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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Validating first-principles molecular dynamics calculations of oxide/water interfaces with x-ray reflectivity data

Metal oxide/water interfaces play a crucial role in many electrochemical and photocatalytic processes, such as photoelectrochemical water splitting, the creation of fuel from sunlight, and electrochemical CO 2 reduction. First-principles electronic structure calculations can reveal unique insights into these processes, such as the role of the alignment of the oxide electronic energy levels with those of liquid water. An essential prerequisite for the success of such calculations is the ability to predict accurate structural models of these interfaces, which in turn requires careful experimental validation. Here we report a general, quantitative validation protocol for first-principles molecular dynamics simulations of oxide/aqueous interfaces. The approach makes direct comparisons of interfacial x-ray reflectivity (XR) signals from experimental measurements and those obtained from ab initio simulations with semilocal and van der Waals functionals. The protocol is demonstrated here for the case of the Al 2 O 3 (001)/water interface, one of the simplest oxide/water interfaces. We discuss the technical requirements needed for validation, including the choice of the density functional, the simulation cell size, and the optimal choice of the thermodynamic ensemble. Our results establish a general paradigm for the validation of structural models and interactions at solid/water interfaces derived from first-principles simulations. Furthermore, while there is qualitative agreement between the simulated structures and the experimental best-fit structure, direct comparisons of simulated and measured XR intensities show quantitative discrepancies that derive from both bulk regions (i.e., alumina and water) as well as the interfacial region, highlighting the need for accurate density functionals to properly describe interfacial interactions. Our results show that XR data are sensitive not only to the atomic structure (i.e., the atom locations) but also to the electron-density distributions in both the substrate and at the interface.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Statistical characteristics of cloud variability. Part 2: Implication for parameterizations of microphysical and radiative transfer processes in climate models

The effects of subgrid cloud variability on grid-average microphysical rates and radiative fluxes are examined by use of long-term retrieval products at the Tropical West Pacific, Southern Great Plains, and North Slope of Alaska sites of the Department of Energy's Atmospheric Radiation Measurement program. Four commonly used distribution functions, the truncated Gaussian, Gamma, lognormal, and Weibull distributions, are constrained to have the same mean and standard deviation as observed cloud liquid water content. The probability density functions are then used to upscale relevant physical processes to obtain grid-average process rates. It is found that the truncated Gaussian representation results in up to 30% mean bias in autoconversion rate, whereas the mean bias for the lognormal representation is about 10%. The Gamma and Weibull distribution function performs the best for the grid-average autoconversion rate with the mean relative bias less than 5%. For radiative fluxes, the lognormal and truncated Gaussian representations perform better than the Gamma and Weibull representations. The results show that the optimal choice of subgrid cloud distribution function depends on the nonlinearity of the process of interest, and thus, there is no single distribution function that works best for all parameterizations. Examination of the scale (window size) dependence of the mean bias indicates that the bias in grid-average process rates monotonically increases with increasing window sizes, suggesting the increasing importance of subgrid variability with increasing grid sizes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High-throughput ab initio design of atomic interfaces using InterMatch

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe 2 . Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl 3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

An optimally tuned range-separated hybrid starting point for ab initio GW plus Bethe–Salpeter equation calculations of molecules

