The Center for Materials Physics and Technology performs basic and applied research on functional, structural, biological, and electronic material systems. Research includes the study of the fundamental physics and properties of materials and systems across wide ranges of length and time scales. The Center pioneers new methods for studying these systems including original experimental techniques for the development of electronic devices, as well as the development of new computational methods for modeling systems. The Center develops innovative scientific and engineering solutions for systems ranging from the atomic scale through the macroscopic, and from basic physics through the prototyping of devices for naval applications.
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Recent Publications
2018

Ordered Structure of FeGe2 Formed During SolidPhase Epitaxy 

Physical Review Materials 
2018 
Show abstract »Fe3Si/Ge(Fe,Si)/Fe3Si thinfilm stacks were grown by a combination of molecular beam epitaxy and solidphase epitaxy (Ge on Fe3Si). The stacks were analyzed using electron microscopy, electron diffraction, and synchrotron xray diffraction. The Ge(Fe,Si) films crystallize in the welloriented, layered tetragonal structure FeGe2 with space group P4mm. This kind of structure does not exist as a bulk material and is stabilized by the solidphase epitaxy of Ge on Fe3Si. We interpret this as an ordering phenomenon induced by minimization of the elastic energy of the epitaxial film.

Parametric Modeling of NIR and SWIR Reflectance Spectra for Dye Mixtures in Fabrics Using Reference Spectra 

Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery 
2018 
Show abstract »This study describes a parametric model of diffuse reflectance for the purpose of simulating the spectral response of nearinfrared (NIR, 0.70.9 mu m) and shortwave infrared (SWIR, 0.91.7 mu m) absorbing dyes for tailoring the NIRSWIR reflectance of fabrics. This model combines diffusereflectance theory with reference spectra for simulating absorption in fabric of NIR/SWIR absorbing dyes whose absorption spectra span the NIR/SWIR spectral range. Fabric samples consisting of a cotton blend were used as the test substrate for NIR/SWIR dye application. The results of this study demonstrate application of the parametric model for simulating NIR/SWIR spectral responses corresponding to variable dye and dye blend concentrations in fabrics.

PhaseField Modeling of Nugget Zone for a AZ31MgAlloy Friction Stir Weld 

Journal of Materials Engineering and Performance 
2018 
Show abstract »This work presents simulation of microstructure evolution in the nugget zone (NZ) of a AZ31Mgalloy friction stir weld. The process parameters (tool geometrical characteristics, rotational speed, travel speed, applied load) have been correlated with the resulting microstructural features in the NZ of the weld (grain size and population) with the aid of the MICRESS software, which provides the ability to simulate both nucleation and grain growth during dynamic recrystallization phenomena evolving in the NZ during the weld thermal cycle. The input parameters of the developed model include the tool geometry, the welding conditions as well as the recrystallization energy, the grain boundary mobility and specific material properties. NZ microstructure obtained by simulation shows good agreement with experimental measurements for both grain population and size.

Realistic Atomistic Structure of Amorphous Silicon from MachineLearningDriven Molecular Dynamics 

Journal of Physical Chemistry Letters 
2018 
Show abstract »Amorphous silicon (aSi) is a widely studied noncrystalline material, and yet the subtle details of its atomistic structure are still unclear. Here, we show that accurate structural models of aSi can be obtained using a machinelearningbased interatomic potential. Our best aSi network is obtained by simulated cooling from the melt at a rate of 10(11)K /s(that is, on the 10 ns time scale), contains less than 2% defects, and agrees with experiments regarding excess energies, diffraction data, and Si29 NMR chemical shifts. We show that this level of quality is impossible to achieve with faster quench simulations. We then generate a 4096atom system that correctly reproduces the magnitude of the first sharp diffraction peak (FSDP) in the structure factor, achieving the closest agreement with experiments to date. Our study demonstrates the broader impact of machinelearning potentials for elucidating structures and properties of technologically important amorphous materials.

