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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Calculating Radiation Damage (DPA) from Transmutation Products

This is a poster for an INL poster session. Accurate models for radiation damage are crucial for predicting material performance in radiation environments. The uncertainty of state-of-the-art radiation damage models is large, contributing to excessive safety margins. A major source of this uncertainty is neglecting the effect that transmutation products have on radiation damage. Transmutation products are new nuclides formed by neutron activation during irradiation; they can contribute to radiation damage by additional neutron capture or decay events. Ignoring the contribution of transmutation products leads to a significant underprediction of the radiation damage (e.g., >10% error in 316 stainless steel). This underprediction is accounted for in part by adding larger safety margins to designs. Currently, the state of the art explicitly accounts for only a single transmutation product, namely nickel-59, during the radiation damage calculation. All other transmutation products are assumed to not contribute to the radiation damage, because there is currently no established method to systematically track all or a selection of radiation damage contributions of transmutation products during activation. In the case of nickel-59, the current method is to apply a precalculated correlation that cannot be used for any other nuclide and is largely dependent on all nuclear engineers being experts in this niche topic. This project proposed to methodically find other transmutation products that cause significant radiation damage, and then to develop a general framework for systematically tracking the radiation damage from these nuclides. This was accomplished by combining the radiation damage calculation into the transmutation calculation already performed for irradiated structural materials. The key idea of our framework is to introduce radiation-damage "pseudo-nuclides" to the list of nuclides used in the transmutation analysis. This allows radiation damage to be tracked alongside the creation and destruction of transmutation products. The main deliverable of this project is a general framework for computing radiation damage while the damaged material undergoes transmutation; this capability allows a significantly more accurate estimation of radiation damage, and in turn reduce required safety margins thereby reducing the cost to construct reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Path-space variational inference for non-equilibrium coarse-grained systems

In this paper we discuss information-theoretic tools for obtaining optimized coarse-grained molecular models for both equilibrium and non-equilibrium molecular simulations. The latter are ubiquitous in physicochemical and biological applications, where they are typically associated with coupling mechanisms, multi-physics and/or boundary conditions. In general the non-equilibrium steady states are not known explicitly as they do not necessarily have a Gibbs structure. The presented approach can compare microscopic behavior of molecular systems to parametric and non-parametric coarse-grained models using the relative entropy between distributions on the path space and setting up a corresponding path-space variational inference problem. The methods can become entirely data-driven when the microscopic dynamics are replaced with corresponding correlated data in the form of time series. Furthermore, we present connections and generalizations of force matching methods in coarse-graining with path-space information methods. We demonstrate the enhanced transferability of information-based parameterizations to different observables, at a specific thermodynamic point, due to information inequalities. We discuss methodological connections between information-based coarse-graining of molecular systems and variational inference methods primarily developed in the machine learning community. However, we note that the work presented here addresses variational inference for correlated time series due to the focus on dynamics. The applicability of the proposed methods is demonstrated on high-dimensional stochastic processes given by overdamped and driven Langevin dynamics of interacting particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Processing of X-ray snapshots from crystals in random orientations

A new method for the treatment of partial reflections from X-ray snapshots is implemented in the program package nXDS, which yields intensity data of almost the same quality as those obtained by the classical rotation method. A functional expression is introduced that relates scattered X-ray intensities from a still or a rotation snapshot to the corresponding structure-factor amplitudes. The new approach was implemented in the program nXDS for processing monochromatic diffraction images recorded by a multi-segment detector where each exposure could come from a different crystal. For images containing indexable spots, the intensities of the expected reflections and their variances are obtained by profile fitting after mapping the contributing pixel contents to the Ewald sphere. The varying intensity decline owing to the angular distance of the reflection from the surface of the Ewald sphere is estimated using a Gaussian rocking curve. This decline is dubbed ‘Ewald offset correction’, which is well defined even for still images. Together with an image-scaling factor and other corrections, an explicit expression is defined that predicts each recorded intensity from its corresponding structure-factor amplitude. All diffraction parameters, scaling and correction factors are improved by post-refinement. The ambiguous case of a lower point group than the lattice symmetry is resolved by a method reminiscent of the technique of ‘selective breeding’. It selects the indexing alternative for each image that yields, on average, the highest correlation with intensities from all other images. Processing a test set of rotation images by XDS and treating the same images by nXDS as snapshots of crystals in random orientations yields data of comparable quality, clearly indicating an anomalous signal from Se atoms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
DOE OSTI2015

