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Cristian V. Ciobanu

Publications and source records attributed to Cristian V. Ciobanu.

15 recordsLinked to original sources
arXiv2024

Direct observation of structural phase transformations during continuous phosphorus deposition on Cu(111)

Blue phosphorene -- two-dimensional, hexagonal-structured, semiconducting phosphorus -- has gained attention as it is considered easier to synthesize on metal surfaces than its allotrope, black phosphorene. Recent studies report different structures of phosphorene, for example, on Cu(111), but the underlying mechanisms of their formation are not known. Here, using a combination of in situ ultrahigh vacuum low-energy electron microscopy and in vacuo scanning tunneling microscopy, we determine the time-evolution of the surface structure and morphology during the deposition of phosphorus on single-crystalline Cu(111). We find that during early stages of deposition, phosphorus intermixes with Cu, resulting in copper phosphide structures. With increasing surface concentration of phosphorus, the phosphide phase disappears and a blue phosphorene layer forms, followed by self-assembly of highly ordered phosphorus clusters that eventually grow into multilayer islands. We attribute the unexpected transformation of stable phosphide to a phosphorene layer, and the previously unreported multilayer growth, to the presence of a large concentration of P2 dimers on the surface. Our results constitute direct evidence for a new growth mode leading to a phosphorene layer via an intermediary phase, which could underpin the growth of other 2D materials on strongly interacting substrates.

cond-mat.mtrl-sci↗
arXiv2019

Interfacial Energy of Copper Clusters in Fe-Si-B-Nb-Cu alloys

Using a combination of numerical simulations and atom-probe tomography experiments, we determine the interfacial energy of Cu nanocrystals precipitated within the amorphous matrix of FINEMET (molar composition Fe72.89Si16.21B6.90Nb3Cu1). Specifically, we use the Langer-Schwartz model implemented in the software Thermocalc to carry out parametric simulations of growth and coarsening of Cu clusters for different interface energies. We have carried out atom-probe tomography (APT) experiments to determine the interface energy as the value for which the simulated particle size distribution best matches the experimental data. This combination of APT and precipitation modeling can be applied to other nanocrystals precipitated within amorphous matrices.

cond-mat.mtrl-sci↗
arXiv2018

Combined Machine Learning and CALPHAD Approach for Discovering Processing-Structure Relationships in Soft Magnetic Alloys

We aim to investigate relationships between select processing parameters or inputs (composition, temperature, annealing time) and two structural parameters, specifically, the mean radius and volume fraction of the Fe$_3$Si nanocrystals. To this end, we have deviced a combined CALPHAD and machine learning approach that led to well-calibrated metamodels able to predict structural parameters quickly and accurately for any desired inputs. In order to generate data for the mean radius and volume fraction of Fe$_3$Si nanocrystals, we have used a precipitation model based in the software Thermocalc to perform annealing simulations at a set of temperatures (490-550~\degree C) and for varying Fe and Si concentrations (Fe$_{72.89 +x}$Si$_{16.21-x}$B$_{6.90}$Nb$_{3}$Cu$_{1}$, $-3\leq x \leq 3$ atomic \%). Thereafter, we used the data to develop metamodels for the mean radius and volume fraction via the \emph{k}-Nearest Neighbour algorithm. The metamodels are shown to reproduce closely the trends obtained from the precipitation model over the entire annealing timescale. Our further analysis via parallel coordinate charts shows the effect of composition, temperature, and annealing time, and helps identify combinations thereof that lead to the desired mean radius and volume fraction for the nanocrystalline phase. This approach utilizes experimental (thermodynamic and kinetic) databases from the CALPHAD approach so as to capture the physics of nucleation and growth, while the machine learning algorithm provides the robustness needed to analyze the effects of processing parameters for this complex precipitation problem. This work contributes to understanding the linkages between processing parameters and desired microstructural characteristics (crystal size and volume fraction) responsible for achieving targeted properties, and illustrates ways to reduce the time from alloy discovery to deployment.

