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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Convoluted filtering for process cycle modeling

Principles of materials science and engineering, physics, mathematics, and information science are used to extract knowledge and insights from the process-structure–property-performance relationships hidden in materials data. The process-structure modeling can be accelerated without loss of interpretability, with artificial intelligence tools that mimic the salient features of the process and process-structure relations. In this work, a novel convoluted model-filtering technique was exploited to build and successfully train the Convoluted Filter (CoFi) artifacts for Fe-based alloy heat treatment cycles. The artifacts were pre-trained to filter out deep models that change the surrogate microstructure state after the heat treatment at ambient conditions. Direct representation of the thermal cycle features within knowledge Graph facilitated development of meaningful data models for microstructure evolution, which reduce overfitting to limited datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials

Noncanonical Amino Acids (NCAAs) provide numerous avenues for introduction of novel functionality to peptides and proteins. NCAAs can be incorporated through solid phase synthesis or genetic code expansion in conjugation with heterologous expression of the encoded protein modification. Due to the difficulty of synthesis, wide chemical space and lack of empirically resolved structures modeling the effects of NCAA mutation is critical for rational protein design. To evaluate the structural and functional perturbations NCAAs introduce we utilize molecular potentials that describe the forces in protein structure. Most potentials such as CHARMM are designed to model canonical residues but can be parameterized in include novel NCAAs. Here, in this work, we introduce NCAP a software package to generate CHARMM compatible parameters from quantum chemical calculation. Unlike currently available tools NCAP is designed to recognize NCAA structure and automatically bridge the gap between DFT calculations and potential parameters. For our software we discuss workflow, validation against canonical parameter sets and comparison to published NCAA-protein structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The exo-β- N -acetylmuramidase NamZ from Bacillus subtilis is the founding member of a family of exo-lytic peptidoglycan hexosaminidases

Endo-β-N-acetylmuramidases, commonly known as lysozymes, are well-characterized antimicrobial enzymes that catalyze an endo-lytic cleavage of peptidoglycan; i.e., they hydrolyze the β-1,4-glycosidic bonds connecting N-acetylmuramic acid (MurNAc) and N-acetylglucosamine (GlcNAc). In contrast, little is known about exo-β-N-acetylmuramidases, which catalyze an exo-lytic cleavage of β-1,4-MurNAc entities from the non-reducing ends of peptidoglycan chains. Such an enzyme was identified earlier in the bacterium Bacillus subtilis, but the corresponding gene has remained unknown so far. We now report that ybbC of B. subtilis, renamed namZ, encodes the reported exo-β-N-acetylmuramidase. A ΔnamZ mutant accumulated specific cell wall fragments and showed growth defects under starvation conditions, indicating a role of NamZ in cell wall turnover and recycling. Recombinant NamZ protein specifically hydrolyzed the artificial substrate para-nitrophenyl β-MurNAc and the peptidoglycan-derived disaccharide MurNAc-β-1,4-GlcNAc. Together with the exo-β-N-acetylglucosaminidase NagZ and the exo-muramoyl-L-alanine amidase AmiE, NamZ degraded intact peptidoglycan by sequential hydrolysis from the non-reducing ends. A structure model of NamZ, built on the basis of two crystal structures of putative orthologs from Bacteroides fragilis, revealed a two-domain structure including a Rossmann-fold-like domain that constitutes a unique glycosidase fold. Thus, NamZ, a member of the DUF1343 protein family of unknown function, is now classified as the founding member of a new family of glycosidases (CAZy GH171). NamZ-like peptidoglycan hexosaminidases are mainly present in the phylum Bacteroidetes and less frequently found in individual genomes within Firmicutes (Bacilli, Clostridia), Actinobacteria, and γ-proteobacteria.

