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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Developing Machine Learning Interatomic Potential for Fe-Cr-Ni Alloys

Accurate prediction of creep and fatigue behavior of stainless steel at elevated temperatures in hydrogen environment requires fundamental understanding of alloy-hydrogen interaction at cross-scale including bulk lattice and key defects such as vacancies, grain boundaries, surfaces, stacking faults, dislocations, and precipitates. This project aims to predict creep behavior of 347H stainless steel with H using machine learning interatomic potentials based on first-principles density functional theory simulations. The Moment Tensor Potentials platform is adopted for this work since it demonstrates a fine balance between model accuracy and computational efficiency. The potential is well trained based on large amount of high-fidelity density functional theory calculations. The validation is carried out by comparing various important properties including short range order, coefficient of thermal expansion, elastic properties, stacking fault energy, grain boundary energy, and surface energy. This work lays the foundation for reliable atomistic simulation of high temperature hydrogen attack of stainless steel.

density functional theory (DFT)↗
DOE OSTI2020

Atomic Layer Deposition of Pt on the Surface Deactivated by Fluorocarbon Implantation: Investigation of the Growth Mechanism

Selective atomic layer deposition (ALD) using surface-controlled reactivity is attracting a great deal of attention as a simple bottom-up patterning process that can provide both continued dimensional scaling and accurate pattern placement for next-generation nanoelectronics. Previously, we reported topographically selective deposition through Pt ALD using a MeCpPtMe 3 precursor and an O 2 counter reactant on fluorocarbon (CF x )-modified surfaces; however, gradual loss of selectivity in the CF x -modified regions was observed during the Pt ALD process. This work develops a fundamental understanding of the microscopic growth mechanisms of Pt ALD on the CF x -modified surface using a combination of experimental analyses and theoretical methods. The Pt growth characteristics on the CF x surface are investigated within a temperature window from 225 to 350 °C, and the results show a sharp sensitivity to growth temperature, with significant Pt growth occurring at temperatures above 300 °C. Through density functional theory (DFT) calculations, the reaction energies for adsorption of oxygen and the MeCpPtMe 3 precursor as well as formation of reaction products of CF x degradation are determined. Based on experimental results in conjunction with the DFT calculations, we show that while lower temperature Pt ALD (<300 °C) on CF x -modified surfaces can be significantly retarded because of a lack of MeCpPtMe 3 chemisorption, the surface reaction pathways for Pt ALD on CF x -modified surfaces at temperatures above 300 °C can proceed through oxygen adsorption and CF 4 desorption followed by Pt nucleation in CF x -degraded regions.

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

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling Framework to Predict Melting Dynamics at Microstructural Defects in TNT-HMX High Explosive Composites

Many high explosive (HE) formulations are composite materials whose microstructure is understood to impact functional characteristics. Interfaces are known to mediate the formation of hot spots that control their safety and initiation. Here, to study such processes at molecular scales, we developed all-atom force fields (FFs) for Octol, a prototypical HE formulation comprised of TNT (2,4,6-trinitrotoluene) and HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine). We extended a FF for TNT and recasted it in a form that can be readily combined with a well-established FF for HMX. The resulting FF was extensively validated against experimental results and density functional theory calculations. We applied the new combined TNT-HMX FF to predict and rank surface and interface energies, which indicate that there is an energetic driver for coarsening of microstructural grains in TNT-HMX composites. Finally, we assess the impact of several microstructural environments on the dynamic melting of TNT crystal under ultrafast thermal loading. We find that both free surfaces and planar material interfaces are effective nucleation points for TNT melting. However, MD simulations show that TNT crystal is prone to superheating by at least 50 K on subnanosecond time scales and that the degree of superheating is inversely correlated with surface and interface energy. The modeling framework presented here will enable future studies on hot spot formation processes in accident scenarios that are governed by strong coupling between microstructural interfaces, material mechanics, momentum and energy transport, phase transitions, and chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Achieving industrial ammonia synthesis rates at near-ambient conditions through modified scaling relations on a confined dual site

