First principles characterization of reversible martensitic transformations

Reversible martensitic transformations (MTs) are the origin of many fascinating phenomena, including the famous shape memory effect. In this work, we present a fully ab initio procedure to characterize MTs in alloys and to assess their reversibility. Specifically, we employ ab initio molecular dynamics data to parametrize a Landau expansion for the free energy of the MT. This analytical expansion makes it possible to determine the stability of the high- and low-temperature phases, to obtain the Ehrenfest order of the MT, and to quantify its free energy barrier and latent heat. We apply our model to the high-temperature shape memory alloy Ti-Ta, for which we observe remarkably small values for the metastability region (the interval of temperatures in which the high-and low-temperature phases are metastable) and for the barrier: these small values are necessary conditions for the reversibility of MTs and distinguish shape memory alloys from other materials

Efficient and accurate determination of lattice-vacancy diffusion coefficients via non equilibrium ab initio molecular dynamics

We revisit the color-diffusion algorithm [P. C. Aeberhard et al., Phys. Rev. Lett. 108, 095901 (2012)] in nonequilibrium ab initio molecular dynamics (NE-AIMD), and propose a simple efficient approach for the estimation of monovacancy jump rates in crystalline solids at temperatures well below melting. Color-diffusion applied to monovacancy migration entails that one lattice atom (colored-atom) is accelerated toward the neighboring defect-site by an external constant force F. Considering bcc molybdenum between 1000 and 2800 K as a model system, NE-AIMD results show that the colored-atom jump rate k_{NE} increases exponentially with the force intensity F, up to F values far beyond the linear-fitting regime employed previously. Using a simple model, we derive an analytical expression which reproduces the observed k_{NE}(F) dependence on F. Equilibrium rates extrapolated by NE-AIMD results are in excellent agreement with those of unconstrained dynamics. The gain in computational efficiency achieved with our approach increases rapidly with decreasing temperatures, and reaches a factor of four orders of magnitude at the lowest temperature considered in the present study

Indexing, Unchained

Improved toughness is one of the central goals in the development of wear-resistant coatings. Previous studies of toughness in transition metal nitride alloys have addressed the effects of chemical composition in these compounds. Herein, we use density functional theory to study the effects of various metal sublattice configurations, ranging from fully ordered to fully disordered, on the mechanical properties of VM2N and TiM2N (M2 = W, Mo) ternary alloys. Results show that all alloys display high incompressibility, indicating strong M-N bonds. Disordered atomic arrangements yield lower values of bulk moduli and C11 elastic constants, as well as higher values of C44 elastic constants, compared to ordered structures. We attribute the low C44 values of ordered structures to the formation of fully-bonding states perpendicular to the applied stress. We find that the ductility of these compounds is primarily an effect of the increased valence electron concentration induced upon alloying

Machine-learning potentials for nanoscale simulations of deformation and fracture: example of TiB2_2 ceramic

Machine-learning interatomic potentials (MLIPs) offer a powerful avenue for simulations beyond length and timescales of ab initio methods. Their development for investigation of mechanical properties and fracture, however, is far from trivial since extended defects -- governing plasticity and crack nucleation in most materials -- are too large to be included in the training set. Using TiB$_2$ as a model ceramic material, we propose a strategy for fitting MLIPs suitable to simulate mechanical response of monocrystals until fracture. Our MLIP accurately reproduces ab initio stresses and failure mechanisms during room-temperature uniaxial tensile deformation of TiB$_2$ at the atomic scale ($\approx{10}^3$ atoms). More realistic tensile tests (low strain rate, Poisson's contraction) at the nanoscale ($\approx{10}^4$--10$^6$ atoms) require MLIP up-fitting, i.e. learning from additional ab initio configurations. Consequently, we elucidate trends in theoretical strength, toughness, and crack initiation patterns under different loading directions. To identify useful environments for further up-fitting, i.e., making the MLIP applicable to a wider spectrum of simulations, we asses transferability to other deformation conditions and phases not explicitly trained on

MOCVD of AlN on epitaxial graphene at extreme temperatures

The initial stages of metal organic chemical vapor deposition (MOCVD) of AlN on epitaxial graphene at temperatures in excess of 1200 °C have been rationalized. The use of epitaxial graphene, in conjunction with high deposition temperatures, can deliver on the realization of nanometer thin AlN whose material quality is characterized by the appearance of luminescent centers with narrow spectral emission at room temperature. It has been elaborated, based on our previous comprehensive ab initio molecular dynamics simulations, that the impact of graphene on AlN growth consists in the way it promotes dissociation of the trimethylaluminum, (CH3)3Al, precursor with subsequent formation of Al adatoms during the initial stages of the deposition process. The high deposition temperatures ensure adequate surface diffusion of the Al adatoms which is an essential factor in material quality enhancement. The role of graphene in intervening with the dissociation of another precursor, trimethylgallium, (CH3)3Ga, has accordingly been speculated by presenting a case of propagation of ultrathin GaN of semiconductor quality. A lower deposition temperature of 1100 °C in this case has better preserved the structural integrity of epitaxial graphene. Breakage and decomposition of the graphene layers has been deduced in the case of AlN deposition at temperatures in excess of 1200 °C