cond-mat.mtrl-sci↗
arXiv2018

Large Piezoelectric Response of van der Waals Layered Solids

The bulk piezoelectric response, as measured by the piezoelectric modulus tensor (\textbf{d}), is determined by a combination of charge redistribution due to strain and the amount of strain produced by the application of stress (stiffness). Motivated by the notion that less stiff materials could exhibit large piezoelectric responses, herein we investigate the piezoelectric modulus of van der Waals-bonded quasi-2D ionic compounds using first-principles calculations. From a pool of 869 known binary and ternary quasi-2D materials, we have identified 135 non-centrosymmetric crystals of which 48 systems are found to have \textbf{d} components larger than the longitudinal piezoelectric modulus of AlN (a common piezoelectric for resonators), and three systems with the response greater than that of PbTiO$_3$, which is among the materials with largest known piezoelectric modulus. None of the identified materials have previously been considered for piezoelectric applications. Furthermore, we find that large \textbf{d} components always couple to the deformations (shearing or axial) of van der Waals "gaps" between the layers and are indeed enabled by the weak intra-layer interactions.

cond-mat.mtrl-sci↗
arXiv2018

Pressure-Induced Phase Transformation in $β$-Eucryptite: an X-Ray Diffraction and Density Functional Theory Study

Certain alumino-silicates display exotic properties enabled by their framework structure made of corner-sharing tetrahedral rigid units. Using \textit{in situ} diamond-anvil cell x-ray diffraction (XRD), we study the pressure-induced transformation of $β$ eucryptite, a prototypical alumino-silicate. $β$ eucryptite undergoes a phase transformation at moderate pressures, but the atomic structure of the new phase has not yet been reported. Based on density functional theory stability studies and Rietveld analysis of XRD patterns, we find that the pressure-stabilized phase belongs to the Pna2$_1$ space group. Furthermore, we discover two other possible pressure-stabilized polymorphs, P1c1 and Pca2$_1$.

cond-mat.mtrl-sci↗
arXiv2018

Enhanced piezoelectric response of AlN via CrN alloying

Since AlN has emerged as an important piezoelectric material for a wide variety of applications, efforts have been made to increase its piezoelectric response via alloying with transition metals that can substitute for Al in the wurtzite lattice. Herein, we report density functional theory calculations of structure and properties of the Cr-AlN system for Cr concentrations ranging past the wurtzite-rocksalt transition point. By studying the different contributions to the longitudinal piezoelectric coefficient, we propose that the physical origin of the enhanced piezoelectricity in Cr$_x$Al$_{1-x}$N alloys is the increase of the internal parameter $u$ of the wurtzite structure upon substitution of Al with the larger Cr ions. Among a set of wurtzite-structured materials, we have found that Cr-AlN has the most sensitive piezoelectric coefficient with respect to alloying concentration. Based on these results, we propose that Cr-AlN is a viable piezoelectric material whose properties can be tuned via Cr composition; we support this proposal by combinatorial synthesis experiments, which show that Cr can be incorporated in the AlN lattice up to 30\% before a detectable transition to rocksalt occurs. At this Cr content, the piezoelectric modulus $d_{33}$ is approximately four times larger than that of pure AlN. This finding, combined with the relative ease of synthesis, may propel Cr-AlN as the prime piezoelectric material for applications such as resonators and acoustic wave generators.

cond-mat.mtrl-sci↗
arXiv2018

Metastable Phase Diagram and Precipitation Kinetics of Magnetic Nanocrystals in FINEMET Alloys

Research over the years has shown that the formation of the Fe$_3$Si phase in FINEMET (Fe-Si-Nb-B-Cu) alloys leads to superior soft magnetic properties. In this work, we use a CALPHAD approach to derive Fe-Si phase diagrams to identify the composition-temperature domain where the Fe$_3$Si phase can be stabilized. Thereafter, we have developed a precipitation model capable of simulating the nucleation and growth of Fe$_3$Si nanocrystals via Langer-Schwartz theory. For optimum magnetic properties, prior work suggests that it is desirable to precipitate Fe$_3$Si nanocrystals with 10-15 nm diameter and with the crystalline volume fraction of about 70 \%. Based on our parameterized model, we simulated the nucleation and growth of Fe$_3$Si nanocrystals by isothermal annealing of Fe$_{72.89}$Si$_{16.21}$B$_{6.90}$Nb$_{3}$Cu$_{1}$ (composition in atomic \%). In numerical experiments, the alloys were annealed at a series of temperatures from 490 to 550 \degree C for two hours to study the effect of holding time on mean radius, volume fraction, size distribution, nucleation rate, number density, and driving force for the growth of Fe$_3$Si nanocrystals. With increasing annealing temperature, the mean radius of Fe$_3$Si nanocrystals increases, while the volume fraction decreases. We have also studied the effect of composition variations on the nucleation and growth of Fe$_3$Si nanocrystals. As Fe content decreases, it is possible to achieve the desired mean radius and volume fraction within one hour holding time. The CALPHAD approach presented here can provide efficient exploration of the nanocrystalline morphology for most FINEMET systems, for cases in which the optimization of one or more material properties or process variables are desired.