The production of ammonia through the Haber–Bosch process is regarded as one of the most important inventions of the 20th century. Despite significant efforts in optimizing the process, it still consumes 1 to 2% of the worldwide annual energy for the high working temperatures and pressures. The design of a catalyst with a high activity at milder conditions represents another challenge for this reaction. Herein, we combine density functional theory and microkinetic modeling to illustrate a strategy to facilitate low-temperature and -pressure ammonia synthesis through modified energy-scaling relationships using a confined dual site. Our results suggest that an ammonia synthesis rate two to three orders of magnitude higher than the commercial Ru catalyst can be achieved under the same reaction conditions with the introduction of confinement. Such strategies will open pathways for the development of catalysts for the Haber–Bosch process that can operate at milder conditions and present more economically viable alternatives to current industrial solutions.

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

ELSI — An open infrastructure for electronic structure solvers

Routine applications of electronic structure theory to molecules and periodic systems need to compute the electron density from given Hamiltonian and, in case of non-orthogonal basis sets, overlap matrices. System sizes can range from few to thousands or, in some examples, millions of atoms. Different discretization schemes (basis sets) and different system geometries (finite non-periodic vs. infinite periodic boundary conditions) yield matrices with different structures. The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. In this paper, we present recent improvements and developments inside ELSI, mainly covering (1) new solvers connected to the interface, (2) matrix layout and communication adapted for parallel calculations of periodic and/or spin-polarized systems, (3) routines for density matrix extrapolation in geometry optimization and molecular dynamics calculations, and (4) general utilities such as parallel matrix I/O and JSON output. The ELSI interface has been integrated into four electronic structure code projects (DFTB+, DGDFT, FHI-aims, SIESTA), allowing us to rigorously benchmark the performance of the solvers on an equal footing. Based on results of a systematic set of large-scale benchmarks performed with Kohn–Sham density-functional theory and density-functional tight-binding theory, we identify factors that strongly affect the efficiency of the solvers, and propose a decision layer that assists with the solver selection process. As a result, we describe a reverse communication interface encoding matrix-free iterative solver strategies that are amenable, e.g., for use with planewave basis sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Data-driven modeling and control of dynamical systems using Koopman and Perron-Frobenius operators

This dissertation studies the data-driven modeling and control problem of nonlinear systems by exploiting the linear operator theoretic framework involving Koopman and Perro-Frobenius operator. A systematic linear-operator based controller design procedure has been established, which can be used to solve a variety of nonlinear control problems, including feedback stabilization using control Lyapunov functions, optimal quadratic regulation using Koopman eigenfunctions and convex optimization formulation of optimal control problem using P-F and Koopman operator approximation. As the core of data-driven modeling, we first propose a new algorithm for the finite-dimensional approximation of the linear transfer Koopman and Perron-Frobenius operator from time-series data. We argue that the existing approach for the finite-dimensional approximation of these transfer operators such as Dynamic Mode Decomposition (DMD) and Extended Dynamic Mode Decomposition (EDMD) do not capture two important properties of these operators, namely positivity and Markov property. The algorithm we propose preserves these two properties. We call the proposed algorithm as naturally structured DMD (NSDMD) since it retains the inherent properties of these operators. Naturally structured DMD algorithm leads to a better approximation of the steady-state dynamics of the system regarding computing Koopman and Perron- Frobenius operator eigenfunctions and eigenvalues. However, preserving positivity property is critical for capturing the real transient dynamics of the system. This positivity property of the transfer operators and it's finite-dimensional approximation play an important role for controller and estimator design of nonlinear systems. To solve the feedback stabilization problem for nonlinear control systems, we tried to take advantage of the Koopman operator framework. The Koopman operator approach provides a linear representation for a nonlinear dynamical system and a bilinear representation for a nonlinear control system. The problem of feedback stabilization of a nonlinear control system is then transformed to the stabilization of a bilinear control system. We propose a control Lyapunov function (CLF)-based approach for the design of stabilizing feedback controllers for the bilinear system. The search for finding a CLF for the bilinear control system is formulated as a convex optimization problem. This leads to a schematic procedure for designing CLF-based stabilizing feedback controllers for the bilinear system and hence the original nonlinear system. Another advantage of the proposed controller design approach outlined in this dissertation is that it does not require explicit knowledge of system dynamics. In particular, the bilinear representation of a nonlinear control system in the Koopman eigenfunction space can be obtained from time-series data. Next, we study the optimal quadratic regulation problem for nonlinear systems. The linear operator theoretic framework involving the Koopman operator is used to lift the dynamics of nonlinear control system to an infinite-dimensional bilinear system. The optimal quadratic regulation problem for nonlinear system is formulated in terms of the finite-dimensional approximation of the bilinear system. A convex optimization-based approach is proposed for solving the quadratic regulator problem for bilinear system. We applied a variety of examples and compared the simulation results between our framework and conventional LQR control using linearized model. For more general optimal control problems, we provide a density-function based convex formulation for the optimal control problem of the nonlinear system. The convex formulation relies on the duality result in the stability theory of a dynamical system involving density function and Perron-Frobenius operator. The optimal control problem is formulated as an infinite-dimensional convex optimization program. The finite-dimensional approximation of the optimization problem relies on the recent advances made in the data-driven computation of the Koopman operator, which is dual to the Perron-Frobenius operator. Simulation results are presented to demonstrate the application of the developed framework.