Conformation of ionizable poly Para phenylene ethynylene in dilute solutions

The conformation of dinonyl poly para phenylene ethynylenes (PPEs) with carboxylate side chains, equilibrated in solvents of different quality is studied using molecular dynamics simulations. PPEs are of interest because of their tunable electro-optical properties, chemical diversity, and functionality which are essential in wide range of applications. The polymer conformation determines the conjugation length and their assembly mode and affects electro-optical properties which are critical in their current and potential uses. The current study investigates the effect of carboxylate fraction on PPEs side chains on the conformation of chains in the dilute limit, in solvents of different quality. The dinonyl PPE chains are modeled atomistically, where the solvents are modeled both implicitly and explicitly. Dinonyl PPEs maintained a stretched out conformation up to a carboxylate fraction f of 0.7 in all solvents studied. The nonyl side chains are extended and oriented away from the PPE backbone in toluene and in implicit good solvent whereas in water and implicit poor solvent, the nonyl side chains are collapsed towards the PPE backbone. Thus, rotation around the aromatic ring is fast and no long range correlations are seen within the backbone.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Systematic renormalization of the effective theory of Large Scale Structure

A perturbative description of Large Scale Structure is a cornerstone of our understanding of the observed distribution of matter in the universe. Renormalization is an essential and defining step to make this description physical and predictive. Here we introduce a systematic renormalization procedure, which neatly associates counterterms to the UV-sensitive diagrams order by order, as it is commonly done in quantum field theory. As a concrete example, we renormalize the one-loop power spectrum and bispectrum of both density and velocity. In addition, we present a series of results that are valid to all orders in perturbation theory. First, we show that while systematic renormalization requires temporally non-local counterterms, in practice one can use an equivalent basis made of local operators. We give an explicit prescription to generate all counterterms allowed by the symmetries. Second, we present a formal proof of the well-known general argument that the contribution of short distance perturbations to large scale density contrast δ and momentum density π(k) scale as k{sup 2} and k, respectively. Third, we demonstrate that the common practice of introducing counterterms only in the Euler equation when one is interested in correlators of δ is indeed valid to all orders.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Emulating ab initio computations of infinite nucleonic matter

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for > 10 6 different parametrizations of a chiral interaction model with explicit Δ -isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He 4 , we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Computational Identification of Diverse Mechanisms Underlying Transcription Factor-DNA Occupancy

ChIP-based genome-wide assays of transcription factor (TF) occupancy have emerged as a powerful, high-throughput method to understand transcriptional regulation, especially on a global scale. This has led to great interest in the underlying biochemical mechanisms that direct TF-DNA binding, with the ultimate goal of computationally predicting a TF’s occupancy profile in any cellular condition. In this study, we examined the influence of various potential determinants of TF-DNA binding on a much larger scale than previously undertaken. We used a thermodynamics-based model of TF-DNA binding, called ‘‘STAP,’’ to analyze 45 TF-ChIP data sets from Drosophila embryonic development. We built a cross-validation framework that compares a baseline model, based on the ChIP’ed (‘‘primary’’) TF’s motif, to more complex models where binding by secondary TFs is hypothesized to influence the primary TF’s occupancy. Candidates interacting TFs were chosen based on RNA-SEQ expression data from the time point of the ChIP experiment. We found widespread evidence of both cooperative and antagonistic effects by secondary TFs, and explicitly quantified these effects. We were able to identify multiple classes of interactions, including (1) long-range interactions between primary and secondary motifs (separated by #150 bp), suggestive of indirect effects such as chromatin remodeling, (2) short-range interactions with specific inter-site spacing biases, suggestive of direct physical interactions, and (3) overlapping binding sites suggesting competitive binding. Furthermore, by factoring out the previously reported strong correlation between TF occupancy and DNA accessibility, we were able to categorize the effects into those that are likely to be mediated by the secondary TF’s effect on local accessibility and those that utilize accessibility-independent mechanisms. Finally, we conducted in vitro pull-down assays to test model-based predictions of short-range cooperative interactions, and found that seven of the eight TF pairs tested physically interact and that some of these interactions mediate cooperative binding to DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Difference equations and integral families for Witten diagrams

We show that tree-level and one-loop Mellin space correlators in anti-de Sitter space obey certain difference equations, which are the direct analog to the differential equations for Feynman loop integrals in the flat space. Finite-difference relations, which we refer to as “summation-by-parts relations”, in parallel with the integration-by-parts relations for Feynman loop integrals, are derived to reduce the integrals to a basis. We illustrate the general methodology by explicitly deriving the difference equations and summation-by-parts relations for various tree-level and one-loop Witten diagrams up to the four-point bubble level.