The ab initio GW plus Bethe–Salpeter equation (GW-BSE, where G is the one particle Green's function and W is the screened Coulomb interaction) approach has emerged as a leading method for predicting excitations in both solids and molecules with a predictive power contingent upon several factors. Among these factors are the (1) generalized Kohn–Sham eigensystem used to construct the GW self-energy and to solve the BSE and (2) the efficacy and suitability of the Tamm–Dancoff approximation. Here, we present a detailed benchmark study of low-lying singlet excitations from a generalized Kohn–Sham (gKS) starting point based on an optimally tuned range-separated hybrid (OTRSH) functional. We show that the use of this gKS starting point with one-shot G0W0 and G0W0-BSE leads to the lowest mean absolute errors (MAEs) and mean signed errors (MSEs), with respect to high-accuracy reference values, demonstrated in the literature thus far for the ionization potentials of the GW100 benchmark set and for low-lying neutral excitations of Thiel’s set molecules in the gas phase, without the need for self-consistency. The MSEs and MAEs of one-shot G0W0-BSE@OTRSH excitation energies are comparable to or lower than those obtained with other functional starting points after self-consistency. Additionally, we compare these results with linear-response time-dependent density functional theory (TDDFT) calculations and find GW-BSE to be superior to TDDFT when calculations are based on the same exchange-correlation functional. This work demonstrates tuned range-separated hybrids used in combination with GW and GW-BSE can greatly suppress starting point dependence for molecules, leading to accuracy similar to that for higher-order wavefunction-based theories for molecules without the need for costlier iterations to self-consistency.

McKeon, Caroline A. (ORCID:0000000217373503)↗
DOE OSTI2023

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗
DOE OSTI2020

Powder X-ray diffraction of fluorometholone, C 22 H 29 FO 4

Commercial fluorometholone, CAS #426-13-1, crystallizes in the monoclinic space group P 2 1 (#4) with a = 6.40648(2), b = 13.43260(5), c = 11.00060(8) Å, β = 92.8203(5)°, V = 945.517(5) Å 3 , and Z = 2. A reduced cell search in the Cambridge Structural Database yielded one previous structure determination, using single-crystal data at 292 K. In this work, the sample was ordered from the United States Pharmacopeial Convention (Lot # R032K0) and analyzed as-received. The room temperature (295 K) crystal structure was refined using synchrotron ( λ = 0.412826 Å) powder diffraction data and optimized using density functional theory (DFT) techniques. Hydrogen positions were included as a part of the structure and were re-calculated during the refinement. The diffraction data were collected on beamline 11-BM at the Advanced Photon Source, Argonne National Laboratory, and the powder X-ray diffraction pattern of the compound has been submitted to ICDD® for inclusion in the Powder Diffraction File™. The agreement of the Rietveld-refined and DFT-optimized structures is excellent; the root-mean-square Cartesian displacement is 0.060 Å. In addition to the O–H⋯O hydrogen bonds observed by Park et al. (Park, Y. J., Lee, M. Y., and Cho, S. I. ( 1992 ). “Fluorometholone,” J. Korean Chem. Soc. 36 , 812–817), C–H⋯O hydrogen bonds contribute to the crystal energy.

Gonzalez, Diana↗
DOE OSTI2022

Machine learning reveals factors that control ion mobility in anti-perovskite solid electrolytes

Solid-state batteries are projected to exhibit improved energy densities and safety compared to liquid-electrolyte-based systems. Consequently, the development of solid electrolytes that can conduct cations at rates comparable to that of liquid electrolytes is an active area of research. To facilitate this search it is desirable to understand the chemical and structural features that control ion transport through a crystalline lattice. Here, machine learning (ML) is used to identify features that influence ion mobility in solids, quantify the relative importance of those features, and demonstrate how the variation of individual features alters ion mobility. Adopting the anti-perovskite lattice as a model system, ML algorithms were trained to predict migration barriers from a data set containing hundreds of barriers calculated using density functional theory. In this study, more than 10 6 feature sets of non-redundant descriptors were evaluated for their ability to predict migration barriers. The present analysis correctly reiterates the importance of several features that are known to influence mobility – for example, anion polarizability – but also identifies others whose importance is not widely recognized. Lattice properties such as hopping distance and channel width exhibit the greatest influence on cation mobility. Individual conditional expectation analyses performed on these features shows that barriers decrease as hopping distance decreases and as channel width increases. The defect formation energy – which is commonly associated with the concentration of defects, but not with their mobility – is identified as an important feature for interstitial migration. In sum, this analysis aids in the design of optimal solid electrolytes by simplifying the multi-dimensional design space to a sub-set of properties that are the most important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A priori filtered chemical source term modeling for LES of high Karlovitz number premixed flames

