Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “phase diagram”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,081 records · Page 60

Understanding the Reactions Between Fe and Se Binary Diffusion Couples

Spurred by recent discoveries of high-temperature superconductivity in Fe-Se based materials, the magnetic, electronic, and catalytic properties of iron-chalcogenides have drawn significant attention. Furthermore, much remains to be understood about the sequence of phase formation in these systems. In this work, we shed light on this issue by preparing a series of binary Fe-Se ultrathin diffusion couples via designed thin film precursors and investigating their structural evolution as a function of composition and annealing temperature. Two previously unreported Fe-Se phases crystallized during the deposition process on a nominally room-temperature Si substrate in the 27-33% and 37-47% Fe (atomic percent) composition regimes. Both phases completely decompose after annealing to 200°C in a nitrogen glovebox. At higher temperatures, the sequence of phase formation is governed by Se loss in the annealing process, consistent with what would be expected from the phase diagram. Films rich in Fe (53-59% Fe) crystalized during deposition as β-FeSe (P4/nmm) with preferred c-axis orientation to the amorphous SiO 2 substrate surface, providing a means to non-epitaxial self-assembly of crystallographically aligned, iron-rich β-FeSe for future research. Our findings suggest the crystallization of binary Fe-Se compounds at room temperature via near diffusionless transformations should be a significant consideration in future attempts to prepare metastable ternary and higher order compounds containing Fe and Se.

36 MATERIALS SCIENCE↗

Weak-Bonding Elements Lead to High Thermoelectric Performance in BaSnS 3 and SrSnS 3 : A First-Principles Study

SnS2, an earth-abundant and ecofriendly material, is limited as a thermoelectric material because of the high lattice thermal conductivity κ L and low carrier mobility μ. By introducing weak-bonding elements Ba or Sr into the SnS 2 framework, we discovered two SnS 2 -based materials BaSnS3 and SrSnS3 with the calculated low κL values of 0.15 and 0.17 W m -1 K -1 , respectively, along the a-axis. The low group velocity and high lattice anharmonicity originating from the weakened and distorted Sn–S bonding network are found in both systems. Moreover, the vibrations of Ba and Sr induce low-lying optical phonons, which strongly couple with the acoustic phonons and strengthen the phonon scattering rates. Compared to SnS 2 , both compounds present lower single-band effective masses, smaller deformation potential constants, and better band convergence, which enhance μ with an insignificantly reduced effective mass. By solving the linearized Boltzmann transport equation with a nonempirical carrier lifetime, we predict excellent ZT values of 2.89 and 2.77 along the a-axis at 900 K in BaSnS 3 and SrSnS 3 , respectively. Further phase diagram calculations of Ba 1–x Sr x SnS 3 solid solutions propose a new compound, Ba 0.5 Sr 0.5 SnS 3 , with an even higher ZT of 3.0. Our work analyzes explicitly how weak-bonding elements enhance μ and suppress κL simultaneously in SnS 2 -analogous systems with a series of compounds nominated as potential high-performance thermoelectric materials.

36 MATERIALS SCIENCE↗

Tuning the Morphology and Electronic Properties of Single-Crystal LiNi 0.5 Mn 1.5 O 4-δ : Exploring the Influence of LiCl–KCl Molten Salt Flux Composition and Synthesis Temperature

Single-crystal materials have played a unique role in the development of high-performance cathode materials for Li batteries due to their favorable chemomechanical stability. The molten salt synthesis method has become one of the most prominent techniques used to synthesize single-crystal layered and spinel materials. In this work, the molten salt synthesis method is used as a technique to tune both the morphology and Mn 3+ content of high-voltage LiNi 0.5 Mn 1.5 O 4 (LNMO) cathodes. The resulting materials are thoroughly characterized by a suite of analytical techniques, including synchrotron X-ray core-level spectroscopy, which are sensitive to the material properties on multiple length scales. Furthermore, the multidimensional characterization allows us to build a materials library according to the molten salt phase diagram as well as to establish the relationship among synthesis, material properties, and battery performance. The results of this work show that the Mn 3+ content is primarily dependent on the synthesis temperature and increases as the temperature is increased. Additionally, the particle morphology is mostly dependent on the composition of the molten salt flux, which can be tailored to obtain well-defined octahedrons enclosed by (111) facets, plates with predominant ($11\tilde{2}$) facets, irregularly shaped particles, or mixtures of these. The electrochemical measurements indicate that the Mn 3+ content has a larger contribution to the battery performance of LNMO than do morphological characteristics and that a significant amount of Mn 3+ could become detrimental to the battery performance. However, with similar Mn 3+ contents, morphology still plays a role in influencing the battery cycle life and rate performance. The insights of molten salt synthesis parameters on the formation of LNMO, with deconvolution of the roles of Mn 3+ and morphology, are crucial to continuing studies in the rational design of LNMO cathode materials for high-energy Li batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer

We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole–dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang–Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.