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

Effect of pH on Amorphous Calcium Carbonate Structure and Transformation

A number of organisms produce crystalline calcium carbonate via a metastable precursor phase termed amorphous calcium carbonate (ACC). ACC also forms during production of CaCO 3 for industrial purposes, e.g., paper manufacturing and synthesis of fillers for polymers. Previous studies suggest that the local structure of ACC controls crystallization kinetics and pathways, i.e., the crystalline polymorph(s) that form(s) in the process. We used pair distribution function (PDF) analysis to provide evidence that the local structure of ACC gradually changes as the pH of the synthesis solutions is increased from 10.6 to 12.7, at ambient conditions. Here, these changes correlate with the mole fraction of incorporated hydroxide ions, which varies gradually from negligible at pH 10.6 to 0.12 at pH 12.7. At lower pH (10.5), vaterite and calcite formed in less than 2 min, but as the pH increased, the lifetime of ACC increased, and it transformed directly to calcite (i.e., no vaterite intermediate). Although higher pH led to a preferable transformation into calcite with decreasing crystal size, variations in ACC local structure cannot be linked to development of a calcite like motif, as has been suggested. On the basis of comparing the measured vaterite PDF to a range of structural models to determine Ca–Ca distances, we found no obvious structural similarity between vaterite and the ACC precursor either, although such analysis is complicated by the ambiguity of the vaterite structure. Presumably, the absence of vaterite and the prolonged ACC stability with increasing synthesis pH could indicate inhibition of crystal nucleation and growth by hydroxide ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Expression of divergent methyl/alkyl coenzyme M reductases from uncultured archaea

Abstract Methanogens and anaerobic methane-oxidizing archaea (ANME) are important players in the global carbon cycle. Methyl-coenzyme M reductase (MCR) is a key enzyme in methane metabolism, catalyzing the last step in methanogenesis and the first step in anaerobic methane oxidation. Divergent mcr and mcr -like genes have recently been identified in uncultured archaeal lineages. However, the assembly and biochemistry of MCRs from uncultured archaea remain largely unknown. Here we present an approach to study MCRs from uncultured archaea by heterologous expression in a methanogen, Methanococcus maripaludis . Promoter, operon structure, and temperature were important determinants for MCR production. Both recombinant methanococcal and ANME-2 MCR assembled with the host MCR forming hybrid complexes, whereas tested ANME-1 MCR and ethyl-coenzyme M reductase only formed homogenous complexes. Together with structural modeling, this suggests that ANME-2 and methanogen MCRs are structurally similar and their reaction directions are likely regulated by thermodynamics rather than intrinsic structural differences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Ab initio calculations of the optical properties of crystalline and liquid InSb

Ab initio calculations of the electronic and optical properties of InSb were performed for both the crystalline and liquid states. Two sets of atomic structure models for liquid InSb at 900 K were obtained by ab initio molecular dynamics simulations. To reduce the effect of structural peculiarities in the liquid models, an averaging of the two sets of the calculated electronic and optical properties corresponding to the two liquid models was performed. The calculated results indicate that, owing to the phase transition from crystal to liquid, the density of states around the Fermi level increases. As a result, the energy band gap opening near the Fermi level disappears. Consequently, the optical properties change from semiconductor to metallic behavior. Namely, owing to the melting of InSb, the interband transition peaks disappear and a Drude-like dispersion is observed in the optical dielectric functions. The optical absorption at a photon energy of 3.06 eV, which is used in Blu-ray Disc systems, increases owing to the melting of InSb. This increase in optical absorption is proposed to result from the increased optical transitions below 2 eV.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Structural origin of recovered ferroelectricity in BaTi O 3 nanoparticles

Nanoscale BaTiO 3 particles (≈10 nm) prepared by ball-milling a mixture of oleic acid and heptane have been reported to have an electric polarization several times larger than that for bulk BaTiO 3 . In this work, detailed local, intermediate, and long-range structural studies are combined with spectroscopic measurements to develop a model structure of these materials. The X-ray spectroscopic measurements reveal large Ti off-centering as the key factor producing the large spontaneous polarization in the nanoparticles. Temperature-dependent lattice parameter changes reveal the sharpening of the structural phase transitions in these BaTiO 3 nanoparticles compared to the pure nanoparticle systems. In conclusion, sharp crystalline-type peaks in the barium oleate Raman spectra suggest that this component in the composite core-shell matrix, a product of mechanochemical synthesis, stabilizes an enhanced polar structural phase of the BaTiO 3 core nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A simplified regression building thermal modelling method for detached two-floor house in U.S.