Relation Between SingleMolecule Properties and Phase Behavior of Intrinsically Disordered Proteins 

Proceedings of the National Academy of Sciences of the United States of America 
2018 
Show abstract »Proteins that undergo liquidliquid phase separation (LLPS) have been shown to play a critical role in many physiological functions through formation of condensed liquidlike assemblies that function as membraneless organelles within biological systems. To understand how different proteins may contribute differently to these assemblies and their functions, it is important to understand the molecular driving forces of phase separation and characterize their phase boundaries and material properties. Experimental studies have shown that intrinsically disordered regions of these proteins are a major driving force, as many of them undergo LLPS in isolation. Previous work on polymer solution phase behavior suggests a potential correspondence between intramolecular and intermolecular interactions that can be leveraged to discover relationships between singlemolecule properties and phase boundaries. Here, we take advantage of a recently developed coarsegrained framework to calculate the theta temperature Ttheta, the Boyle temperature TB, and the critical temperature Tc for 20 diverse protein sequences, and we show that these three properties are highly correlated. We also highlight that these correlations are not specific to our model or simulation methodology by comparing between different pairwise potentials and with data from other work. We, therefore, suggest that smaller simulations or experiments to determine Ttheta or TB can provide useful insights into the corresponding phase behavior.

Representing Crack Growth in Additively Manufactured Ti6Al4V 

International Journal of Fatigue 
2018 
Show abstract »The aerospace industry is now seriously considering the use of Additive Manufacturing (AM) both in new aircraft design and also for aircraft sustainment. However, as explained in MILSTD 1530 certification requires the operational life of the airframe to be determined by a damage tolerance analysis. In addition, MILSTD1530 reinforces this requirement and that and the role of testing is merely to validate or correct the analysis. This means that if AM Ti6Al4V produced parts are to be used as load carrying members it is important that the crack growth (da/dN) versus stress intensity change (Delta K) curves be determined and, if possible, a valid mathematical representation is determined. Within the aerospace industry, the NASGRO computer program is the most widely used to compute crack growth and hence to determine operational life. In this context, the present paper demonstrates that the associated crack growth curves can be represented reasonably well by the HartmanSchijve variant of the NASGRO crack growth equation regardless of the specific AM process studied, the power level used and the build direction. This is achieved by applying the HartmanSchijve equation to data produced for a wide variety of AM processes. It is also shown that the variability in the various da/dN versus Delta K curves is captured reasonably well by proper changes in the threshold and the effective fracture toughness terms. A consequence of the comparative analysis of the data indicates that if AMproduced parts are to be used on operational aircraft a focus of future research should be on minimizing the size of the nucleating material discontinuities. This includes small naturally occurring cracks that arise due to the stress concentrations associated with the surface roughness as well as material discontinuities in the bulk of the material.

Role of ManyBody Interactions in the Structure of CoarseGrained Polymers 

Physical Review E 
2018 
Show abstract »In developing coarsegrained (CG) polymer models it is important to reproduce both local and moleculescale structure. We develop a procedure for fast calculation of the bondorientation correlation and the internal squared distance < R2(M)> through evaluation of the probability distribution functions that represent a CG model. Different CG models inherently contain or omit correlations between CG variables. Here, we construct CG models that contain specific correlations between CG variables. The importance of different correlations is tested on CG models of polyethylene, polytetrafluoroethylene, and polyLlactic acid. The chain stiffness and < R2(M)> are calculated using both analytic evaluation and Monte Carlo sampling, and approximate model results are compared with exact results from allatom simulations. For polymers with an exponential correlation decay, the bondorientation correlation and < R2(M)> indicate which CG variable correlations are most important to reproduce moleculescale structure. Analysis of the bondorientation correlation and internalsquared distance indicates that for polyLlactic acid the bondorientation correlation requires qualitatively different additional terms in CG models and quantifies the error in neglecting this important behavior.

Simulating ATR Spectra for Detecting Nerve AgentSorbent Binding 

Chemical, Biological, Radiological, Nuclear, and Explosives (Cbrne) Sensing Xix 
2018 
Show abstract »Prototype simulations of attenuated total re flection (ATR) applied for infrared molecular binding spectroscopy, which is for nerveagent detection, are presented. The simulations use: calculated estimates of permitivity functions (for the custom sorbent SiFA4H, nerve agent simulant DMMP and molecular structure SiFA4HDMMP); and a model of reflection from multicomponentmultilayer systems, which is based on the scatteringmatrix representation of electromagneticwave propagation. The physical assumptions and approximations underlying these simulations, and modelparameter sensitivity are examined with respect to quantitative prediction of ATR spectra associated with nerveagent detection. Experimentally measured ATR spectra are utilized for qualitative comparison and quantitative adjustment of model parameters.