36 MATERIALS SCIENCE↗

Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. Here we show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First-Principles Insights into the Thermocatalytic Cracking of Ammonia-Hydrogen Blends on Fe(110): 1. Thermodynamics

Ammonia (NH 3 ) is being considered as a practical means to transport hydrogen (H 2 ) because of its higher volumetric energy density for the same temperature and pressure. Thermodynamics suggest high temperature is needed to decompose NH 3 to nitrogen (N 2 ) and H 2 . Furthermore, overcoming decomposition kinetic barriers requires a catalyst. Via density functional theory, we study this reaction on a model catalyst: the close-packed (110) facet of α-Fe. Specifically, we predict detailed in-operando temperature- and pressure-dependent surface phase diagrams on this benchmark catalyst that offer insights for the design of optimal NH 3 decomposition catalysts. Here, we explore the equilibrium composition(s) of the Fe(110) surface when exposed to NH 3 –H 2 mixtures. Further, we predict that both N and NH partially cover the Fe(110) surface at 300–400 °C (far above the NH 3 decomposition-formation coexistence temperature at standard partial pressures of 1 bar: ~ 180 °C) and 2–4 bar of total reactor pressure. At the equilibrium N/NH coverage, these species inhibit coadsorption of H, indicating that direct H 2 production may occur. However, from thermodynamics alone, removal of N/NH as N 2 (g) is extremely unfavorable even at these elevated temperatures–effectively deactivating the surface toward further NH 3 decomposition. Thus, catalysts that remain active toward N–H bond breaking but with weakened N binding relative to Fe are needed to enable high-turnover catalytic NH 3 decomposition to release H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determining Catalytically Relevant Surfaces through Coverage-Dependent Lattice Gas Models: Carbon Adsorption on Fe(100)

Here, we have quantified the C–C lateral interactions on Fe(100) using a density functional theory (DFT)-parameterized lattice gas cluster expansion (LG CE) model trained using 265 unique configurations spanning a C coverage from 0 to 1 monolayer (ML). Our LG CE model shows high predictive accuracy with a leave-multiple-out cross-validation score of 10.2 and 16.6 meV/site for systems with and without the top two layers of Fe atoms fixed, respectively. Electronic ground-state structures identified from the lattice gas model (including the structures at 0 and 1 monolayers) were further used to generate ab initio phase diagrams under a range of temperatures and pressures. At low temperatures (<400 K), we found that the 1.0 monolayer structure is dominant, whereas at higher temperatures (>500 K), the 0.88 ML structure is most likely to form on the Fe surface. Interestingly, our model identified a c (2 × 2) ordered structure at 1/2 ML, which correlates well with previous DFT studies for carbon adsorption on iron surfaces and matches with the experimentally observed low-energy electron diffraction structure. Overall, the DFT-parameterized energies for the C/Fe system including effects of coverage and configurational space can further help in developing multiscale models for various heterogeneous reactions involving C–C and C–Fe interactions.

08 HYDROGEN↗

Ab Initio Molecular Dynamics Spectra for Characterization of Hydrated Al 2 O 3 Supported MoO x

The structure of supported MoO x /Al 2 O 3 catalysts is investigated using ab initio molecular dynamics (AIMD) and density-functional theory (DFT). Phase diagrams were computed to understand the hydroxylation coverage as a function of the temperature, H 2 O partial pressure, and MoO x loading. We relate the shifts in experimental Raman vibrational frequencies under hydrated conditions to hydrogen bonding interactions and the MoO x anchoring location. We showcase that the use of AIMD as a benchmark for DFT can provide insight into how, under certain hydrated conditions, DFT excels as an inexpensive method for computing vibrational frequencies, while, under dehydrated conditions, it is susceptible to the largest errors. Additionally, to facilitate the analysis of the hydroxyl region of experimental infrared spectra, we compute the power spectra of individual hydroxyls and see a strong relationship between OH stretching frequencies and the surrounding coordination environment, which are also impacted by anchored MoO x . Here, we compare computational and experimental IR and Raman spectra of catalysts synthesized herein under the same conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coverage-Dependent Adsorption of Hydrogen on Fe(100): Determining Catalytically Relevant Surface Structures via Lattice Gas Models

