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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Origin of Disorder Tolerance in Piezoelectric Materials and Design of Polar Systems

Current high-performing piezoelectric materials are dominated by perovskites that rely on soft optical phonon modes stabilized by disorder near a morphotropic phase boundary and a unique resilience of the polar response to that disorder. To identify structural families with similar resilience, in this study we develop a first-principles sensitivity analysis approach to determine the effect of disorder on the piezoelectric response for structures in the Materials Project database. In well-known piezoelectric systems, the lattice dynamics, rather than internal strain or dielectric, control the polar response. Additionally, multiple stable optical phonon modes are found to contribute to the piezoelectric response, providing a fingerprint for disorder tolerance. A multiple-phonon mode criterion is used to evaluate candidate materials for disorder-tolerant piezoelectric prototype systems. Five promising structures are altered through chemical substitution, generating potential MPB end points with large piezoelectric responses beyond perovskites including Akermanite Sr 2 x Ca 2 – 2 x CoSi 2 O 7 , which exhibits a nearly 20% increase in response at the 50% composition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Oil in Alaska North Slope Gas Hydrate Reservoir: Micro-CT and Flow Simulation Insights into Permeability

Gas hydrate-bearing sands on the Alaska North Slope (ANS) host minor volumes of crude oil whose impact on formation permeability has never been quantified relative to a gas hydrate reservoir system. Here, we combine in situ pressure-core microcomputed-tomography (μ-CT), thermogravimetric analysis (TGA), gas-chromatography–mass-spectrometry (GC–MS), scanning-electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and Stokes-flow simulation to (i) quantify oil saturation, (ii) infer its source, and (iii) evaluate its influence on permeability after gas-hydrate dissociation. μ-CT and SEM-EDS imaging identify the host sediment as silty, with some grain-coating clay present. Eight representative 3003-voxel subvolumes extracted from a preserved pressure core (Core 15P-3c, from the B1 sand (unit B), HYDRATE 02 Geo Data Well (GDW), 886.96–887.29 m measured depth, MD) exhibit porosities of 0.34–0.37 and an average oil saturation of 0.09 ± 0.03, in comparison to an independent TGA-based estimate of 0.16. GC-MS fingerprints obtained from an adjacent depressurized core (Core 17P-1, 891.37–891.44 m MD), together with oil pore habit revealed by μ-CT, suggest that the oil is partly native but also includes contributions from mineral oil-based drilling fluid contamination. Further analysis of oil–porewater interactions and flushing tests confirms that native oil saturation in the analyzed samples ranges from 0.04 to 0.08 with an average of approximately 0.06, and the oil is highly immobile. Flow simulations demonstrate that the native oil saturation of ≈0.06 reduces permeability by approximately 50% due to both pore blockage and increased flow-path tortuosity. These findings reveal the potential presence of native oil within the ANS gas hydrate reservoir and suggest that future simulation models may need to account for its impact on permeability to improve long-term performance predictions of gas and water production.

02 PETROLEUM↗
DOE OSTI2025

Ion Clusters Reveal the Sources, Impacts, and Drivers of Freshwater Salinization

Population growth, land use change, climate change, and natural resource extraction are driving the salinization of freshwater resources worldwide. Reversing these trends will require data-centric approaches that identify salt sources, environmental drivers, and ecosystem responses. In this study, we applied principal component analysis and hierarchical clustering to identify ion covariance patterns, or “ion clusters,” in Broad Run, an urban stream in the Mid-Atlantic United States. These clusters correspond to distinct hydrologic regimes and reveal specific salinization risks: (1) phosphorus pollution mobilized during summer storms (Cluster 1); (2) elevated concentrations of sulfate and bicarbonate during baseflow (Cluster 2), likely reflecting groundwater discharge; and (3) elevated specific conductance and sodium, chloride, and potassium ion concentrations during snowmelt and rain-on-snow events (Cluster 3), driven by deicer and anti-icer wash-off. These ion fingerprints offer a transferable framework for diagnosing salt sources, assessing ecological risk, and identifying management targets. Our findings underscore the need for next-generation stormwater infrastructure and smart growth policies to protect aquatic life in rapidly urbanizing watersheds.