Structural, Magnetic and Transport Properties of SmBa(x)Sr(1X)Co2O(5+delta) (0.1 ≪= X ≪= 0.5) 

AIP Advances 
2018 
Show abstract »The structural, transport, and magnetic properties of bulk SmBaxSr1xCo2O5+delta samples were investigated as a function of Ba content. At room temperature the magnetization was observed to increase as a function of decreasing Ba composition. As the samples were cooled below room temperature, a ferromagnetic transition was observed for 0.1 <= x <= 0.5 with the Curie temperatures showing a linear dependence on the Bacomposition. Transport measurements showed that resistivity values increased with decreasing temperature indicating a semiconductinglike behavior.

Testing Dynamical System Variables for Reconstruction 

Chaos 
2018 
Show abstract »Analyzing data from dynamical systems often begins with creating a reconstruction of the trajectory based on one or more variables, but not all variables are suitable for reconstructing the trajectory. The concept of nonlinear observability has been investigated as a way to determine if a dynamical system can be reconstructed from one signal or a combination of signals [L. A. Aguirre, IEEE Trans. Educ. 38, 33 (1995); C. Letellier, L. A. Aguirre, and J. Maquet, Phys. Rev. E 71, 066213 (2005); L. A. Aguirre, S. B. Bastos, M. A. Alves, and C. Letellier, Chaos 18, 013123 (2008); L. A. Aguirre and C. Letellier, Phys. Rev. E 83, 066209 (2011); and E. BiancoMartinez, M. S. Baptista, and C. Letellier, Phys. Rev. E 91, 062912 (2015)]; however, nonlinear observability can be difficult to calculate for a high dimensional system. In this work, I compare the results from nonlinear observability to a continuity statistic that indicates the likelihood that there is a continuous function between two sets of multidimensional pointsin this case, two different reconstructions of the same attractor from different signals are simultaneously measured. Without a metric against which to test the ability to reconstruct a system, the predictions of nonlinear observability and continuity are ambiguous. As an additional test on how well different signals can predict the ability to reconstruct a dynamical system, I use the fitting error from training a reservoir computer. Published by AIP Publishing.

Uncovering the Mechanism of the ImpuritySelective Mott Transition in Paramagnetic V2O3 

Physical Review Letters 
2018 
Show abstract »While the phase diagrams of the one and multiorbital Hubbard model have been well studied, the physics of real Mott insulators is often much richer, material dependent, and poorly understood. In the prototype Mott insulator V2O3, chemical pressure was initially believed to explain why the paramagneticmetal to antiferromagneticinsulator transition temperature is lowered by Ti doping while Cr doping strengthens correlations, eventually rendering the hightemperature phase paramagnetic insulating. However, this scenario has been recently shown both experimentally and theoretically to be untenable. Based on full structural optimization, we demonstrate via the charge selfconsistent combination of density functional theory and dynamical meanfield theory that changes in the V2O3 phase diagram are driven by defectinduced local symmetry breakings resulting from dramatically different couplings of Cr and Ti dopants to the host system. This finding emphasizes the high sensitivity of the Mott metalinsulator transition to the local environment and the importance of accurately accounting for the oneelectron Hamiltonian, since correlations crucially respond to it.

Using Reservoir Computers to Distinguish Chaotic Signals 

Physical Review E 
2018 
Show abstract »Several recent papers have shown that reservoir computers are useful for analyzing and predicting dynamical systems. Reservoir computers have also been shown to be useful for various classification problems. In this work, a reservoir computer is used to identify one out of the 19 different Sprott systems. An advantage of reservoir computers for this problem is that no embedding is necessary. Some guidance on choosing the reservoir computer parameters is given. The dependance on number of points, number of reservoir nodes, and noise in identifying the Sprott systems is explored.
2017

A Parametric Model of NIR and SWIR Reflectance Spectra for Dyed Fabrics 

Journal of Electromagnetic Waves and Applications 
2017 
Show abstract »This study describes a parametric model of diffuse reflectance for the purpose of simulating the spectral response of nearinfrared (NIR, 0.70.9m) and shortwave infrared (SWIR, 0.91.7m) absorbing dyes for minimizing NIRSWIR reflectance of dyed fabrics. This model is purely phenomenological, but is optimal with respect to numbers of parameters. This model establishes groundwork for development of a prediction tool, which when given the constituent materials available, will enable rapid optimization of NIR/SWIR band contrast matching of composite systems, (e.g. uniforms and ancillary gear) for a given specification of NIRSWIR reflectance. This model adopts absorption coefficients for NIR/SWIR absorbing dyes whose absorption spectra span the NIR/SWIR spectral range. Military camouflage fabric consisting of 50/50 nylon/cotton blend in a ripstop weave printed with fourcolor digital pattern was used as the test substrate for NIR/SWIR dye application. The results of this study provide validation of the parametric model within reasonable error, for practical applications including simulating NIR/SWIR spectral responses corresponding to fixed dye and dye blend concentrations in prototype camouflage fabrics.