Assumptions behind closure models for the filtered source term are studied a priori using results from DNS of turbulent n-heptane/air premixed flames at varying Karlovitz numbers. Simulations with both detailed chemistry and tabulated chemistry, as well as unity and non-unity Lewis numbers, are used to determine if finite-rate chemistry and differential diffusion effects affect the filtered chemical source terms. While the unfiltered source term shows large fluctuations, the filtered source terms from detailed chemistry and tabulated chemistry are in good agreement at sufficiently large filter widths (Δ ≳ l F ). Using the concept of optimal estimators, it is shown that a tabulation approach using the filtered progress variable and its variance can predict accurately the filtered chemical source terms. Finally, the filtered source terms from the DNS are compared to predictions from two commonly assumed sub-filter probability density function models. Both models show deviations from the filtered DNS source terms but predict accurately the mean turbulent flame speed. In conclusion, the results illustrate the potential of using simple tabulated chemistry approaches based on presumed PDFs for LES of premixed flames in the thin and distributed reaction zones regimes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Oxygen Evolution on Iron Oxide Nanoparticles: The Impact of Crystallinity and Size on the Overpotential

The oxygen evolution reaction (OER) is a critical reaction in electrolysis and photoelectrolysis of water to generate and store clean energy. Therefore, the development of low-cost and efficient electrocatalysts for the OER is of great scientific and technological importance. Although promising iron oxide-based electrocatalysts have been recently developed for the OER, an in-depth experimental and theoretical analysis of the OER mechanism on iron oxide-based electrocatalysts is still needed to provide guidelines to optimize the performance of iron oxide-based electrocatalysts further. To address this need, we synthesized a series of monodisperse iron oxide nanoparticles to analyze their intrinsic OER activities. Using nanoparticles of the same size but different crystallinity, we show that amorphous iron oxide nanoparticles have better OER activity than crystalline ones. The size effect studies further revealed that the edge/defect sites are the active sites for the OER. Density functional theory calculations demonstrated that the edge/defect sites provide bridge sites to adsorb OER intermediates, resulting in low OER overpotential. These calculations confirm that the high OER activity of amorphous nanoparticles results from a high concentration of defect sites on their surface. These results provide novel strategies to increase the performance of iron oxide-based and likely other oxide-based OER electrocatalysts.

Electrochemistry↗
DOE OSTI2015

Study of components and statistical reaction mechanism in simulation of nuclear process for optimized production of {sup 64}Cu and {sup 67}Ga medical radioisotopes using TALYS, EMPIRE and LISE++ nuclear reaction and evaporation codes

Production of medical radioisotopes is one of the most important tasks in the field of nuclear technology. These radioactive isotopes are mainly produced through variety nuclear process. In this research, excitation functions and nuclear reaction mechanisms are studied for simulation of production of these radioisotopes in the TALYS, EMPIRE and LISE++ reaction codes, then parameters and different models of nuclear level density as one of the most important components in statistical reaction models are adjusted for optimum production of desired radioactive yields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

A Generic Model for Electric Double Layers in Porous Electrodes

The performance of electric-double-layer capacitors (EDLCs) hinges on microscopic charge distributions near the electrode/electrolyte interfaces. Whereas practical EDLCs consist of electrodes made of amorphous porous materials, theoretical understanding of EDLCs is mostly based on EDL structure near a planar surface or on simplistic models that have little relevance to realistic systems. In this work, we propose a spherical shell model to account for both pore size and curvature effects of amorphous porous materials. The EDL structure in spherical shells has been investigated over a broad range of pore sizes and curvatures by use of classic density functional theory. Theoretical results reveal that the curvature effects on convex and concave EDLs are drastically different and that materials with extensive convex surfaces will lead to maximized capacitance. Like a slit pore, the spherical shell model also predicts oscillatory variation of capacitance with pore size, but the oscillatory behavior is magnified as the curvature increases. The joint effects of pore size and curvature identified in this work give new insight into materials design for porous electrodes with optimal EDLC performance.