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

Investigation of the Solution Chemistry of Hybrid Organic–Inorganic Indium Halides for New Material Discovery

Recently, metal halide perovskites (MHPs) have emerged as a new class of materials for optical and electronic applications such as solar cells and ionizing radiation detectors. Although the solution-processability of MHPs is among their greatest advantages, the solution chemistries of most metal halide systems and their relationship with the observed structural and chemical diversity are poorly understood. In this work, we study the solution chemistry of a model indium halide system, methylammonium (MA)–In–Br, using a combination of the UV–vis spectroscopy, electrospray ionization mass spectrometry (ESI-MS) measurements, small-angle X-ray scattering (SAXS), and density functional theory (DFT) calculations. Our results show that indium could form either octahedral [InBr 6 3– ] or tetrahedral [InBr 4 – ] anions in solution or a combination of both, depending on the loading ratios of MABr and InBr 3 reactants. Understanding the solution chemistry of this system and recognizing the optical fingerprints of these polyanions allow for targeted crystallization of two novel compounds: MAInBr 4 featuring tetrahedral [InBr 4 – ] anions and MA 2 InBr 5 containing both octahedral [InBr 6 3– ] and tetrahedral [InBr 4 – ] anions. Further increase of the MABr content leads to the formation of previously reported MA 4 InBr 7 , containing only octahedral [InBr 6 3– ] anions separated by Br – anions. Furthermore, our results suggest that understanding the solution chemistry of multinary metal halide systems could be a valuable tool for discovering functional materials for practical applications.

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

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning

Accurately predicting small molecule partitioning and hydrophobicity is critical in the drug discovery process. There are many heterogeneous chemical environments within a cell and entire human body. For example, drugs must be able to cross the hydrophobic cellular membrane to reach their intracellular targets, and hydrophobicity is an important driving force for drug–protein binding. Atomistic molecular dynamics (MD) simulations are routinely used to calculate free energies of small molecules binding to proteins, crossing lipid membranes, and solvation but are computationally expensive. Machine learning (ML) and empirical methods are also used throughout drug discovery but rely on experimental data, limiting the domain of applicability. We present atomistic MD simulations calculating 15,000 small molecule free energies of transfer from water to cyclohexane. This large data set is used to train ML models that predict the free energies of transfer. We show that a spatial graph neural network model achieves the highest accuracy, followed closely by a 3D-convolutional neural network, and shallow learning based on the chemical fingerprint is significantly less accurate. A mean absolute error of ~4 kJ/mol compared to the MD calculations was achieved for our best ML model. We also show that including data from the MD simulation improves the predictions, tests the transferability of each model to a diverse set of molecules, and show multitask learning improves the predictions. This work provides insight into the hydrophobicity of small molecules and ML cheminformatics modeling, and our data set will be useful for designing and testing future ML cheminformatics methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

QC-GN 2 oMS 2 : a Graph Neural Net for High Resolution Mass Spectra Prediction

Predicting the mass spectrum of a molecular ion is often accomplished via three generalized approaches: rules-based methods for bond breaking, deep learning, or quantum chemical (QC) modeling. Rules-based approaches are often limited by the conditions for different chemical subspaces and perform poorly under chemical regimes with few defined rules. QC modeling is theoretically robust but requires significant amounts of computational time to produce a spectrum for a given target. Among deep learning techniques, graph neural networks (GNNs) have performed better than previous work with fingerprint-based neural networks in mass spectra prediction. To explore this technique further, we investigate the effects of including quantum chemically derived information as edge features in the GNN to increase predictive accuracy. The models we investigated include categorical bond order, bond force constants derived from extended tight-binding (xTB) quantum chemistry, and acyclic bond dissociation energies. Throughout this work, we evaluated these models against a control GNN with no edge features in the input graphs. Bond dissociation enthalpies yielded the best improvement with a cosine similarity score of 0.462 relative to the baseline model (0.437). In this work we also apply dynamic graph attention which improves performance on benchmark problems and supports the inclusion of edge features. Between implementations, we investigate the nature of the molecular embedding for spectra prediction and discuss the recognition of fragment topographies in distinct chemistries for further development in tandem mass spectrometry prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ice Phase Classification Made Easy with Score-Based Denoising

Accurate identification of ice phases is essential for understanding various physicochemical phenomena. However, such classification for structures simulated with molecular dynamics is complicated by the complex symmetries of ice polymorphs and thermal fluctuations. For this purpose, both traditional order parameters and data-driven machine learning approaches have been employed, but they often rely on expert intuition, specific geometric information, or large training data sets. In this work, we present an unsupervised phase classification framework that combines a score-based denoiser model with a subsequent model-free classification method to accurately identify ice phases. Further, the denoiser model is trained on perturbed synthetic data of ideal reference structures, eliminating the need for large data sets and labeling efforts. The classification step utilizes the smooth overlap of atomic position (SOAP) descriptors as the atomic fingerprint, ensuring Euclidean symmetries and transferability to various structural systems. Our approach achieves a remarkable 100% accuracy in distinguishing ice phases of test trajectories using only seven ideal reference structures of ice phases as model inputs. This demonstrates the generalizability of the score-based denoiser model in facilitating phase identification for complex molecular systems. The proposed classification strategy can be broadly applied to investigate structural evolution and phase identification for a wide range of materials, offering new insights into the fundamental understanding of water and other complex systems.

