhanced oil recovery operations or for storage in underground saline formations. Remaining thermal energy in the exhaust gases is recovered in a bottoming steam Rankine cycle while supplying any process heat requirements. A reduced order model (ROM) developed at the Pacific Northwest National Laboratory (PNNL) is used to predict the SOFC performance. The ROM, while being computationally effective for system studies, provides other detailed information about the state of the stack, such as the internal temperature gradient, generally not available from simple performance models often used to represent the SOFC. Such additional information can be important in system optimization studies to preclude operation under off-design conditions that can adversely impact overall system reliability. The NGFC system performance was analyzed by varying salient system parameters, including the percent of internal (to the SOFC module) NG reformation—ranging from 0 to 100 percent—fuel utilization, and current density. The impact of advances in underlying SOFC technology on electrical performance was also explored.

solid oxide fuel cell (SOFC), natural gas fuel cel↗
DOE OSTI2021

Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach

Abstract Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged, practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction channels. To directly probe these effects, we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit description. We parameterize the framework for Li 7- x La 3 Zr 2 O 12 (LLZO) garnet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered systems. Systematically designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO, quantified by newly defined metrics that characterize the complex ionic transport mechanism. Our results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data, while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is highest. Additional implications of our results are discussed, including a possible connection between ion conduction behavior and dendrite formation.

25 ENERGY STORAGE↗
DOE OSTI2026

Emergence of low-energy spin waves in superconducting electron-doped cuprates

In order to fully utilize the technological potential of unconventional superconductors, an enhanced understanding of the superconducting mechanism is necessary. In the best performing superconductors, the cuprates, superconductivity is intimately linked with magnetism, although the details of this coupling remain elusive. Here, we address this gap by studying the electron-doped cuprate Nd 1.85 Ce 0.15 CuO 4−δ that has an antiferromagnetic ground state when synthesized and only becomes superconducting after a reductive annealing process. Using neutron spectroscopy, we show that the as-grown crystal exhibits a large spin pseudogap in the magnetic fluctuation spectrum. Annealing removes defects introduced by the commonly employed synthesis method and significantly reduces the spin pseudogap. While the spin pseudogap in the annealed sample likely arises from superconductivity, in the as-grown sample it results from the absence of long-wavelength spin waves. These results reveal a direct connection between defects, magnetism, and superconductivity, offering new insight into the mechanisms underlying high-temperature superconductivity and guiding the design of improved superconducting materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

The effect of varying powder feedstock chemistry and printing atmosphere on the microstructure of additively manufactured nickel-based ODS alloys: Role on stabilization of cellular structures vs. oxide dispersion formation

Nickel-based alloys have a wide variety of structural applications due to their high corrosion resistance and mechanical strength which depend on solid solution strengthening, or the formation of oxides and/or intermetallic precipitation for their properties. In this study, the microstructure of six Ni–Cr–Y–Ti–Al powder batches designed for the production of oxide dispersion strengthened nickel were compared. These batches varied in chemistry and atomization technique used which included Gas Atomization Reactive Synthesis (GARS). The batches of powder were then consolidated via Additive Manufacturing (AM) Powder Bed Fusion using Laser Beam (PBF-LB) and characterized via transmission electron microscopy to elucidate the influence of powder feedstock (i.e. synthesis methodology and chemistry) on the PBF-LB microstructure. The study investigates (i) how the amount of yttrium and titanium additions in the powder feedstock and the addition of oxygen during the processing (through GARS) affect the microstructure of the powder itself and the AM printed microstructure, and (ii) how the control of oxygen addition in the printing atmosphere during the PBF-LB printing process itself is another important parameter for achieving the formation of the wanted oxide dispersion versus the stabilization of the cellular structure (often observed in AM processed alloys). Microstructural characterization of both powder particles and additively manufactured nickel alloys in this study provide important insights into the movement of yttrium within the material upon solidification, particularly along cell boundaries, and how yttrium behaves depending on alloy chemistry. When a threshold of yttrium content is reached within the system, yttrium consistently reacts to form an intermetallic along cell boundaries instead of forming oxide nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Designing Sequence-Defined Peptoids for Biomimetic Control over Inorganic Crystallization