Huang, Bowen↗
DOE OSTI2026

Phase diagram of magnetic shape memory alloy Ni 50 Mn $50–x$ In $x$ , 0 < $x$ , 25 from first principles, via spin cluster expansion and phonon vibrational entropies

The metamagnetic shape memory Heusler alloy Ni 50 Mn $50–x$ In $x$ exhibits a rich phase diagram featuring competing magnetic states, coupled magnetic–structural phase transitions, and strong compositional sensitivity. Existing first-principles approaches struggletocapturetheintertwinedchemical, magnetic, andvibrationaleffectsinthesealloys, necessitating a more integrated modeling framework. We develop a spin cluster expansion (spin-CE) framework augmented by a quasi-harmonic phonon model to capture both configurational (chemical and magnetic) and vibrational contributions to the free energy of Ni 50 Mn $50–x$ In $x$ over the full compositional range 0 ≤ x ≤25. The spin-CE includes both chemical clusters and composition-dependent Ising spin interactions, with parameters fit to a first-principles density functional theory (DFT) dataset. Using this approach, we predict the complete magnetostructural phase diagram and transformation temperatures of Ni 50 Mn $50–x$ In $x$ across the composition space. We find that vibrational entropy alone is insufficient to reproduce the martensitic transformation in the magnetic shape memory alloy regime, highlighting the essential role of magnetism. Incorporating both magnetic and vibrational contributions allows us to reproduce all experimentally known phases, including the disappearance of the stable martensite phase at a critical In concentration and the Curie temperature of the austenite phase. The method also captures the transition with increasing In in martensite from antiferromagnetic to ferromagnetic order and predicts re-entrant ferromagnetism, though the latter occurs at higher In content than reported experimentally. We discuss possible sources of this discrepancy and highlight the broader applicability of the method to other magnetostructurally complex materials, where it may offer mechanistic insight and predictive design capabilities.

Cluster expansion↗
DOE OSTI2022

Increasing the composition range of a novel τ 11 -Al 4 Fe 1.7 Si alloy with additions of Mn

Automotive applications need low-cost, lightweight, high-temperature alloys to increase vehicle efficiency. The Al–Fe–Si system provides an opportunity to develop such a material, as it consists of three low-cost elements that are all abundant in nature. Specifically, the τ 11 -Al 4 Fe 1.7 Si ternary intermetallic phase is a high-temperature, lightweight phase with high strength and good corrosion resistance. However, this phase exhibits a narrow compositional range of stability, resulting in undesirable microstructures forming during solidification and processing, limiting its use in potential applications. Density functional theory (DFT) calculations and a thermodynamically-driven experimental approach utilizing diffusion couples were employed to study the effect of Mn on the stability and composition range of τ 11 -Al 4 Fe 1.7 Si. The DFT calculations showed a decrease in the energy of the structure when alloying with Mn. Experimental results confirmed the predictions from the DFT calculations, indicating that alloying with Mn increases the compositional range, and thus the processability of this phase. New phase diagrams and equilibria are proposed by exploring and determining phase boundaries for the τ 11 -Al 4 Fe 1.7 Si phase with Mn.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomistic and cluster dynamics modeling of fission gas (Xe) diffusivity in TRISO fuel kernels