AdS-CFT Correspondence↗
DOE OSTI2015

Fermi orbital derivatives in self-interaction corrected density functional theory: Applications to closed shell atoms

A recent modification of the Perdew-Zunger self-interaction-correction to the density-functional formalism has provided a framework for explicitly restoring unitary invariance to the expression for the total energy. The formalism depends upon construction of Löwdin orthonormalized Fermi-orbitals which parametrically depend on variational quasi-classical electronic positions. Derivatives of these quasi-classical electronic positions, required for efficient minimization of the self-interaction corrected energy, are derived and tested, here, on atoms. Total energies and ionization energies in closed-shell singlet atoms, where correlation is less important, using the Perdew-Wang 1992 Local Density Approximation (PW92) functional, are in good agreement with experiment and non-relativistic quantum-Monte-Carlo results albeit slightly too low.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

flowVS: channel-specific variance stabilization in flow cytometry

Abstract Background Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. Results We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett’s likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. Conclusions The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett’s likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Chemical Complexity Controls Energy Dissipation and Defect Evolution

The development of metallic alloys is arguably one of the oldest sciences, dating back at least 3,000 years. Most research and applications have been focused on alloys with comprised multiple phases with one or two dominant elements, to which the addition of alloying elements in low concentrations leads to various performance improvements and changes in radiation resistance. In sharp contrast to traditional alloys, recent success in the synthesis of single phase concentrated solid solution alloys (SP-CSAs) has opened up new frontiers in materials research. In these alloys, a random arrangement of multiple elemental species on a lattice (fcc or bcc) results in unique site-to-site lattice distortions and local disordered chemical environments. Intense radiation in nuclear fission and fusion energy power systems, nuclear waste forms, high-energy accelerators and space exploration transfers energy to the electrons and atoms that make up the material, and thereby produces defects that ultimately compromise material strength and lifetime. A grand challenge in materials research is to understand complex electronic correlations and non-equilibrium atomic interactions, and how such intrinsic properties and dynamic processes affect energy transfer and defect evolution in irradiated materials. Since SP-CSAs possess unique links between intrinsic material properties (can be altered by alloy complexity), energy dissipation and various defect dynamic processes; they are ideal systems to fill knowledge gaps between electronic- /atomic-level interactions and radiation resistance mechanisms. In our work, we show that chemical disorder and compositional complexity in SP-CSAs have an enormous impact on defect dynamics through substantial modification of energy dissipation pathways. Based on a closely integrated computational and experimental study using a novel set of Ni-based SP-CSAs, we have explicitly demonstrated that increasing chemical disorder can lead to a substantial reduction in the electron mean free path and electrical and thermal conductivity. These reductions have a significant impact on energy dissipation and consequentially on defect evolution during ion irradiation. Considerable enhancement in radiation resistance with increasing chemical complexity from pure nickel to binary, and to more complex quaternary solid solutions, is observed under ion irradiation. Contrary to conventional alloys with low solute concentration but multiple phases, energy dissipation and defect evolution at the level of electrons and atoms in SP- CSA systems with extreme compositional disorder is an unexplored frontier in materials science. The integrated experimental/modeling effort provides new insights into defect dynamics at the level of atoms and electrons, and an innovative path forward towards solving a long-standing challenge in structural materials. Increasing chemical complexity achieved orders-of-magnitude reductions in electron mean free paths and electron and thermal conductivities of alloys of NiCo, NiFe and NiCoFeCr, compared to Ni, and suppressed damage accumulation under ion irradiation. This discovery provides insights to address the grand challenge of understanding complex electronic correlations and non-equilibrium atomic interactions, and the effect of these intrinsic properties and dynamic processes on energy transfer and defect evolution in irradiated materials. Understanding how material properties and defect dynamics can be tailored by alloy complexity may pave the way for new design principles of functional alloys. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2017

Sample-based synthesis of two-scale structures with anisotropy

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the sample structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.

42 ENGINEERING↗
DOE OSTI2025

Interrelationships among methods of estimating microbial biomass across multiple soil orders and biomes

Understanding the role of soil microbes is critical to ecosystem processes, and more thorough comparisons of measurement proxies for soil microbial biomass could broaden the inclusion of explicit microbial parameterization in soil carbon cycling and earth system models. We measured physical, chemical, and biological data from eight soil orders representing 11 major biomes and four climate regions. Four prominent methods to measure microbial abundance—chloroform fumigation extraction (CFE), total DNA yield, gene copy number by quantitative polymerase chain reaction (GCN), and phospholipid fatty acids (PLFA)—were compared to assess their relationships with each other and with soil characteristics. Correlations were observed when comparing methods, with CFE correlating strongly with total DNA yield, GCN, and PLFA; CFE with bacterial GCN and bacterial PLFA; and to a lesser extent, total PLFA and total DNA yield. Correlations improved with the removal of organic soils (Histosols, Gelisols). Comparisons involving extracted DNA were improved by correcting for clay content, due to DNA extraction inefficiencies in clay-rich soils. Correlations involving fungi (PLFA or GCN) were always less significant. These methods could serve as reliable, inter-relatable proxies for the estimation of total soil microbial biomass while recognizing that the proxies are less effective at parsing differences between bacteria and fungi. Here, we provide specific equations to relate measures of soil microbial biomass by these four different methods to enable microbial models to utilize a greater diversity of observed data sources in parameterizations and simulations. Caveats for the equations and their values are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Field-driven ion pairing dynamics in concentrated electrolytes

