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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Computational simulation of vibrationally resolved spectra for spin‐forbidden transitions

Abstract In this computational study, we illustrate a method for computing phosphorescence and circularly polarized phosphorescence spectra of molecular systems, which takes into account vibronic effects including both Franck‐Condon and Herzberg‐Teller contributions. The singlet and triplet states involved in the phosphorescent emission are described within the harmonic approximation, and the method fully takes mode‐mixing effects into account when evaluating Franck‐Condon integrals. Spin‐orbit couplings, which are responsible for these otherwise forbidden phenomena, are accounted for by means of a relativistic two‐component time‐dependent density functional theory method. The model is applied to two types of chiral systems: camphorquinone, a rigid organic system that allows for an extensive benchmark, and some members of a class of iridium complexes. The merits and shortcomings of the methods are discussed, and some perspectives for future developments are offered.

Egidi, Franco↗
DOE OSTI2017

Computer-Assisted Diagnosis System for Breast Cancer in Computed Tomography Laser Mammography (CTLM)

Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633–643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images. The proposed CAD system contains three main stages including segmentation of volume of interest (VOI), feature extraction and classification. A 3D Fuzzy segmentation technique has been implemented to extract the VOI. The shape and texture of angiogenesis in CTLM images are significant characteristics to differentiate malignancy or benign lesions. The 3D compactness features and 3D Grey Level Co-occurrence matrix (GLCM) have been extracted from VOIs. Multilayer perceptron neural network (MLPNN) pattern recognition has developed for classification of the normal and abnormal lesion in CTLM images. The performance of the proposed CAD system has been measured with different metrics including accuracy, sensitivity, and specificity and area under receiver operative characteristics (AROC), which are 95.2, 92.4, 98.1, and 0.98%, respectively.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Kinetic-j : A computational kernel for solving the linearized Vlasov equation applied to calculations of the kinetic, configuration space plasma current for time harmonic wave electric fields

We present the Kinetic-j code, a computational kernel for evaluating the linearized Vlasov equation withapplication to calculating the kinetic plasma response (current) to an applied time harmonic wave electricfield. This code addresses the need for a configuration space evaluation of the plasma current to enablekinetic full-wave solvers for waves in hot plasmas to move beyond the limitations of the traditional Fourierspectral methods. We benchmark the kernel via comparison with the standard k-space forms of the hotplasma conductivity tensor.

Green, David L.↗
DOE OSTI2018

Application of X-ray computed tomography for the characterization of graphite morphology in compact-graphite iron

Highlights: • X-ray Tomography is a powerful technique for graphite morphology characterization. • 3D characterization reveals true nodularity and spatial connectivity of graphite. • Tri-modal distribution of SG suggests a multi-stage graphite nucleation process. - Abstract: In the present study, high-energy X-ray tomography technique was used to characterize the graphite morphology of compact graphite iron. The size, shape, spatial connectivity and structure of different graphite morphologies were examined in 3D using computer-aided image analysis. In addition, nodularity analysis was performed in 3D and the results are compared to the traditional 2D technique. It is found that the variation of nodularity within 2 × 2 × 1.2 mm{sup 3} of the sample can be as high as 20 (%) from 2D analysis and the averaged nodularity (2D) is higher than that from 3D analysis. The size distribution of spheroidal graphite shows a tri-modal distribution, which suggests a multi-step nucleation process during solidification.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Exploring the Impact of Nuclear Data Uncertainties in Ultra-high Resolution Gamma Spectroscopy for Isotopic Analysis Using Approximate Bayesian Computation