Hydrogen adatoms are a critical surface species for several reactions catalyzed by Fe surfaces such as Fischer–Tropsch synthesis, ammonia synthesis, and the hydrodeoxygenation of biomass-derived oxygenates. Parameterizing the energetics for H/Fe in terms of both coverage and configuration space can significantly aid in the development of multiscale models as well as provide atomic level insight into the dominant surface structures present under realistic reaction conditions. Here, we construct a lattice gas model for H/Fe(100), where the lateral interactions are determined from first-principles using density functional theory. Using 950 symmetrically unique H/Fe(100) configurations, we generate a cluster expansion with a predictive accuracy in terms of surface energy of 3.8 meV/site over a coverage range from 0 to 3 monolayers. Ten electronic ground state structures are identified from this thorough scan (including the structures at 0 and 3 monolayers), which were subsequently used to generate ab initio phase diagrams under a range of temperatures and pressures. Under reaction conditions typical of Fischer–Tropsch synthesis, ammonia synthesis, and biomass oxygenate hydrodeoxygenation, we find that the 1.0 monolayer structure is dominant. Furthermore, examination of the total H–H lateral interactions for the H/Fe(100) electronic ground state structures shows that H/Fe(100) can be accurately modeled via a mean-field ideal lattice gas model for coverages less than 1.0 monolayers. Altogether, this work enables the incorporation of H–H lateral interactions on Fe(100) into multiscale models, via either mean-field or site-dependent techniques, and provides atomic insight into the catalytically relevant H/Fe(100) structures for a range of heterogeneous reactions.

09 BIOMASS FUELS↗

Acetonitrile Transition Metal Interfaces from First Principles

Acetonitrile is among the most commonly used nonaqueous solvents in catalysis and electrochemistry. Here, we study its interfaces with multiple facets of the metals Ag, Cu, Pt, and Rh using density functional theory calculations; the structures reported shed new light on experimental observations and underscore the importance of solvent–solvent interactions at high coverage. We investigate the relationship of potential of zero charge (PZC) to metal work function, reporting results in agreement with experimental measurements. We develop a model to explain the effects of solvent chemisorption and orientation on the PZC to within a mean absolute deviation of 0.08–0.12 V for all facets studied. Our electrostatic field dependent phase diagram agrees with spectroscopic observations and sheds new light on electrostatic field effects. This work provides new insight into experimental observations on acetonitrile metal interfaces and provides guidance for future studies of acetonitrile and other nonaqueous solvent interfaces with transition metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Anomalies and Local Structure of Liquid Water from Boiling to the Supercooled Regime as Predicted by the Many-Body MB-pol Model

For the past 50 years, researchers have sought molecular models that can accurately reproduce water’s microscopic structure and thermophysical properties across broad ranges of its complex phase diagram. Herein, molecular dynamics simulations with the many-body MB-pol model are performed to monitor the thermodynamic response functions and local structure of liquid water from the boiling point down to deeply supercooled temperatures at ambient pressure. The isothermal compressibility and isobaric heat capacity show maxima near 223 K, in excellent agreement with recent experiments, and the liquid density exhibits a minimum at ~208 K. A local tetrahedral arrangement, where each water molecule accepts and donates two hydrogen bonds, is found to be the most probable hydrogen-bonding topology at all temperatures. Further, this work suggests that MB-pol may provide predictive capability for studies of liquid water’s physical properties across broad ranges of thermodynamic states, including the so-called water’s “no man’s land” which is difficult to probe experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Topological Frustration as a New Parameter to Tune Morphology Revealed through Exploring the Continuum between A-B-C 3-Arm Star and Linear Triblock Polymers