TRISO fuel particles are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The UCO fuel kernel consists of a uranium dioxide (UO) and uranium carbide mixture. The addition of UC helps suppress the formation of carbon monoxide gas, which led to failures during initial TRISO development. The addition of uranium carbide alters the chemistry of the UO kernel, which is known to influence performance parameters such as fission gas diffusivity, although the impact has not been quantified and no models exist that take the change in chemistry into account. Therefore, better understanding and more accurate models of the impact of chemistry on fuel performance are of high priority. In this paper, a first-principles density functional theory (DFT) and empirical potential based multi-scale study has been carried out to model the diffusivity of fission gas xenon (Xe) in UCO TRISO fuel kernels. The focus is on the UO component in the UCO fuel kernels, as that represents the largest volume fraction of the fuel kernels. The study relies on DFT and empirical potential calculations to determine Xe and point defect properties, which are then used in thermodynamic and kinetic models to predict diffusion for intrinsic conditions. In addition, the information is utilized in cluster dynamics simulations using the Centipede code to estimate the impact of irradiation on defect transport. Additionally, the presence of UC or UC in the UCO fuel kernels is shown to have a substantial impact on the UO non-stoichiometry by inducing oxygen vacancies and driving UO sub-stoichiometric, which causes much slower Xe diffusion in UCO compared to light water reactor UO fuel. The application of this model in fuel performance simulations using the Bison code is also demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Stable bismuth-antimony alloy cathode with a conversion-dissolution/deposition mechanism for high-performance zinc batteries

Although a large number of intercalation cathode materials for aqueous Zn batteries have been reported, limited intercalation capacity precludes achieving a higher energy density. Here, for this work, we develop a high-performance aqueous Zn battery based on BiSb alloy (Bi 0.5 Sb 0.5 ) using a high-concentrated strong-basic polyelectrolyte. We demonstrate that a conversion-dissolution/deposition electrochemical mechanism (BiSb ↔ Bi + SbO 2 – ↔ Bi + SbO 3 – ↔ Bi 2 O 3 ) through in situ X-ray diffraction (XRD), Raman, and ex-situ X-ray photoelectron spectrometry (XPS) characterizations with the help of density functional theory calculations. The BiSb cathode delivers large capacity of 512 mAh g –1 at 0.3 Ag –1 and superior rate capability of 90 mAh g –1 even at 20 Ag –1 , and long-term cyclability with capacity retentions of 184 mAh g –1 after 600 cycles at 0.5 Ag –1 and 130 mAh g –1 after 1300 cycles at 1 Ag –1 . Remarkably, even at temperatures as low as –10 and –20 °C, capacities of 210 and 197 mAh g –1 are reserved at 1 Ag –1 , respectively. Moreover, the prepared pouch Zn//BiSb battery delivers a high energy density of 303 Wh kg –1 BiSb at 0.3 Ag –1 . When coupled with a high concentration polyelectrolyte, the Zn/BiSb battery exhibits an excellent performance over a wide temperature range (–40 to 40 °C). Our research reveals the metal cathode is promising for Zn batteries to achieve a high performance with the unique mechanism and alloys can be an effective approach to stabilize metal electrodes for cycling.