The residential building sector accounts for approximately 37% of total U.S. electricity consumption. Within the residential building sector, heating and cooling is the main target for peak load shifting/reduction since it is the largest contributor to peak demand. In fact, the flexibility of residential HVAC loads can provide continuous variation of demand to provide grid services by varying their demand over a baseline. The performance of HVAC load control to provide grid services relies heavily on the accuracy of indoor air temperature or cooling/heating demand predictions and therefore the quality of building model. Besides forward models, popular building models are data-driven models which can be broken down into two categories: gray-box model, e.g. Resistance-Capacitance (RC) model and black-box model. RC model, also called lumped capacitance or network model, which is constituted with electrical analogue pattern with resistance (R) and capacitance (C). In general, RC models require considerable computation burden and long periods of data to train limited number of model coefficients. Black-box models have gained increasing interest due to their capability in analyzing large-scale data and flexibility in practical applications. But, the data-mining based (machine learning algorithms/techniques based) models tend to have invisible model structures which poses a problem when trying to use the model for optimal control or model predictive control of the HVAC system. Hence, there is a continuing need for efficient online system identification techniques, which can provide explicit parameters for the model. Traditional regression models fit well for this specific purpose. This paper presents an innovative way to predict average indoor temperature in separate floors of typical detached residential house. A rolling horizon linear regression model, which includes online adaptive correction component, is proposed to predict the temperature difference between downstairs and upstairs. A RC model is used to predict the overall mean indoor air temperature. Since the adaptive algorithm needs to be implemented online, a less computation-demanding polynomial fitting algorithm is adopted. This kind of fitting problem can be cast as linear regression problem with multiple variables, parameters of which can be efficiently obtained by well-known gradient descent method.The validation is conducted by comparing the predicted results with the results from data-mining based models as well as measured data from a real typical detached two-floor house. The results show that the developed method has satisfactory performance in predicting the building indoor temperature in 1st and 2nd floors.

Cui, Borui↗
DOE OSTI2015

Conditional random fields for pattern recognition applied to structured data

Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building) or “natural” (such as a tree). Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X) is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs) model structured data using the conditional distribution P(Y|X = x), without specifying a model for P(X), and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches) in the output domain. Second, we identify research topics and present numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Accurate prediction of protein structures and interactions using a three-track neural network

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo–electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. Here, we make the method available to the scientific community to speed biological research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accelerating uncertainty quantification in incremental dynamic analysis using dimension reduction-based surrogate modeling

We propose a surrogate modeling framework based on dimension reduction to facilitate the quantification of seismic risk of structural systems in performance-based earthquake engineering. The framework adopts incremental dynamic analysis (IDA) for addressing hazard variability, and promotes significant computational efficiency improvement for propagating epistemic uncertainties associated with the structural models. It utilizes both linear and nonlinear dimension reduction approaches, equipped with inverse mappings, to learn a functional between the input parameter space (e.g., the epistemic uncertainties of the structure) to the high-dimensional output space created through the IDA implementation across different ground motions and seismic intensity levels. Polynomial chaos expansion is adopted as the surrogate model to learn this functional in the reduced space. A nine-story steel moment-resisting frame with uncertain structural properties is used as a testbed. Furthermore, we select the seismic fragility curves as a measure of the structure’s seismic performance, since it provides an estimate of the probability of entering specified damage states for given levels of ground shaking.