Crystallization defines what the world is all about, ranging from biomineralization in living organisms to various materials in our lives. During these processes, biomineralization set a superexcellent example of the additive-controlled crystallization. However, the high complexity and low stability of peptides and proteins preclude their wide applications in controlling inorganic crystallization beyond the biological systems. Peptoids are one type of sequence-defined biomimetic polymers with a simple structure, high stability, protein-like molecular recognition, and distinctive self-assembly properties. They provide a promising alternative to mimic peptides and proteins for controlling inorganic crystallization and extend its application to predictive materials synthesis. In this review article, we extract the main concepts of peptoid engineering and highlight the recent advances in peptoid-controlled inorganic crystallization. Our focus is to understand the principles of sequence engineering that lead to the predictable physiochemical properties of these substances, which will give insights into other inorganic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Uncertainty-aware mixed-variable machine learning for materials design

Abstract Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods. Bayesian optimization (BO) employs uncertainty-aware machine learning models to select promising designs to evaluate, hence reducing the cost. However, BO with mixed numerical and categorical variables, which is of particular interest in materials design, has not been well studied. In this work, we survey frequentist and Bayesian approaches to uncertainty quantification of machine learning with mixed variables. We then conduct a systematic comparative study of their performances in BO using a popular representative model from each group, the random forest-based Lolo model (frequentist) and the latent variable Gaussian process model (Bayesian). We examine the efficacy of the two models in the optimization of mathematical functions, as well as properties of structural and functional materials, where we observe performance differences as related to problem dimensionality and complexity. By investigating the machine learning models’ predictive and uncertainty estimation capabilities, we provide interpretations of the observed performance differences. Our results provide practical guidance on choosing between frequentist and Bayesian uncertainty-aware machine learning models for mixed-variable BO in materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Design for Carbon Conversion Product Pathways with Nuclear Power Plant Integration (PCC)

Coal is a globally abundant resource that historically has been used for power generation via combustion. As the power industry replaces coal with cleaner methods of generation, energy rich coal could be used in other chemical and fuel applications. This study presents a coal utilization option in which coal combustion is replaced with a carbon-free nuclear power plant and the coal is upgraded to valuable products for a variety of markets. Coal is prepared for conversion first by the pyrolysis process, which will optimize solid, liquid, and gaseous products based on the market size and potential product value, maximizing the monetary value of coal. This process is designed using bituminous coal from the Appalachian region as a basis to provide a pathway to preserve or transition coal-related jobs and create new jobs associated with the clean energy transition. Process modeling will be used to determine each component’s sensitivities, costs, inputs, and outputs Advanced and light-water reactors are considerations to supply the heat, steam, and electricity to the process. This paper focuses on the technical and market analysis used to determine the optimal processes and product pathways for the carbon refinery. Product pathways are on activated carbon, formic acid synthesis, and methanol synthesis for further upgrading to marketable chemical and polymer products.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Hierarchical and scalable integration of nanostructures for energy and environmental applications: a review of processing, devices, and economic analyses

Hierarchical nanostructure, an engineered nanostructure with a higher assembly-level of constituents by low dimensional nano-building blocks, has received extensive attentions in the latest advancements in nanomaterial science and nanotechnology development. The ordered hierarchical nanostructures could offer merits such as more active sites, synergistic properties owing to their geometric complexity and building blocks variation, as well as the resultant multi-functional capabilities. In this review, we specifically focus on the integration approaches that may be feasible for large-scale production and manufacturing of engineered nanomaterials for various industrial applications, and the design criteria of hierarchical nanostructures targeted at various sustainable energy and environmental applications. In addition to chemical synthesis and integration methods, the development and application of hierarchical nanostructures are surveyed in energy conversion, generation, storage, utilization, and sensing devices. Meanwhile, a much-needed survey is also touched upon the techno-economic analyses of engineered nanomaterials, proposing the need of establishing various standard protocols on various factors and parameters that could be envisaged as a guide toward the viable transition to the practices in the future nano-industries.

77 NANOSCIENCE AND NANOTECHNOLOGY↗