Block polymers assemble into a variety of phase-separated morphologies based on volume fraction (φ) and interactions (χ) of the respective blocks. The arrangement of three different polymer blocks could either be a 3-arm star, with each block having one terminus attached to a common junction point or a linear A-B-C architecture. A versatile strategy is reported to synthesize a series of well-defined graft polymers that lie along the unexplored continuum between a 3-arm star and an A-B-C linear triblock polymer architecture. Using the technique of single-molecule insertion, precise control over the position of graft arm C along the B chain was achieved. A series of discrete graft polymers (PMMA-b-PS-g-PEO) with fixed φ and prescribed ω values that lie on the continuum between a 3-arm star (ω = 0) and linear triblock polymer (ω = 1) were synthesized. Morphological studies using small-angle X-ray scattering and conventional and energy-filtered transmission electron microscopy reveal the transition between lamellae, perforated lamellae, and cylindrical morphologies with systematic variation in the ω values, a trend attributed to the topological frustration and the associated χ values between the three blocks. Molecular dynamic simulations of coarse-grained models were found to predict phase diagrams that are consistent with the experimentally observed morphologies. Furthermore, our results suggest that changes in ω lead to topological frustration which is an important additional new design parameter that can be used to tune the morphology of multiblock polymers in addition to φ and χ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correction to “Frank–Kasper Phases of Diblock Copolymer Melts Studied with the DPD Model: SCF Results”

In a recent study, (1) we performed the self-consistent field (SCF) calculations of a dissipative particle dynamics (DPD) model of conformationally asymmetric diblock copolymer A-B melts to study the stability of various Frank–Kasper (FK) phases formed by such A-B melts. While all the equations in ref (1) are correct, we did not calculate the dimensionless (mean-field) Helmholtz free energies per chain βf c = βu c,χ + βu c,κ – s c /k B and the dimensionless stresses dβf c /dθ of ordered phases accurately. For example, the dimensionless (nonbonded) internal energy per chain due to the system compressibility βu c,κ = (N/2κ)∑ q βû 0 (|q|)(ϕ̂ A (q) + ϕ̂ B (q) – δ q,0 )(ϕ̂ A (−q) + ϕ̂ B (−q) – δ– q,0 ) should be calculated in the reciprocal space as given (note that βû 0 (|q|) is obtained analytically, and that since ϕ A (r) is real 𝜙̂ A (−𝐪)= $\overline{𝜙̂ A}$(𝐪), i.e., the complex conjugate of ϕ̂ A (q)); this corresponds to numerically evaluating βu c,κ = (N/2κ)∫dr(ϕ A (r) + ϕ B (r) – 1)ψ(r) with ψ(r) ≡ (∫dr′βu 0 (|r–r′|)(ϕ A (r′) + ϕ B (r′) – 1)/V in the real space via the (composite) trapezoidal rule. While the trapezoidal rule is less accurate than the Romberg integration (2) in general, the opposite occurs when the integration domain is periodic; this was pointed out by Matsen in ref (3) and explained in detail in refs (4and5). With our ignorance of this exceptional convergence property of the trapezoidal rule for periodic functions, we calculated all convolutions having the form of ψ(r) in the reciprocal space via the fast Fourier transforms (6) but those having the form of βu c,κ in the real space via Romberg integration; the latter leads to inaccurate results and unfortunately incorrect phase diagrams reported in ref (1), which are corrected here.

He, Juntong↗

Data-Efficient Methods for Determining Flory–Huggins χ Parameters in Multicomponent Polymer Formulations

Polymer formulations are essential in diverse applications including personal care products, coatings, paints, adhesives, and plastic materials. Designing these formulations requires navigating large, complex design spaces, where phase and self-assembly behavior critically impact performance. The Flory–Huggins χ parameter, which quantifies segmental miscibility, is widely used to parametrize the excess free energy of mixing in formulation models. In this work, we introduce two data-efficient, top-down methods for estimating χ parameters using the Random Phase Approximation (RPA): (i) Boundary Nonlinear Regression (Boundary-NLR), which fits theoretical spinodal boundaries to experimental phase boundaries, and (ii) Surrogate Model Inverse Parameter Estimation (SMIPE), which uses a Gaussian Process Classifier to fit sparse phase maps via a surrogate model. Both methods allow rapid parametrization of polymer field-theoretic models without the need for additional experiments. We evaluate these approaches on data sets involving polymer–solvent–nonsolvent ternary mixtures and block copolymer–solvent systems, demonstrating their robustness to experimental noise and their relevance for real-world formulation design.