cond-mat.mtrl-sci↗
arXiv2017

Tuning the piezoelectric and mechanical properties of the AlN system via alloying with YN and BN

Recent advances in microelectromechanical systems often require multifunctional materials, which are designed so as to optimize more than one property. Using density functional theory calculations for alloyed nitride systems, we illustrate how co-alloying a piezoelectric material (AlN) with different nitrides helps tune both its piezoelectric and mechanical properties simultaneously. Wurtzite AlN-YN alloys display increased piezoelectric response with YN concentration, accompanied by mechanical softening along the crystallographic c direction. Both effects increase the electromechanical coupling coefficients relevant for transducers and actuators. Resonator applications, however, require superior stiffness, thus leading to the need to decouple the increased piezoelectric response from a softened lattice. We show that co-alloying of AlN with YN and BN results in improved elastic properties while retaining most of the piezoelectric enhancements from YN alloying. This finding may lead to new avenues for tuning the design properties of piezoelectrics through composition-property maps. Keywords: piezoelectricity, electromechanical coupling, density functional theory, co-alloying

cond-mat.mtrl-sci↗
arXiv2017

Thermal regimes of Li-ion conductivity in beta-eucryptite

While it is well established that ionic conduction in lithium aluminosilicates proceeds via hopping of Li ions, the nature of the various hoping-based mechanisms in different temperature regimes has not been fully elucidated. The difficulties associated with investigating the conduction have to do with the presence of grains and grain boundaries of different orientations in these usually polycrystalline materials. Herein, we use electrochemical impedance spectroscopy (EIS) to investigate the ion conduction mechanisms in -eucryptite, which is a prototypical lithium aluminosilicate. In the absence of significant structural transitions in grain boundaries, we have found that there are three conduction regimes for the one-dimensional ionic motion along the c axis channels in the grains, and determined the activation energies for each of these temperature regimes. Activation energies computed from molecular statics calculations of the potential energy landscape encountered by Li ions suggest that at temperatures below 440 °C conduction proceeds via cooperative or correlated motion, in agreement with established literature. Between 440 °C and 500°C, the activation barriers extracted from EIS measurements are large and consistent with those from atomistic calculations for uncorrelated Li ion hopping. Above 500 °C the activation barriers decrease significantly, which indicates that after the transition to the Li-disordered phase of -eucryptite, the Li ion motion largely regains the correlated character.

cond-mat.mtrl-sci↗
arXiv2011

Reactive force field for lithium-aluminum silicates with applications to eucryptite phases

We have parameterized a reactive force field (ReaxFF) for lithium aluminum silicates using density functional theory (DFT) calculations of structural properties of a number of bulk phase oxides, silicates, and aluminates, as well as of several representative clusters. The force field parameters optimized in this study were found to predict lattice parameters and heats of formation of selected condensed phases in excellent agreement with previous DFT calculations and with experiments. We have used the newly developed force-field to study the eucryptite phases in terms of their thermodynamic stability and their elastic properties. We have found that (a) these ReaxFF parameters predict the correct order of stability of the three crystalline polymorphs of eucryptite, α, β, and γ, and (b) that upon indentation, a new phase appears at applied pressures \geq 7 GPa. The high pressure phase obtained upon indentation is amorphous, as illustrated by the radial distribution functions calculated for different pairs of elements. In terms of elastic properties analysis, we have determined the elements of the stiffness tensor for α- and β- eucryptite at the level of ReaxFF, and discussed the elastic anisotropy of these two polymorphs. Polycrystalline average properties of these eucryptite phases are also reported to serve as ReaxFF predictions of their elastic moduli (in the case of α-eucryptite), or as tests against values known from experiments or DFT calculations (β- eucrypite). The ReaxFF potential reported here can also describe well single-species systems (e.g., Li-metal, Al-metal, and condensed phases of silicon), which makes it suitable for investigating struc- ture and properties of suboxides, atomic-scale mechanisms responsible for phase transformations, as well as oxidation-reduction reactions.