42 ENGINEERING↗
DOE OSTI2014

Bottom-up derivation of conservative and dissipative interactions for coarse-grained molecular liquids with the conditional reversible work method

Molecular simulations of soft matter systems have been performed in recent years using a variety of systematically coarse-grained models. With these models, structural or thermodynamic properties can be quite accurately represented while the prediction of dynamic properties remains difficult, especially for multi-component systems. In this work, we use constraint molecular dynamics simulations for calculating dissipative pair forces which are used together with conditional reversible work (CRW) conservative forces in dissipative particle dynamics (DPD) simulations. The combined CRW-DPD approach aims to extend the representability of CRW models to dynamic properties and uses a bottom-up approach. Dissipative pair forces are derived from fluctuations of the direct atomistic forces between mapped groups. The conservative CRW potential is obtained from a similar series of constraint dynamics simulations and represents the reversible work performed to couple the direct atomistic interactions between the mapped atom groups. Neopentane, tetrachloromethane, cyclohexane, and n-hexane have been considered as model systems. These molecular liquids are simulated with atomistic molecular dynamics, coarse-grained molecular dynamics, and DPD. We find that the CRW-DPD models reproduce the liquid structure and diffusive dynamics of the liquid systems in reasonable agreement with the atomistic models when using single-site mapping schemes with beads containing five or six heavy atoms. For a two-site representation of n-hexane (3 carbons per bead), time scale separation can no longer be assumed and the DPD approach consequently fails to reproduce the atomistic dynamics.

2-2-DIMETHYLPROPANE↗
DOE OSTI2017

Structural insights into the interaction of the conserved mammalian proteins GAPR-1 and Beclin 1, a key autophagy protein

Mammalian Golgi-associated plant pathogenesis-related protein 1 (GAPR-1) is a negative autophagy regulator that binds Beclin 1, a key component of the autophagosome nucleation complex. Beclin 1 residues 267–284 are required for binding GAPR-1. Here, sequence analyses, structural modeling, mutagenesis combined with pull-down assays, X-ray crystal structure determination and small-angle X-ray scattering were used to investigate the Beclin 1–GAPR-1 interaction. Five conserved residues line an equatorial GAPR-1 surface groove that is large enough to bind a peptide. A model of a peptide comprising Beclin 1 residues 267–284 docked onto GAPR-1, built using the CABS-dock server, indicates that this peptide binds to this GAPR-1 groove. Mutation of the five conserved residues lining this groove, H54A/E86A/G102K/H103A/N138G, abrogates Beclin 1 binding. The 1.27 Å resolution X-ray crystal structure of this pentad mutant GAPR-1 was determined. Comparison with the wild-type (WT) GAPR-1 structure shows that the equatorial groove of the pentad mutant is shallower and more positively charged, and therefore may not efficiently bind Beclin 1 residues 267–284, which include many hydrophobic residues. Both WT and pentad mutant GAPR-1 crystallize as dimers, and in each case the equatorial groove of one subunit is partially occluded by the other subunit, indicating that dimeric GAPR-1 is unlikely to bind Beclin 1. SAXS analysis of WT and pentad mutant GAPR-1 indicates that in solution the WT forms monomers, while the pentad mutant is primarily dimeric. Thus, changes in the structure of the equatorial groove combined with the improved dimerization of pentad mutant GAPR-1 are likely to abrogate binding to Beclin 1.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Crystal Structure, Magnetic and Electrical Properties of Half-Doped Chromium Manganite La{sub 0.5}Sr{sub 0.5}Mn{sub 0.5}Cr{sub 0.5}O{sub 3}