copolymers↗

Hybrid Symmetry Epitaxy of the Superconducting Fe(Te,Se) Film on a Topological Insulator

It is challenging to grow an epitaxial 4-fold compound superconductor (SC) on a 6-fold topological insulator (TI) platform due to the stringent lattice-matching requirement. Here, we demonstrate that Fe(Te,Se) can grow epitaxially on a TI (Bi 2 Te 3 ) layer due to accidental, uniaxial lattice match, which is dubbed as “hybrid symmetry epitaxy”. This new growth mode is critical to stabilizing robust superconductivity with TC as high as 13 K. Furthermore, the superconductivity in this FeTe 1–x Se x /Bi 2 Te 3 system survives in the Te-rich phase with Se content as low as x = 0.03 but vanishes at Se content above x = 0.56, exhibiting a phase diagram that is quite different from that of the conventional Fe(Te,Se) systems. This unique heterostructure platform that can be formed in both TI-on-SC and SC-on-TI sequences opens a route to unprecedented topological heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

LASSO for CALPHAD Model Selection Enables Data-Efficient Thermodynamic Modeling: An Application in Thermochemical Hydrogen Production Materials

Phenomenological CALPHAD (CALculation of PHAse Diagrams) models, widely used for multicomponent materials, often contain a considerable number of parameters and require fitting using data from a relatively small number of experimental measurements or theoretical calculations. Sometimes these parameters are introduced for the purpose of improving model fits but without clear physical justification, which leads to overparametrized models with poor generalization performance. Automated approaches for optimal model selection based on the available data therefore become critical. Here, in this work, a least absolute shrinkage and selection operator (LASSO)-based approach is developed for model selection by leveraging the linearity of the CALPHAD model with respect to its parameters to convert the model selection and fitting to a LASSO minimization problem. We demonstrate its utility for thermodynamic modeling of thermochemical hydrogen (TCH) production materials using lanthanum strontium manganite (LSM) as an example. Various TCH-relevant properties, including oxygen stoichiometry as a function of oxygen partial pressure, enthalpy of reduction, and entropy of reduction, are successfully predicted with reasonable accuracy using a minimal set of model parameters. Importantly, the model selection and fitting involve minimal human decision; it can therefore be applied to high-throughput DFT defect calculations and yield efficient workflows for TCH material modeling and optimization.

CALPHAD↗

Structural Rearrangements of Subnanometer Cu Oxide Clusters Govern Catalytic Oxidation

Sub-nanometer metal oxide clusters are very important materials that are widely used, for example, in catalysis or electronic devices such as sensors. Hence, it is critical to understand the atomic structures and properties of sub-nanometer metal oxide clusters under a reactive gas environment, such as O 2 . We consider here experimentally accessible precise-size Cu clusters (Cu 4 ) supported on partially hydroxylated amorphous alumina and show that such clusters can access, in catalytic conditions at high temperature under a pressure of O 2 , a large ensemble of oxidized structures, representing a large variety of oxygen content, of geometries in link with the support, and of catalytic activities for oxidation reactions, as seen from their reducibilities. A grand canonical basin hopping method based on first-principles energy reveals an ensemble of 24 configurations for the Cu 4 O x cluster of low free energy, less than 0.8 eV above the global minimum. The low free energy ensemble consists of clusters of different stoichiometries, which are mainly Cu 4 O 3 and Cu 4 O 4 in the temperature range of 200–400 °C and under a pressure of 0.5 bar of O 2 . The presence of several competitive isomers at each composition implies that cluster fluxionality impacts the phase diagram, which should be ensemble-averaged. In terms of catalytic oxidation activity, Cu 4 O 3 isomers present highly variable O abstraction energy: the most stable isomers are inactive for alkane oxidative dehydrogenation, but isomerization to metastable isomers, that proceed with low barrier, enable to create active configurations with low O abstraction energy. O atoms with the lowest anionic character, and thus of more electrophilic nature, present the best oxidation capability. In contrast, all Cu 4 O 4 isomers show a low O abstraction energy and a high potential catalytic activity. Here, this manuscript demonstrates the unique structural and electronic properties of sub-nano Cu oxide clusters and illustrates the critical roles of configuration ensembles and rearrangement to highly reactive metastable cluster isomers in nanocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