High purity germanium (HPGe) currently provides the highest readily available resolution gamma detection for a broad range of radiation measurements, but microcalorimetry is a developing option that has considerably higher resolution even than HPGe. Superior microcalorimetry resolution offers the potential to better distinguish closely spaced X-rays and gamma-rays, a common challenge for the low energy spectral region near 100 keV from special nuclear materials, and the higher signal-to-background ratio also confers an advantage in detection limit. As microcalorimetry continues to develop, it is timely to assess the impact of uncertainties in detector and item response functions and in basic nuclear data, such as branching ratios and half-lives, used to interpret spectra in terms of the contributory radioactive isotopes. We illustrate that a new inference option known as approximate Bayesian computation (ABC) is effective and convenient both for isotopic inference and for uncertainty quantification for microcalorimetry. The ABC approach opens a pathway to new and more powerful implementations for practical applications than currently available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2018

A Combined Experimental and Computational Study on the Reaction Dynamics of the 1-Propynyl (CH 3 CC)–Acetylene (HCCH) System and the Formation of Methyldiacetylene (CH 3 CCCCH)

We investigated the 1-propynyl (CH 3 CC; X 2 A 1 ) plus acetylene/acetylene-d 2 (HCCH/DCCD; X 1 Σg + ) under single-collision conditions using the crossed molecular beams method. The reaction was found to produce C 5 H 4 plus atomic hydrogen (H) via an indirect reaction mechanism with a reaction energy of -123 ± 18 kJ mol –1 . Using the DCCD isotopologue, we confirmed that the hydrogen atom is lost from the acetylene reactant. Our computational analysis suggests the reaction proceeds by the barrierless addition of the 1-propynyl radical to acetylene, resulting in C 5 H 5 intermediate(s) that dissociate preferentially to methyldiacetylene (CH 3 CCCCH; X 1 A 1 ) via hydrogen atom emission with a computed reaction energy of -123 ± 4 kJ mol –1 . The barrierless nature of this reaction scheme suggests the 1-propynyl radical may be a key intermediate in hydrocarbon chain growth in cold molecular clouds like TMC-1, where methyl-substituted (poly)acetylenes are known to exist.

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

Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational Screening of Supported Metal Oxide Nanoclusters for Methane Activation: Insights into Homolytic versus Heterolytic C–H Bond Dissociation

Since its discovery in zeolites, the [CuOCu] 2+ motif has played an important role in our understanding of selective methane activation over supported metal oxide nanoclusters. Although there are two known C-H bond dissoci-ation mechanisms, namely homolytic and heterolytic cleavage, most computational studies on optimizing metal oxide nanoclusters for improved methane activation reactivity have focused only on the homolytic mechanism. In this work, both mechanisms were examined for a set of 21 mixed metal oxide complexes of the form of [M 1 OM 2 ] 2+ (M 1 , M 2 = Mn, Fe, Co, Ni, Cu, Zn). Except for pure copper, heterolytic cleavage was found to be the dominant C-H bond activation pathway for all systems. Furthermore, mixed systems including [CuOMn] 2+ , [CuONi] 2+ , and [CuOZn] 2+ are predicted to possess similar methane activation activity as pure [CuOCu] 2+ . Furthermore, these results suggest that both homolytic and heterolytic mechanisms should be considered in computing methane activation energies on supported metal oxide nanoclusters.

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

Toward Computation-Guided Design of Tunable Organic-Inorganic CdS Quantum Dot Binary Superlattices

Combining the advantages of structural programmability in sequence-defined biomimetic molecules and the controllable packing geometry in nanoparticle superlattices, we demonstrate a self-assembled organic-inorganic superlattice whose structure can be altered with the slightest change in the sequence of the organic counterpart. Here, oleate-coated CdS quantum dots (QDs) form a square-packed superlattice with a 1:1 molar equivalence of a di-block amphiphilic peptoid (Nbrpe6Dig) in chloroform. In contrast, no apparent structure is observed in the organic solvent alone. Based on theoretical evidence, we show that the assembly is a binary superlattice where both the CdS QDs and the peptoids serve as building blocks and further predict a correlation between the superlattice structure and the peptoid sequence. The computationally guided prediction is validated by experiments where superlattice transformation is observed with modified peptoids. The mechanism identified in our work inspires new ways to control and tune organic-inorganic hybrid nanomaterial self-assembly.