AdsorptionInduced Deformation of Hierarchically Structured Mesoporous Silica Effect of PoreLevel Anisotropy 

Langmuir 
2017 
Show abstract »The goal of this work is to understand adsorptioninduced deformation of hierarchically structured porous silica exhibiting welldefined cylindrical mesopores. For this purpose, we performed an in situ dilatometry measurement on a calcined and sintered monolithic silica sample during the adsorption of N2 at 77 K. To analyze the experimental data, we extended the adsorption stress model to account for the anisotropy of cylindrical mesopores, i.e., we explicitly derived the adsorption stress tensor components in the axial and radial direction of the pore. For quantitative predictions of stresses and strains, we applied the theoretical framework of Derjaguin, Broekhoff, and de Boer for adsorption in mesopores and two mechanical models of silica rods with axially aligned pore channels: an idealized cylindrical tube model, which can be described analytically, and an ordered hexagonal array of cylindrical mesopores, whose mechanical response to adsorption stress was evaluated by 3D finite element calculations. The adsorptioninduced strains predicted by both mechanical models are in good quantitative agreement making the cylindrical tube the preferable model for adsorptioninduced strains due to its simple analytical nature. The theoretical results are compared with the in situ dilatometry data on a hierarchically structured silica monolith composed by a network of mesoporous struts of MCM41 type morphology. Analyzing the experimental adsorption and strain data with the proposed theoretical framework, we find the adsorptioninduced deformation of the monolithic sample being reasonably described by a superposition of axial and radial strains calculated on the mesopore level. The structural and mechanical parameters obtained from the model are in good agreement with expectations from independent measurements and literature, respectively.

An Intrinsic Growth Instability in Isotropic Materials Leads to QuasiTwoDimensional Nanoplatelets 

Nature Materials 
2017 
Show abstract »Colloidal nanoplatelets are atomically flat, quasitwodimensional sheets of semiconductor that can exhibit efficient, spectrally pure fluorescence. Despite intense interest in their properties, the mechanism behind their highly anisotropic shape and precise atomicscale thickness remains unclear, and even counterintuitive for commonly studied nanoplatelets that arise from isotropic crystal structures (such as zincblende CdSe and lead halide perovskites). Here we show that an intrinsic instability in growth kinetics can lead to such highly anisotropic shapes. By combining experimental results on the synthesis of CdSe nanoplatelets with theory predicting enhanced growth on narrow surface facets, we develop a model that explains nanoplatelet formation as well as observed dependencies on time and temperature. Based on standard concepts of volume, surface and edge energies, the resulting growth instability criterion can be directly applied to other crystalline materials. Thus, knowledge of this previously unknown mechanism for controlling shape at the nanoscale can lead to broader libraries of quasitwodimensional materials.

Communication with Unstable Basis Functions 

Chaos Solitons & Fractals 
2017 
Show abstract »Work by Corron et al. [1,2] represented a chaotic signal as a set of basis functions, and built a matched filter for the resulting signal. This paper makes use of basis functions without an underlying chaotic system. Matched filtering is still possible, allowing communication in noisy environments, but the resulting signals can be broad band, which is useful for producing signals that are hard to detect. The receiver design retains the simplicity of Corron et al. [1,2], which is good when weight, power consumption or bandwidth are constraints on the receiver. Published by Elsevier Ltd.