25 ENERGY STORAGE↗
DOE OSTI2025

Ligand-Driven Electrochemical Tuning of Co 6 Se 8 Chevrel Clusters

Molecular “Chevrel-type” clusters of the formula Co 6 Se 8 L 6 (L = neutral ligand) are a well-studied class of clusters due to their utility as molecular analogues to the Chevrel extended solid phase and their application as subunits in hierarchical materials. However, their solution and optical properties remain relatively underexplored. Aiming to develop the fundamental relationships between the molecular and electronic structures of these clusters and their electrochemical and photophysical properties, this work reports the preparation of a series of Co 6 Se 8 (P­(C 6 H 4 R) 3 ) 6 -type clusters with R = Cl (1), F (2), H (3), CH 3 (4), and OCH 3 (5) via a stepwise synthetic approach. Solution and solid-state experimental characterization and density functional theory calculations reveal that the Co 6 Se 8 cores of 1–5 maintain consistent electronic and structural properties despite the variation of the triarylphosphine ligand para-substituent Hammett parameters (σ p ). However, cyclic voltammetry measurements indicate that the electron transfer energetics of 1–5 are strongly influenced by ligand substitution, with the E 1/2 of a given redox event spanning ∼0.5 V depending on the triarylphosphine ligand’s σ p . In conclusion, these findings support the characterization of Co 6 Se 8 clusters as atomically precise nanoclusters with both the structural robustness and the electrochemical tunability needed to act as components in larger charge transfer assemblies.

Wheaton, Amelia M. [Argonne National Laboratory (A↗
DOE OSTI2023

Linearized Pair-Density Functional Theory for Vertical Excitation Energies

Multiconfiguration pair-density functional theory (MC-PDFT) is a computationally efficient method that computes the energies of electronic states in a state specific or state average framework via an on-top functional. However, MC-PDFT does not include state interaction among these states since the final energies do not come from the diagonalization of an effective model-space Hamiltonian. Recently, multistate extensions such as linearized PDFT (L-PDFT) have been developed to accurately model the potentials near conical intersections and avoided crossings. However, there has not been any systematic study evaluating their performance for predicting vertical excitations at the equilibrium geometry of a molecule, when the excited states are generally well separated. In this paper, we report the performance of L-PDFT on the extensive QUESTDB data set of vertical excitations using a database of automatically selected active spaces. We show that L-PDFT performs well on all these excitations and successfully reproduces the performance of MC-PDFT. These results further demonstrate the potential of L-PDFT, as its scaling is constant with the number of states included in the state-average manifold, whereas MC-PDFT scales linearly in this regard.

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

Axis dependent conduction polarity in the air-stable semiconductor, PdSe 2

Axis-dependent conduction polarity (ADCP) is a unique electronic phenomena in which the charge polarity of carrier conduction can differ from p-type to n-type depending on the direction of travel through the crystal. Most materials that exhibit ADCP are metals, and very few semiconducting materials exhibit this effect. Here, in this work, we establish that PdSe 2 , a ~0.5 eV band gap semiconductor that is air- and water-stable, exhibits ADCP, through the growth and characterization of the transport properties of crystals with extrinsic p- and n-type doping levels of Ir and Sb, respectively, in the 10 16 –10 18 cm –3 range. Electron doped PdSe 2 exhibits p-type conduction in the cross-plane direction and n-type conduction along the in-plane directions above an onset temperature of 100–200 K that varies with doping level. Lightly p-doped samples show p-type thermopower in all directions at low temperatures, but above ~360 K the in-plane thermopower turns negative. Density functional theory calculations indicate that the origin of ADCP arises from the complementary effective mass anisotropies in the valence and conduction bands in this material, which facilitate hole transport in the cross-plane direction, and electron transport along the in-plane directions. ADCP occurs at temperatures with sufficient thermal population of both carrier types to overcome the extrinsic doping levels to exploit the effective mass anisotropy. In total, the development of this stable semiconductor in which thermally or optically excited holes and electrons inherently migrate along different directions opens up numerous potential applications in a multitude of technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Full configuration interaction simulations of exchange-coupled donors in silicon using multi-valley effective mass theory

Abstract Donor spins in silicon have achieved record values of coherence times and single-qubit gate fidelities. The next stage of development involves demonstrating high-fidelity two-qubit logic gates, where the most natural coupling is the exchange interaction. To aid the efficient design of scalable donor-based quantum processors, we model the two-electron wave function using a full configuration interaction method within a multi-valley effective mass theory. We exploit the high computational efficiency of our code to investigate the exchange interaction, valley population, and electron densities for two phosphorus donors in a wide range of lattice positions, orientations, and as a function of applied electric fields. The outcomes are visualized with interactive images where donor positions can be swept while watching the valley and orbital components evolve accordingly. Our results provide a physically intuitive and quantitatively accurate understanding of the placement and tuning criteria necessary to achieve high-fidelity two-qubit gates with donors in silicon.