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

The role of moisture in MgCl 2 salt: A multiscale approach to TES performance

This study presents a comprehensive multiscale analysis to evaluate the influence of moisture on the thermal performance of thermal energy storage systems using magnesium chloride (MgCl 2 ) as the phase-changing material. The system uses graphite foam with 90% relative density to enhance thermal conductivity. The analysis includes thermal conductivity calculations and specific heat capacity for different hydrate phases of MgCl 2 : Anhydrous, Mono, Di, Tetra, and Hexa. These properties were evaluated for the first time using the phonon density of states from Density Functional Theory simulations. Results showed that thermal conductivity decreased, while specific heat capacity increased by a factor of two as the phase changed from anhydrous to hexahydrate. Meso-scale models were created to account for the anisotropy of graphite foam and property variations of the MgCl 2 hydrate phases. Asymptotic Expansion homogenization simulations determined the anisotropic thermal conductivity for all phases. This unique methodology improved simulation accuracy, which matched experimental data for anhydrous MgCl 2 . A parametric study examined various operating conditions and their effect on TES performance. It revealed that higher charging temperatures did not enhance exergy efficiency, but increased discharge mass flow rates improved it due to better heat transfer. Thermal performance evaluated by the exergy efficiency remained consistent across hydrate systems under the tested conditions. Furthermore, the study suggests that this uniformity is linked to missing key data, particularly latent heat and melting point for different hydrates. Overall, it highlights the importance of multiscale effects and accurate material properties in designing and optimizing TES systems.

Molten salt degradation↗
DOE OSTI2021

AENET–LAMMPS and AENET–TINKER : Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials

Machine-learning potentials (MLPs) trained on data from quantum-mechanics based first-principles methods can approach the accuracy of the reference method at a fraction of the computational cost. To facilitate efficient MLP-based molecular dynamics and Monte Carlo simulations, an integration of the MLPs with sampling software is needed. Here, we develop two interfaces that link the atomic energy network (ænet) MLP package with the popular sampling packages TINKER and LAMMPS. The three packages, ænet, TINKER, and LAMMPS, are free and open-source software that enable, in combination, accurate simulations of large and complex systems with low computational cost that scales linearly with the number of atoms. Scaling tests show that the parallel efficiency of the ænet–TINKER interface is nearly optimal but is limited to shared-memory systems. The ænet–LAMMPS interface achieves excellent parallel efficiency on highly parallel distributed memory systems and benefits from the highly optimized neighbor list implemented in LAMMPS. We demonstrate the utility of the two MLP interfaces for two relevant example applications: the investigation of diffusion phenomena in liquid water and the equilibration of nanostructured amorphous battery materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Crystal structure of rivastigmine hydrogen tartrate Form I (Exelon®), C 14 H 23 N 2 O 2 (C 4 H 5 O 6 )

The crystal structure of rivastigmine hydrogen tartrate has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional techniques. Rivastigmine hydrogen tartrate crystallizes in space group P 2 1 (#4) with a = 17.538 34(5), b = 8.326 89(2), c = 7.261 11(2) Å, β = 98.7999(2)°, V = 1047.929(4) Å 3 , and Z = 2. The un-ionized end of the hydrogen tartrate anions forms a very strong hydrogen bond with the ionized end of another anion to form a chain. The ammonium group of the rivastigmine cation forms a strong discrete hydrogen bond with the carbonyl oxygen atom of the un-ionized end of the tartrate anion. These hydrogen bonds form a corrugated network in the bc -plane. Both hydroxyl groups of the tartrate anion form intramolecular O–H···O hydrogen bonds. Several C–H···O hydrogen bonds appear to contribute to the crystal energy. The powder pattern is included in the Powder Diffraction File ™ as entry 00-064-1501.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Structural and electronic properties of Li8ZrO6 and its CO2 capture capabilities: an ab initio thermodynamic approach