Qi, Xin↗
DOE OSTI2016

Computational Approach for Epitaxial Polymorph Stabilization through Substrate Selection

With the ultimate goal of finding new polymorphs through targeted synthesis conditions and techniques, we outline a computational framework to select optimal substrates for epitaxial growth using first principle calculations of formation energies, elastic strain energy, and topological information. To demonstrate the approach, we study the stabilization of metastable VO2 compounds which provides a rich chemical and structural polymorph space. We find that common polymorph statistics, lattice matching, and energy above hull considerations recommends homostructural growth on TiO2 substrates, where the VO2 brookite phase would be preferentially grown on the a-c TiO2 brookite plane while the columbite and anatase structures favor the a-b plane on the respective TiO2 phases. Overall, we find that a model which incorporates a geometric unit cell area matching between the substrate and the target film as well as the resulting strain energy density of the film provide qualitative agreement with experimental observations for the heterostructural growth of known VO2 polymorphs: rutile, A and B phases. The minimal interfacial geometry matching and estimated strain energy criteria provide several suggestions for substrates and substrate-film orientations for the heterostructural growth of the hitherto hypothetical anatase, brookite, and columbite polymorphs. These criteria serve as a preliminary guidance for the experimental efforts stabilizing new materials and/or polymorphs through epitaxy. The current screening algorithm is being integrated within the Materials Project online framework and data and hence publicly available.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Computational design of CO-tolerant Pt 3 M anode electrocatalysts for proton-exchange membrane fuel cells

CO is a typical contaminant in hydrogen fuel produced via steam reforming. Development of a CO-tolerant Pt-based anode for the proton-exchange membrane fuel cells (PEMFC) is of great interest to avoid catalyst deactivation caused by strong CO adsorption on Pt. Pt–Ru, Pt–Mo, and Pt 3 Sn are three known Pt-based bimetallic CO-tolerant anode materials. The enhanced CO-tolerance of these alloys has been generally attributed to a bifunctional effect enabling oxidative CO removal at low applied potential and a ligand effect between the two metals which weakens CO bonding and reduces CO surface coverage. In this study, we use density functional theory to calculate surface adsorption states under reaction conditions for Pt-based alloys. Our calculations provide a molecular-level understanding of the enhanced CO-tolerance of Pt alloys induced by the second metal. We find that Mo and Sn dopants promote CO-tolerance by reducing CO surface coverage and enabling CO oxidative removal at low applied potential. In contrast, Ru is not able to promote CO electro-oxidation at the low applied potential of the operating conditions of a PEMFC anode. The CO-tolerance induced by Ru is attributed to the reduction of CO coverage on Pt sites. Based on these mechanisms, we carried out a computational screening of Pt 3 M electrocatalysts for CO-tolerant PEMFC anodes. A number of promising candidates have been identified for experimental examination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Charging toward improved lithium-ion polymer electrolytes: exploiting synergistic experimental and computational approaches to facilitate materials design

Ion-conducting polymer electrolytes are attractive materials for all-solid-state lithium-ion batteries (LiBs) as a result of their potential to improve performance, mitigate safety concerns, and facilitate efficient device processing. Understanding how lithium-ionic transport is influenced by the macromolecular features, such as dielectric strength, solvation site connectivity, monomer segment relaxation timescales, segregation strength, and mesophase composition, is crucial for advancing ion-conducting materials. The integration of experimental and computational efforts can provide comprehensive links between chemical and structural characteristics (e.g., ion solvation, chain mobility, morphology) and macroscopic performance properties, accelerating the adoption of next-generation polymer electrolytes. Furthermore, this perspective highlights several synergistic experimental–computational approaches that have provided unique insights into local ion and polymer interactions, chain dynamics, and thermodynamics to promote the rational design of new ion-conducting polymers. Additionally, this work concludes with several suggested areas in which methodologies can be augmented, novel properties can be realized, and polymer electrolytes can be integrated to generate more robust LiB systems.

25 ENERGY STORAGE↗