Polycrystalline sample La{sub 0.5}Sr{sub 0.5}Mn{sub 0.5}Cr{sub 0.5}O{sub 3} (LSMCO) was prepared by a conventional solid-state reaction method in the air, and its structure was determined by Rietveld refinement using consistent resolution time-of-flight X-ray diffraction. Different structural models have been used for analysis of X-ray diffraction data recorded at room temperature, but the best fits have been found using a mixture of rhombohedral and an orthorhombic structural phases (42(1)%/57(1)%). The rhombohedral, centro-symmetric space group R 3-bar c(No.167,a≈√2a{sub p},c≈2√3a{sub p},Z=6) with octahedral tilting scheme a{sup −}a{sup −}a{sup −} leading to a three identical out-of-phase tilt angle of (Mn/Cr)-O{sub 6} octahedron along three perovskite main directions: x, y, and z-axes. The orthorhombic space group Pbnm(No.62,a≈b≈√2a{sub p},c≈2a{sub p},Z=4) with octahedral tilting scheme a{sup −}a{sup −}c{sup +}, leads to an anti-phase tilts of the same magnitude about [100] and [010] directions of the elementary specimen cell and in-phase tilt of different magnitude about the [001] direction. At low temperature 10 K, Rietveld refinement of powder diffraction data revealed that the crystal structure of sample is distorted with a single orthorhombic symmetry (space group Pbnm). Magnetic measurements indicate that our investigated sample exhibits an overall anti-ferromagnetic behavior mainly attributed to the frustration induced by both competing AFM Cr{sup 3+}-O-Cr{sup 3+}, Mn{sup 4+}-O-Mn{sup 4+} networks, and the mixed one Mn{sup 4+}-O-Cr{sup 3+}exchange magnetic interactions. The temperature dependence of the resistivity measured under zero field shows a semi-conducting behavior in the whole temperature range, which probably could be described by the adiabatic small polaron hoping model with relatively high polaron activation energy.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Role of Mass Spectrometry in Structural Studies of Flavin-Based Electron Bifurcating Enzymes

For decades, biologists and biochemists have taken advantage of atomic resolution structural models of proteins from X-ray crystallography, nuclear magnetic resonance spectroscopy, and more recently cryo-electron microscopy. However, not all proteins relent to structural analyses using these approaches, and as the depth of knowledge increases, additional data elucidating a mechanistic understanding of protein function is desired. Flavin-based electron bifurcating enzymes, which are responsible for producing high energy compounds through the simultaneous endergonic and exergonic reduction of two intercellular electron carriers (i.e., NAD + and ferredoxin) are one class of proteins that have challenged structural biologists and in which there is great interest to understand the mechanism behind electron gating. A limited number of X-ray crystallography projects have been successful; however, it is clear that to understand how these enzymes function, techniques that can reveal detailed in solution information about protein structure, dynamics, and interactions involved in the bifurcating reaction are needed. In this review, we cover a general set of mass spectrometry-based techniques that, combined with protein modeling, are capable of providing information on both protein structure and dynamics. Techniques discussed include surface labeling, covalent cross-linking, native mass spectrometry, and hydrogen/deuterium exchange. We cover how biophysical data can be used to validate computationally generated protein models and develop mechanistic explanations for regulation and performance of enzymes and protein complexes. Our focus will be on flavin-based electron bifurcating enzymes, but the broad applicability of the techniques will be showcased.

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

Low global warming potential (GWP) refrigerant supermarket refrigeration system modeling and its application

As an environmentally friendly low global warming potential (GWP) refrigerant, Carbon dioxide (CO 2 ) has continuously gained popularity and research attention as alternative refrigerant for supermarket refrigeration system. In this paper, to fulfill the increasing need of accurate Low-GWP supermarket refrigeration models for development of supervisory level control and optimization strategies, a high fidelity model is developed for CO 2 transcritical supermarket refrigeration system which includes compressor rack of low temperature (LT) compressors and medium temperature (MT) compressors, air-cooled gas cooler, evaporator, expansion valves and other auxiliary equipment. A resistance-capacity model structure is proposed to simulate the display cases. Semi-thermodynamic models are proposed to estimate reciprocating compressors volumetric efficiency and power consumption. Furthermore the zone modeling approach is used for evaporator simulation, and air-cooled gas cooler is modeled with distributed modeling method. The expansion valve simulation is based on orifice flow model. To calibrate these models, both manufacture performance data and experimental data are used. The experiments are conducted with a full instrumental CO 2 supermarket refrigeration system installed in Oak Ridge National Lab Flexible Research Platform (FRP). The simulation model can predict the system performance, including power consumption, cooling capacity, mass flow rate, temperature, and pressure, with high accuracy (within ±4%) compared to experimental data. In addition, this developed model has been used to create the system optimum high side pressure for high side expansion valve control, and to generate wide operating range simulation data for developing the batter-equivalent commercial refrigeration system model which can be used in grid interactive control development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Atomic-Level Structure of Mesoporous Hexagonal Boron Nitride Determined by High-Resolution Solid-State Multinuclear Magnetic Resonance Spectroscopy and Density Functional Theory Calculations