Joecker, Benjamin (ORCID:0000000302635440)↗
DOE OSTI2023

Spatially anisotropic 𝑆=1 square-lattice antiferromagnet with single-ion anisotropy realized in a Ni(II) pyrazine-𝑛,𝑛′-dioxide coordination polymer

The Ni(NCS) 2 (pyzdo) 2 coordination polymer is found to be an S = 1 spatially anisotropic square lattice with easy-axis single-ion anisotropy. This conclusion is based upon considering in concert the experimental probes x-ray diffraction, magnetic susceptibility, magnetic-field-dependent heat capacity, muon-spin relaxation, neutron diffraction, neutron spectroscopy, and pulsed-field magnetization. Long-range antiferromagnetic (AFM) order develops at T N = 18.5 K. Although the samples are polycrystalline, there is an observable spin-flop transition and saturation of the magnetization at ≈80 T. Linear spin-wave theory yields spatially anisotropic exchanges within an AFM square lattice, J x =0.235 meV, J y =2.014 meV, and an easy-axis single-ion anisotropy D=−1.622 meV (after renormalization). The anisotropy of the exchanges is supported by density functional theory.

2-dimensional systems↗
DOE OSTI2023

High-Temperature Thermodynamics of Uranium from Ab Initio Modeling

We present high-temperature thermodynamic properties for uranium in its γ phase (γ-U) from first-principles, relativistic, and anharmonic theory. The results are compared to CALPHAD modeling. The ab initio electronic structure is obtained from density-functional theory (DFT) that includes spin–orbit coupling and an added self-consistent orbital-polarization (OP) mechanism for more accurate treatment of magnetism. The first-principles method is coupled to a lattice dynamics scheme that is used to model anharmonic lattice vibrations, namely, Self-Consistent Ab Initio Lattice Dynamics (SCAILD). The methodology can be summarized in the acronym DFT + OP + SCAILD. Upon thermal expansion, γ-U develops non-negligible magnetic moments that are included for the first time in thermodynamic theory. The all-electron DFT approach is shown to model γ-U better than the commonly used pseudopotential method. In addition to CALPHAD, DFT + OP + SCAILD thermodynamic properties are compared with other ab initio and semiempirical modeling and experiments. Our first-principles approach produces Gibbs free energy that is essentially identical to CALPHAD. The DFT + OP + SCAILD heat capacity is close to CALPHAD and most experimental data and is predicted to have a significant thermal dependence due to the electronic contribution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Bimolecular Reaction Mechanism in the Amido Complex-Based Atomic Layer Deposition of HfO 2

The surface chemistry of the initial growth during the first or first few precursor cycles in atomic layer deposition is decisive for how the growth proceeds later on and thus for the quality of the thin films grown. Yet, although general schemes of the surface chemistry of atomic layer deposition have been developed for many processes and precursors, in many cases, knowledge of this surface chemistry remains far from complete. For the particular case of HfO 2 atomic layer deposition on a SiO 2 surface from an alkylamido-hafnium precursor and water, we address this lack by carrying out an operando atomic layer deposition experiment during the first cycle of atomic layer deposition. Ambient-pressure X-ray photoelectron spectroscopy and density functional theory together show that the decomposition of the metal precursor on the stoichiometric SiO 2 surface in the first half-cycle of atomic layer deposition proceeds via a bimolecular reaction mechanism. The reaction leads to the formation of Hf-bonded methyl methylene imine and free dimethylamine. In addition, ligand exchange takes place involving the surface hydroxyls adsorbed at defect sites of the SiO 2 surface.

36 MATERIALS SCIENCE↗