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

Ab Initio Study of Vibronic and Magnetic 5f-to-5f and Dipole-Allowed 5f-to-6d and Charge-Transfer Transitions in [UX 6 ] n – (X = Cl, Br; n = 1, 2)

The absorption spectra of the octahedral [UX 6 ] n– (X = Cl, Br; n = 1, 2) complexes in the near-infrared (NIR) and UV–vis spectral regions were studied theoretically, using a relativistic restricted active space second-order perturbation theory (RASPT2) wavefunction framework, with the spin–orbit (SO) coupling treated by state interaction, in conjunction with Kohn–Sham density functional theory calculations for determining the vibrational normal modes. The electric-dipole-allowed ligand-to-metal charge-transfer (LMCT) and 5f-to-6d transitions, and the electric-dipole-forbidden 5f-to-5f ligand field (LF) transitions, are thereby obtained within the same theoretical framework. For the 5f-to-5f LF transitions, the observed absorption intensity is mostly due to vibronic coupling with low-energy electric-dipole-allowed transitions, but in some cases, the magnetic dipole intensity of the purely electronic transition has comparable intensity to the vibronic transitions. Here, experimental LF spectra of 5f 2 open-shell systems have been reported decades back, but ab initio calculations of their vibronic intensity have not yet been reported in the literature. Although the LF spectra for the 5f 2 systems can be assigned in detail, based on the calculations, the spectra are very complex and the underlying electronic states are strongly multiconfigurational. Therefore, the usefulness of the LF spectra beyond serving as a “fingerprint” of the LF and the metal oxidation state appears to be limited.

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

Time-Resolved Optical Pump-Resonant X-ray Probe Spectroscopy of 4-Thiouracil: A Simulation Study

We theoretically monitor the photoinduced ππ* → nπ* internal conversion process in 4-thiouracil (4TU), triggered by an optical pump. The element-sensitive spectroscopic signatures are recorded by a resonant X-ray probe tuned to the sulfur, oxygen, or nitrogen K-edge. We employ high-level electronic structure methods optimized for core-excited electronic structure calculation combined with quantum nuclear wavepacket dynamics computed on two relevant nuclear modes, fully accounting for their quantum nature of nuclear motions. We critically discuss the capabilities and limitations of the resonant technique. For sulfur and nitrogen, we document a pre-edge spectral window free from ground-state background and rich with ππ* and nπ* absorption features. The lowest sulfur K-edge shows strong absorption for both ππ* and nπ*. In the lowest nitrogen K-edge window, we resolve a state-specific fingerprint of the ππ* and an approximate timing of the conical intersection via its depletion. A spectral signature of the nπ* transition, not accessible by UV–vis spectroscopy, is identified. The oxygen K-edge is not sensitive to molecular deformations and gives steady transient absorption features without spectral dynamics. Here, the ππ*/nπ* coherence information is masked by more intense contributions from populations. Altogether, element-specific time-resolved resonant X-ray spectroscopy provides a detailed picture of the electronic excited-state dynamics and therefore a sensitive window into the photophysics of thiobases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Unimolecular Dynamics of Partially Deuterated Hydroperoxyalkyl Intermediates (•QOOD) in Cyclohexane and Cyclopentane Oxidation

The hydroperoxyalkyl radicals (•QOOH) formed in cyclohexane and cyclopentane oxidation with carbon radical center at the β site relative to the hydroperoxy group have recently been observed through their infrared fingerprint and time- and energy-resolved unimolecular dissociation dynamics to hydroxyl (OH) radical and cyclic ether products. Partial deuteration shifts the IR transitions associated with OH/OD motion to lower frequencies, providing a new window on the IR spectroscopy and unimolecular dynamics of these transient intermediates. Specifically, the overtone OD stretch (2ν OD ) has been identified at 5215.0 cm –1 and 5216.0 cm –1 for the β-QOOD intermediates in cyclohexane and cyclopentane oxidation, respectively. Unimolecular decay rates of the •QOOD intermediates at these energies have been obtained from the time-resolved appearance of OD products. The experimental rates are compared with statistical microcanonical rates evaluated using RRKM theory, including heavy-atom tunneling associated with simultaneous O–O bond elongation and C–O–O angle contraction along the reaction pathway. The experimental rates provide a further test of the previously determined transition state (TS) barriers, which were computed utilizing a benchmarking approach that builds on higher-level reference calculations for the smaller ethane oxidation system. Here, the experimental rate measurements for both •QOOD intermediates agree well with the computed rates after accounting for small changes in zero-point energy and a minor empirical adjustment of the TS barriers in both systems.