Here, we investigate ion pairing dynamics in electrolytes driven far from equilibrium using molecular simulations and nonequilibrium rate theory. Focusing on 0.5M LiPF 6 in water and acetonitrile under uniform electric fields, we compute transition path theory observables, including reactive fluxes and mean first-passage times of ion pairing. Moreover, we introduce a dynamical proxy of free-ion population, where its field-induced change is strongly correlated with the nonlinear enhancement of conductivity, yielding an increase of 40% at 50 mV/Å in acetonitrile, compared to that of less than 10% in aqueous electrolytes. Further kinetic analysis elucidates that Onsager’s classical theory substantially overestimates field-induced enhancement of ion pair dissociation in molecular electrolytes. This discrepancy arises from solvent-mediated dynamical pathways and field-induced dielectric decrement that suppress ion pair dissociation within explicit solvents, highlighting that a faithful description of molecular details is essential. Our results provide a molecular interpretation of nonlinear electrolyte transport beyond continuum theories and establish a general framework for quantifying nonequilibrium reaction kinetics in condensed phase systems.

Moon, Seokjin [University of California, Berkeley,↗
DOE OSTI2022

Distinguishing between Quantum and Classical Markovian Dephasing Dissipation

Understanding whether dissipation in an open quantum system is truly quantum is a question of both fundamental and practical interest. We consider n qubits subject to correlated Markovian dephasing and present a sufficient condition for when bath-induced dissipation can generate system entanglement and hence must be considered quantum. Surprisingly, we find that the presence or absence of time-reversal symmetry plays a crucial role: broken time-reversal symmetry is required for dissipative entanglement generation. Further, simply having nonzero bath susceptibilities is not enough for the dissipation to be quantum. We also present an explicit experimental protocol for identifying truly quantum dephasing dissipation and lay the groundwork for studying more complex dissipative systems and finding optimal noise mitigating strategies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Geometry of conformal manifolds and the inversion formula

Families of conformal field theories are naturally endowed with a Riemannian geometry which is locally encoded by correlation functions of exactly marginal operators. We show that the curvature of such conformal manifolds can be computed using Euclidean and Lorentzian inversion formulae, which combine the operator content of the conformal field theory into an analytic function. Analogously, operators of fixed dimension define bundles over the conformal manifold whose curvatures can also be computed using inversion formulae. These results relate curvatures to integrated four-point correlation functions which are sensitive only to the behavior of the theory at separated points. We apply these inversion formulae to derive convergent sum rules expressing the curvature in terms of the spectrum of local operators and their three-point function coefficients. We further show that the curvature can smoothly diverge only if a conserved current appears in the spectrum, or if the theory develops a continuum. We verify our results explicitly in 2d examples. In particular, for 2d (2,2) superconformal field theories we derive a lower bound on the scalar curvature, which is saturated by free theories when the central charge is a multiple of three.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Ellipsometry characterization of polycrystalline ZnO layers with the modeling of carrier concentration gradient: Effects of grain boundary, humidity, and surface texture

Spectroscopic ellipsometry (SE) has been applied to study the effects of grain boundary, humidity, and surface texture on the carrier transport properties of Al-doped ZnO layers fabricated by dc and rf magnetron sputtering. In the SE analysis, the variation in the free carrier absorption toward the growth direction, induced by the ZnO grain growth on foreign substrates, has been modeled explicitly by adopting a multilayer model in which the optical carrier concentration (N{sub opt}) varies continuously with a constant optical mobility (μ{sub opt}). The effect of the grain boundary has been studied by comparing μ{sub opt} with Hall mobility (μ{sub Hall}). The change in μ{sub Hall}/μ{sub opt} indicates a sharp structural transition of the ZnO polycrystalline layer at a thickness of d ∼ 500 nm, which correlates very well with the structure confirmed by transmission electron microscopy. In particular, below the transition thickness, the formation of the high density grain boundary leads to the reduction in the μ{sub Hall}/μ{sub opt} ratio as well as N{sub opt}. As a result, we find that the thickness dependence of the carrier transport properties is almost completely governed by the grain boundary formation. On the other hand, when the ZnO layer is exposed to wet air at 85 °C, μ{sub Hall} reduces drastically with a minor variation of μ{sub opt} due to the enhanced grain boundary scattering. We have also characterized textured ZnO:Al layers prepared by HCl wet etching by SE. The analysis revealed that the near-surface carrier concentration increases slightly after the etching. We demonstrate that the SE technique can be applied to distinguish various rough textured structures (size ∼ 1 μm) of the ZnO layers prepared by the HCl etching.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