cond-mat.mtrl-sci↗
arXiv2010

Bandgap opening in metallic carbon nanotubes due to silicon impurities

Controlling the bandgap of carbon nanostructures is key to the development and mainstream application of carbon-based nanoelectronic devices. We report density functional theory calculations of the effect of silicon impurities on the electronic properties of carbon nanotubes (CNTs). We have found that Si adatoms open up a bandgap in intrinsically metallic CNTs even when the linear density of Si atoms is low enough that they do not create a bonded adatom chain. The bandgap opened in metallic CNTs can range between 0.10 eV and 0.47 eV, depending on adsorption site, linear density of Si adatoms, and CNT chirality.

cond-mat.mtrl-sci↗
arXiv2005

The stability of strained H:Si(105) and H:Ge(105) surfaces

We report atomic scale studies of the effect of applied strain and hydrogen environment on the reconstructions of the (105) Si and Ge surfaces. Surface energy calculations for monohydride-terminated (001) and (105) reconstructions reveal that the recently established single-height rebonded model is unstable not only with respect to (001), but also in comparison to other monohydride (105) structures. This finding persists for both Si and Ge, for applied biaxial strains from -4% to 4%, and for nearly the entire relevant domain of the chemical potential of hydrogen, thus providing an explanation for the recently observed H-induced destabilization of the Ge(105) surface.

cond-mat.mtrl-sci↗
arXiv2004

Reconstruction of silicon surfaces: a stochastic optimization problem

Over the last two decades, scanning tunnelling microscopy (STM) has become one of the most important ways to investigate the structure of crystal surfaces. STM has helped achieve remarkable successes in surface science such as finding the atomic structure of Si(111) and Si(001). For high-index Si surfaces the information about the local density of states obtained by scanning does not translate directly into knowledge about the positions of atoms at the surface. A commonly accepted strategy for identifying the atomic structure is to propose several possible models and analyze their corresponding {\em simulated} STM images for a match with the experimental ones. However, the number of good candidates for the lowest-energy structure is very large for high-index surfaces, and heuristic approaches are not likely to cover all the relevant structural models. In this article, we take the view that finding the atomic structure of a surface is a problem of stochastic optimization, and we address it as such. We design a general technique for predicting the reconstruction of silicon surfaces with arbitrary orientation, which is based on parallel-tempering Monte Carlo simulations combined with an exponential cooling. The advantages of the method are illustrated using the Si(105) surface as example, with two main results: (a) the correct single-step rebonded structure [e.g., Fujikawa {\em et al.}, Phys. Rev. Lett. 88, 176101 (2002)] is obtained even when starting from the paired-dimer model [Mo {\em et al.}, Phys. Rev. Lett. 65, 1020 (1990)] that was assumed to be correct for many years, and (b) we have found several double-step reconstructions that have lower surface energies than any previously proposed double-step models.

cond-mat.mtrl-sci↗
arXiv2003

The incomplete beta function law for parallel tempering sampling of classical canonical systems

We show that the acceptance probability for swaps in the parallel tempering Monte Carlo method for classical canonical systems is given by a universal function that depends on the average statistical fluctuations of the potential and on the ratio of the temperatures. The law, called the incomplete beta function law, is valid in the limit that the two temperatures involved in swaps are close to one another. An empirical version of the law, which involves the heat capacity of the system, is developed and tested on a Lennard-Jones cluster. We argue that the best initial guess for the distribution of intermediate temperatures for parallel tempering is a geometric progression and we also propose a technique for the computation of optimal temperature schedules. Finally, we demonstrate that the swap efficiency of the parallel tempering method for condensed-phase systems decreases naturally to zero at least as fast as the inverse square root of the dimensionality of the physical system.

physics.chem-ph↗