Ethers↗
DOE OSTI2026

Exploring Local Vibrational Structure in Protein-Bound Chlorophyll a: Isotope-Enrichment Experiments and Electrostatic Analysis

Local chlorophyll (Chl) vibrations play an essential role in biological photosynthesis by facilitating rapid energy transfer between pigments. In research studies, they also provide a useful spectroscopic probe of the local protein environment that surrounds each pigment. However, measuring the complete vibrational absorption spectrum of a protein-bound Chl molecule is much more difficult than, for example, Chl in neat solvent due to overlap with protein vibrations that typically drown out Chl vibrational features. Resonance Raman and fluorescence spectroscopies provide a way around this problem for Franck–Condon active vibrations, but these often rely on cryogenic measurement conditions and fail to capture vibrational signatures from, e.g., ester-group vibrations that lack coupling to a convenient electronic transition. In the present contribution, we use 13 C-enrichment of the protein backbone to shift protein background signals to lower frequency, providing a largely clean spectral window in which to study local Chl a C═O stretch modes. A room-temperature absorption spectrum for Chl a in the water-soluble chlorophyll protein (WSCP) of Lepidium virginicum is thus extracted as a difference between protein-plus-pigment and protein-only vibrational spectra. Excellent agreement in the molecular fingerprint region with the vibrational spectrum of Chl a in organic solvents confirms that the resulting spectrum represents the response of the protein-bound Chl a molecule. Furthermore, the ester group resonance is observed to shift in response to the S53P mutation that eliminates a 17 3 ester group hydrogen bond from the protein environment. Finally, we analyze these experimental results using MD-based electrostatic analysis, finding that electric-field mapping at the C atom of the ester group provides a satisfactory explanation for the observed frequency shifts between organic solvent and protein environment. MD analysis further suggests that a red-shifted ester peak observed experimentally for the S53P mutant results from solvation of the 17 3 Chl ester group due increase water penetration into the Chl-binding pocket relative to wild-type WSCP. Here, we anticipate that these results will prove useful both for benchmarking future simulation work and as a reference for interpreting Chl vibrational spectra as a probe of pigment–protein interactions.

14 SOLAR ENERGY↗
DOE OSTI2021

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗
DOE OSTI2023

Core-Level Spectroscopy with Hard and Soft X-rays on Phosphorus-Containing Compounds for Energy Conversion and Storage

The electronic properties of nine solid phosphorus (P)-containing compounds with varying oxidation states and chemical environments, including GaP (–III) , InP (–III) , red-P (0) , H 3 P (III) O 3 , Na 2 H 2 P 2 (IV) O 6 , H 3 P (V) O 4 , KH 2 P (V) O 4 , Na 2 HP (V) O 4 , and InP (V) O 4 , are investigated using X-ray absorption near-edge structure (XANES) spectroscopy in the hard (P K-edge) and soft X-ray regime (P L 2,3 - edge). We find shifts in the absorption-edge positions and correlate them with the ligands surrounding the P atom, likely causing a different core–hole interaction screening for different compounds. Complementing the experimental analysis, ab initio many-body calculations of XANES spectra provide insights into the excitonic nature of the observed spectral features and their impact on the electronic structure of the materials. Furthermore, we report on P K-edge XANES measurements on aqueous phosphorus-containing acids, including H 3 PO 3 , H 3 PO 4 , and their mixtures. At first sight, the spectra of the aqueous acids are similar to those of their solid counterparts. However, close inspection reveals a slight red shift of the absorption edge and the presence of fewer spectral features compared with spectra of the respective solids. Mixtures of aqueous acids display spectral features corresponding to the individual components, indicating the potential for speciation and quantification through fingerprinting.