The structural, electronic, and phonon properties of Li8ZrO6 are investigated with the application of density functional theory and lattice phonon dynamics. Based on the calculated data, the thermodynamics of CO2 absorption?desorption for Li8ZrO6 is analyzed and compared with those of Li2ZrO3 and Li6Zr2O7. The band gap of Li8ZrO6 is indirect along G?L with a value of 4.74 eV. From the calculated thermodynamic properties of Li8ZrO6 reacting with CO2, we found that Li8ZrO6 could be regenerated at high temperatures (>1100 K). Our results indicated that the lithium zirconate with a lower Li2O/ZrO2 ratio has a lower turnover temperature. Hence, by mixing or doping two or more materials to form a new material, it is possible to find or synthesize CO2 sorbents that can fit the industrial needs for optimal performance. Although the CO2 capture capacity of Li8ZrO6 is much higher than that of Li2ZrO3, the high energy required for regeneration, the capacity loss during long absorption?desorption cycles, solid sintering at high temperature, and the material cost may affect its overall capture performance. Our results also provided some general guidelines for designing new CO2 sorbents.

Duan, Y↗
DOE OSTI2015

The atomistic origin of the extraordinary oxygen reduction activity of Pt 3 Ni 7 fuel cell catalysts

Recently Debe et al. reported that Pt 3 Ni 7 leads to extraordinary Oxygen Reduction Reaction (ORR) activity. However, several reports show that hardly any Ni remains in the layers of the catalysts close to the surface (“Pt-skin effect”). This paradox that Ni is essential to the high catalytic activity with the peak ORR activity at Pt 3 Ni 7 while little or no Ni remains close to the surface is explained here using large-scale first-principles-based simulations. We make the radical assumption that processing Pt–Ni catalysts under ORR conditions would leach out all Ni accessible to the solvent. To simulate this process we use the ReaxFF reactive force field, starting with random alloy particles ranging from 50% Ni to 90% Ni and containing up to ~300 000 atoms, deleting the Ni atoms, and equilibrating the resulting structures. We find that the Pt 3 Ni 7 case and a final particle radius around 7.5 nm lead to internal voids in communication with the exterior, doubling the external surface footprint, in fair agreement with experiment. Then we examine the surface character of these nanoporous systems and find that a prominent feature in the surface of the de-alloyed particles is a rhombic structure involving 4 surface atoms which is crystalline-like but under-coordinated. Using density-functional theory, we calculate the energy barriers of ORR steps on Pt nanoporous catalysts, focusing on the O ad -hydration reaction (O ad + H 2 O ad → OH ad + OH ad ) but including the barriers of O 2 dissociation (O 2ad → O ad + O ad ) and water formation (OH ad + H ad → H 2 O ad ). We find that the reaction barrier for the O ad -hydration rate-determining-step is reduced significantly on the de-alloyed surface sites compared to Pt(111). Moreover we find that these active sites are prevalent on the surface of particles de-alloyed from a Pt–Ni 30 : 70 initial composition. These simulations explain the peak in surface reactivity at Pt 3 Ni 7 , and provide a rational guide to use for further optimization of improved catalytic and nanoporous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Investigation of Proposed Ladderane Biosynthetic Genes from Anammox Bacteria by Heterologous Expression in E. coli