ConstantPressure Nested Sampling with Atomistic Dynamics 

Physical Review E 
2017 
Show abstract »The nested sampling algorithm has been shown to be a general method for calculating the pressuretemperaturecomposition phase diagrams of materials. While the previous implementation used singleparticle Monte Carlo moves, these are inefficient for condensed systems with general interactions where singleparticle moves cannot be evaluated faster than the energy of the whole system. Here we enhance the method by using allparticle moves: either Galilean Monte Carlo or the total enthalpy Hamiltonian Monte Carlo algorithm, introduced in this paper. We show that these algorithms enable the determination of phase transition temperatures with equivalent accuracy to the previous method at 1/N of the cost for an Nparticle system with general interactions, or at equal cost when singleparticle moves can be done in 1/N of the cost of a full Nparticle energy evaluation. We demonstrate this speedup for the freezing and condensation transitions of the LennardJones system and show the utility of the algorithms by calculating the orderdisorder phase transition of a binary LennardJones model alloy, the eutectic of coppergold, the density anomaly of water, and the condensation and solidification of beadspring polymers. The nested sampling method with all three algorithms is implemented in the PYMATNEST software.

Deep Donor State of the Copper Acceptor as a Source of Green Luminescence in ZnO 

Applied Physics Letters 
2017 
Show abstract »Copper impurities have long been linked with green luminescence (GL) in ZnO. Copper is known to introduce an acceptor level close to the conduction band of ZnO, and the GL has conventionally been attributed to transitions involving an excited state which localizes holes on neighboring oxygen atoms. To date, a theoretical description of the optical properties of such deep centers has been difficult to achieve due to the limitations of functionals in the density functional theory. Here, we employ a screened hybrid density functional to calculate the properties of Cu in ZnO. In agreement with the experiment, we find that CuZn features an acceptor level near the conduction band of ZnO. However, we find that CuZn also gives rise to a deep donor level 0.46 eV above the valence band of ZnO; the calculated optical transitions involving this state agree well with the GL observed in ZnO:Cu.

Delamination Growth in PolymerMatrix Fibre Composites and the Use of Fracture Mechanics Data for Material Characterisation and Life Prediction 

Composite Structures 
2017 
Show abstract »The growth of delaminations in polymermatrix fibre composites under cyclicfatigue loading in operational aircraft structures has always been a very important factor which has the potential to significantly affect the servicelife of such structures. The recent introduction by the Federal Aviation Administration (FAA) of a 'slow growth' approach to the certification of composites has further focused attention on the experimental data and the analytical tools needed to assess the growth of delaminations under fatigue loads. Specific attention is given to the test and datareduction procedures required to determine a 'valid' rate of fatigue crack growth (FCG), da/dN, versus the range of the energy releaserate, DG, (or the maximum energy releaserate, GMAx, in a cycle) relationship (a) to characterise and compare different types of composites, and (b) for designing and lifing inservice composite structures. Now, fibrebridging may occur behind the tip of the advancing delamination and may cause very significant retardation of the FCG rate. Such retardation effects cannot usually be avoided when using the Mode I doublecantilever beam test to ascertain experimentally the fatigue behaviour of composites, so that a means of estimating a valid (i.e. ideally a 'retardationfree' or, at least, a very lowretardation) relationship is needed. The present paper presents a novel methodology, that is based on a variant of the HartmanSchijve equation, to ascertain a valid, 'retardationfree', upperbound FCG rate curves. (C) 2017 Elsevier Ltd. All rights reserved.

Dimension from Covariance Matrices 

Chaos 
2017 
Show abstract »We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

DoubleStage Nematic Bond Ordering Above Double Stripe Magnetism: Application to BaTi2Sb2O 

Physical Review B 
2017 
Show abstract »Spindriven nematicity, or the breaking of the pointgroup symmetry of the lattice without longrange magnetic order, is clearly quite important in ironbased superconductors. From a symmetry point of view, nematic order can be described as a coherent locking of spin fluctuations in two interpenetrating Neel sublattices with ensuing nearestneighbor bond order and an absence of static magnetism. Here, we argue that the lowtemperature state of the recently discovered superconductor BaTi2Sb2O is a strong candidate for a more exotic form of spindriven nematic order, in which fluctuations occurring in four Neel sublattices promote both nearestand nextnearestneighbor bond order. We develop a lowenergy field theory of this state and show that it can have, as a function of temperature, up to two separate bondorder phase transitions, namely, one that breaks rotation symmetry and one that breaks reflection and translation symmetries of the lattice. The resulting state has an orthorhombic lattice distortion, an intraunitcell charge density wave, and no longrange magnetic order, all consistent with reported measurements of the lowtemperature phase of BaTi2Sb2O. We then use density functional theory calculations to extract exchange parameters to confirm that the model is applicable to BaTi2Sb2O.