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

In Situ Monitoring of H 2 -Induced Nonstoichiometry in Cu 2 O

Nonstoichiometry plays a pivotal role in the functioning of oxide materials, but it is challenging to measure the non-stoichiometric formation and the resulting charge redistribution around the point defects. Using ambient-pressure X-ray photoelectron spectroscopy and Auger electron spectroscopy to monitor the reduction of Cu 2 O in H 2 , we identify the formation of an intermediate, oxygen-deficient Cu 2 O phase and its progressive inward growth into the deeper region of the oxide. Complemented by DFT modeling, we show that the oxygen-deficient Cu 2 O formation occurs via molecular H 2 adsorption at the Cu 2 O surface, which results in the loss of lattice O from the formation of H 2 O molecules that desorb spontaneously from the oxide surface. The resulting oxy-gen-deficient Cu 2 O is a stable intermediate that persists before the Cu 2 O is fully reduced to metallic Cu. The O vacancy induced charge redistribution of the coordinating Cu atoms results in a satellite feature in Cu LMM, which can be used a fingerprint to identify the nonstoichiometry and local charge transfer in non-stoichiometric oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spectroscopic Signature of Metal-hydroxo and Peroxo Species in K-edge X-ray Absorption Spectra

Metal-dioxygen species are important intermediates formed during dioxygen activations by metalloenzymes in various biological processes, by catalysts in fuel cells, and prior to O 2 evolution by photosystem II. In this work, we focus on manganese-porphyrin complexes using tetramesitylporphyrin ligand (TMP) to explore changes in Mn K-edge X-ray absorption spectroscopy (XAS) associated with the formation of Mn-hydroxide and Mn–O 2 peroxide species. With limited spectroscopic characterization of these compounds, Mn K β X-ray emission spectroscopy (XES), XAS, density functional theory (DFT), and time-dependent DFT (TD-DFT) analysis will enhance our understanding of their complex electronic structure. We show that the shape of the pre-edge in the K-edge Mn X-ray absorption near-edge structure (XANES) can serve as a spectroscopic signature of the Mn III -peroxo formation and thus can be used to track the presence of the side-on peroxide as an intermediate in time-resolved or in situ experiments. In conclusion, our results will help to further summarize the spectroscopic fingerprints for peroxo and hydroxo species, addressing the challenge of identifying the reactive metal species in catalytic reactions.

Extended X-ray absorption fine structure↗
DOE OSTI2026

Multinuclear Solid-State NMR and NMR Crystallography of Solid Forms of Creatine and Creatinine

Creatine is a performance-enhancing supplement with two widely available commercial solid forms, namely, creatine monohydrate (creatine·H 2 O) and creatine HCl, the latter of which does not have a reported crystal structure. Moreover, commercial formulations of creatine may contain creatinine, an undesired impurity phase resulting from the self-cyclization of creatine during manufacturing. Therefore, reliable methods for characterizing the different solid forms of creatine and detecting the presence of creatinine are essential. Herein, we address these challenges using 13 C, 15 N, and 35 Cl solid-state NMR (SSNMR) spectroscopy to obtain distinct spectral fingerprints for creatine·H 2 O and creatine HCl, along with creatinine and creatinine HCl. The acquisition of these SSNMR spectra offers a robust approach for both the rapid characterization of each solid form and the detection of the impurity phases. Additionally, quadrupolar NMR crystallography-guided crystal structure prediction (QNMRX-CSP) was applied for the de novo crystal structure determination of creatine HCl, which was validated by the subsequently determined single-crystal X-ray diffraction (SCXRD) structure. Finally, to investigate the relationship between NMR parameters and structural features, 13 C and 15 N chemical shifts and 35 Cl electric field gradient (EFG) tensors were computed from geometry-optimized structures of the four solid forms by using dispersion-corrected DFT-D2* methods. Finally, this integrative approach offers a powerful framework for advancing the structural understanding and quality control of creatine-based supplements and next-generation formulations, as well as a wide range of other solid pharmaceuticals and nutraceuticals.

NMR↗
DOE OSTI2022

Controlling the Balance between Remote, Pinhole, and van der Waals Epitaxy of Heusler Films on Graphene/Sapphire

Remote epitaxy is promising for the synthesis of lattice-mismatched materials, exfoliation of membranes, and reuse of expensive substrates. However, clear experimental evidence of a remote mechanism remains elusive. Alternative mechanisms such as pinhole-seeded epitaxy or van der Waals epitaxy can often explain the resulting films. Here, in this study, we show that growth of the Heusler compound GdPtSb on clean graphene/sapphire produces a 30° rotated (R30) superstructure that cannot be explained by pinhole epitaxy. With decreasing temperature, the fraction of this R30 domain increases, compared to the direct epitaxial R0 domain, which can be explained by a competition between remote versus pinhole epitaxy. Careful graphene/substrate annealing and consideration of the relative lattice mismatches are required to obtain epitaxy to the underlying substrate across a series of other Heusler films, including LaPtSb and GdAuGe. The R30 superstructure provides a possible experimental fingerprint of remote epitaxy, since it is inconsistent with the leading alternative mechanisms.

36 MATERIALS SCIENCE↗