Ladderanes are hydrocarbon chains with three or five linearly concatenated cyclobutane rings that are uniquely produced as membrane lipid components by anammox (anaerobic ammonia-oxidizing) bacteria. By virtue of their angle and torsional strain, ladderanes are unusually energetic compounds, and if produced biochemically by engineered microbes, could serve as renewable, high-energy-density jet fuel components. The biochemistry and genetics underlying the ladderane biosynthetic pathway are unknown, however, previous studies have identified a pool of 34 candidate genes from the anammox bacterium, Kuenenia stuttgartiensis , some or all of which may be involved with ladderane fatty acid biosynthesis. The goal of the present study was to establish a systematic means of testing the candidate genes from K. stuttgartiensis for involvement in ladderane biosynthesis through heterologous expression in E. coli under anaerobic conditions. This study describes an efficient means of assembly of synthesized, codon-optimized candidate ladderane biosynthesis genes in synthetic operons that allows for changes to regulatory element sequences, as well as modular assembly of multiple operons for simultaneous heterologous expression in E. coli (or potentially other microbial hosts). We also describe in vivo functional tests of putative anammox homologs of the phytoene desaturase CrtI, which plays an important role in the hypothesized ladderane pathway, and a method for soluble purification of one of these enzymes. This study is, to our knowledge, the first experimental effort focusing on the role of specific anammox genes in the production of ladderanes, and lays the foundation for future efforts toward determination of the ladderane biosynthetic pathway. Our substantial, but far from comprehensive, efforts at elucidating the ladderane biosynthetic pathway were not successful. We invite the scientific community to take advantage of the considerable synthetic biology resources and experimental results developed in this study to elucidate the biosynthetic pathway that produces unique and intriguing ladderane lipids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Novel Process for Converting Coal to High-Value Polyurethane Products

Battelle has demonstrated a patented process for making high-value, polyurethane (PU) foam from coal, based on preparing liquefied coal via direct liquefaction, converting it to polyols as an intermediate via ozonation, and then making PU foams from these polyols. This process represents a breakthrough in innovative utilization of U.S. coals, and is applicable to bituminous as well as sub-bituminous coals. The resulting PU foam products are projected to have an extremely high value (i.e., over $\$5,000$ /ton), with nearly 100% of carbon utilization from coalderived liquid feedstock, and 31.5% to 43.5% of the carbon in the PU foam polyol product being bio-based. The targeted products represent an extremely large (i.e., over $80 billion/year), existing PU foam market, which could expand into making coatings and adhesives. The process can further help reduce petroleum imports, while improving the economics of PU foam production. This work was completed with funding from the National Energy Technology Laboratory (NETL), with cost share from the State of Ohio’s Ohio Development Services Agency (ODSA) and others, and has advanced the process to 10 kg/day continuous scale and thus to Technology Readiness Level (TRL) 5. A total of 48 coal-based polyols were prepared and evaluated. The initial 28 polyols focused on range finding for ideal conditions. The later 20 polyols were produced as part of process optimizations. These optimizations were targeted around a continuous ozonolysis process to evaluate extended time reactions and to create the necessary intermediate for production of 1-gallon samples of polyol. The most unique attribute of Battelle’s polyol is in the utilization of coal’s aromaticity to gain final foam rigidity. Typically, polyols depend on the isocyanate fraction and cross-linking to gain rigidity. By utilizing coal, we were able to maintain rigidity while reducing the overall hydroxyl value of the polyol. This is important as lower hydroxyl value leads to greater percent weight of the coal-based polyol because less isocyanate is required for foaming. This leads to greater foam cost savings. This report provides the details, process, and process cost models of the conversion of coal to polyols and further to PU foams. Battelle’s process begins with coal liquids. These liquids can be obtained by two processes: coal coking or pyrolysis to produce coal tar, and Battelle’s biobased coal-to-liquids (CTL) process to produce heavy syncrude after liquifying >85% coal. After liquification, Battelle utilizes ozonolysis to create functionalization on the polyaromatic coal structure. The functionalization is then converted to the final polyester polyol through transesterification, or to hydroxyamide polyol through amidification. Equivalent or better standard properties have been obtained for 2 lb/ft 3 density rigid, water and freon-alternative blown foams, including compressive strength, density, R-value, and dimensional stability. Target applications for these foams are insulation, packaging, and energy-absorbing foams. Some exploratory testing also showed promise for adhesives applications. A detailed economic analysis showed that Battelle’s polyol process is economical, at a 140 metric tons per day (MTD) polyol production scale. An attractive return on investment (ROI) at competitive pricing validates the process is ready for a pilot-plant demonstration. A scale-up plan is provided.

01 COAL, LIGNITE, AND PEAT↗