Mesoporous hexagonal boron nitride (p-BN) has received significant attention over the last decade as a promising candidate for water cleaning/pollutant removal and hydrogen storage applications. In this work, high-resolution solid-state NMR spectroscopy and plane-wave density-functional theory (DFT) calculations are used to obtain an atomic-level description of p-BN. 1 H– 15 N or 1 H– 14 N heteronuclear (HETCOR) correlation experiments recorded with either conventional NMR at room temperature or dynamic nuclear polarization surface-enhanced spectroscopy (DNP-SENS) at ca. 100 K reveal NB 2 H, NBH 2 , NBH 3 + species residing on the edges of BN sheets. Ultra-high field 35.2 T 11 B NMR spectroscopy was used to resolve 11 B NMR signals from BN 3 , BN 2 O x (OH) 1–x (x = 0–1), BNO x (OH) 2–x (x = 0–2), BO x (OH) 3–x (x = 0–3), and BO x (OH) 4–x – (x = 0–4). Importantly, 2D 11 B dipolar double-quantum–single-quantum homonuclear correlation spectra reveal that many pore/defect sites are composed of boron oxide/hydroxide clusters connected to the BN framework through BN 2 O units. 1D and 2D 11 B{ 15 N} HETCOR NMR experiments, in addition to plane-wave DFT calculations of nine different structural models, further confirm the assignment of all NMR signals. The detailed structure determination of the pore and edge/defect sites within p-BN should further enable the rational design and development of next-generation p-BN-based materials. In addition, the techniques outlined here should be applicable to determine structure within other porous and/or boron-based materials.

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

BaCu 4/3 Si 2/3 P 2 and BaCu 2–( x + y ) Zn x Si y P 2 : Expanding the Semiconducting Landscape in the ThCr 2 Si 2 -Type Family

ThCr 2 Si 2 -type layered materials are a large family of compounds with applications ranging from thermoelectricity to magnetism, with the vast majority of the members exhibiting metallic behavior. Here, in this study, we synthesized a new group of materials with Cu-Si and Cu-Zn-Si square nets with the general formula BaCu 1.33 Si 0.67 P 2 and BaCu 2–(x+y) Zn x Si y P 2 (0 ≤ x ≤ 0.9; 0.3 ≤ y ≤ 0.7). Several synthesized compounds are charge-balanced semiconductors, which are rare in the ThCr 2 Si 2 family. All the reported compounds crystallize in the ThCr 2 Si 2 -type tetragonal I4/mmm space group, with Cu/Zn/Si jointly occupying the same 4d crystallographic site. In the Zn-free composition, BaCu 1.33 Si 0.67 P 2 , Ba, and P each occupy a single crystallographic site. The introduction of Zn results in the expansion of the unit cell and splitting the Ba atomic sites along the [001] direction. Such structural displacement of the Ba atoms was confirmed by the heat capacity measurements. Band structure and density-of-states calculations on ordered hypothetical structural models reveal either a small bandgap (∼0.2 eV) or semimetallic band structures. The compounds reported here exhibit high Seebeck coefficients and ultralow thermal conductivity, making them promising candidates for the development of thermoelectric materials.

crystal structure↗