Direct-acting antivirals and hepatocellular carcinoma in chronic hepatitis C: A few lights and many shadows

With the introduction of direct-acting antiviral agents (DAA), the rate of sustained virological response (SVR) in the treatment of hepatitis C virus (HCV) has radically improved to over 95%. Robust scientific evidence supports a beneficial role of SVR after interferon therapy in the progression of cirrhosis, resulting in a decreased incidence of hepatocellular carcinoma (HCC). However, a debate on the impact of DAAs on the development of HCC is ongoing. This review aimed to analyse the scientific literature regarding the risk of HCC in terms of its recurrence and occurrence after the use of DAAs to eradicate HCV infection. Among 11 studies examining HCC occurrence, the de novo incidence rate ranged from 0 to 7.4% (maximum follow-up: 18 mo). Among 18 studies regarding HCC recurrence, the rate ranged from 0 to 54.4% (maximum "not well-defined" followup: 32 mo). This review highlights the major difficulties in interpreting data and reconciling the results of the included studies. These difficulties include heterogeneous cohorts, potential misclassifications of HCC prior to DAA therapy, the absence of an adequate control group, short follow-up times and different kinds of follow-up. Moreover, no clinical feature-based scoring system accounts for the molecular characteristics and pathobiology of the tumours. Nonetheless, this review does not suggest that there is a higher rate of de novo HCC occurrence or recurrence after DAA therapy in patients with previous HCV infection. \ua9 2018 The Author(s). Published by Baishideng Publishing Group Inc. All rights reserved

Transition Metal Nitrides : Alloy Design and Surface Transport Properties using Ab-initio and Classical Computational Methods

Enhanced toughness in brittle ceramic materials, such as transition metal nitrides (TMN), is achieved by optimizing the occupancy of shear-sensitive metallic electronic-states. This is the major result of my theoretical research, aimed to solve an inherent long-standing problem for hard ceramic protective coatings: brittleness. High hardness, in combination with high toughness, is thus one of the most desired mechanical/physical properties in modern coatings. A significant part of this PhD Thesis is dedicated to the density functional theory (DFT) calculations carried out to understand the electronic origins of ductility, and to predict novel TMN alloys with optimal hardness/toughness ratios. Importantly, one of the TMN alloys identified in my theoretical work has subsequently been synthesized in the laboratory and exhibits the predicted properties. The second part of this Thesis concerns molecular dynamics (MD) simulations of Ti, N, and TiNx adspecies diffusion on TiN surfaces, chosen as a model material, to provide unprecedented detail of critical atomic-scale transport processes, which dictate the growth modes of TMN thin films. Even the most advanced experimental techniques cannot provide sufficient information on the kinetics and dynamics of picosecond atomistic processes, which affect thin films nucleation and growth. Information on these phenomena would allow experimentalists to better understand the role of deposition conditions and fine tune thin films growth modes, to tailor coatings properties to the requirements of different applications. The MD simulations discussed in the second part of this PhD Thesis, predict that Ti adatoms and TiN2 admolecules are the most mobile species on TiN(001) terraces. Moreover, these adspecies are rapidly incorporated at island descending steps, and primarily contribute to layer-by-layer growth. In contrast, TiN3 tetramers are found to be essentially stationary on both TiN(001) terraces and islands, and thus constitute the critical nuclei for three-dimensional growth

Transition Metal Nitrides : Alloy Design and Surface Transport Properties using Ab-initio and Classical Computational Methods

Enhanced toughness in brittle ceramic materials, such as transition metal nitrides (TMN), is achieved by optimizing the occupancy of shear-sensitive metallic electronic-states. This is the major result of my theoretical research, aimed to solve an inherent long-standing problem for hard ceramic protective coatings: brittleness. High hardness, in combination with high toughness, is thus one of the most desired mechanical/physical properties in modern coatings. A significant part of this PhD Thesis is dedicated to the density functional theory (DFT) calculations carried out to understand the electronic origins of ductility, and to predict novel TMN alloys with optimal hardness/toughness ratios. Importantly, one of the TMN alloys identified in my theoretical work has subsequently been synthesized in the laboratory and exhibits the predicted properties. The second part of this Thesis concerns molecular dynamics (MD) simulations of Ti, N, and TiNx adspecies diffusion on TiN surfaces, chosen as a model material, to provide unprecedented detail of critical atomic-scale transport processes, which dictate the growth modes of TMN thin films. Even the most advanced experimental techniques cannot provide sufficient information on the kinetics and dynamics of picosecond atomistic processes, which affect thin films nucleation and growth. Information on these phenomena would allow experimentalists to better understand the role of deposition conditions and fine tune thin films growth modes, to tailor coatings properties to the requirements of different applications. The MD simulations discussed in the second part of this PhD Thesis, predict that Ti adatoms and TiN2 admolecules are the most mobile species on TiN(001) terraces. Moreover, these adspecies are rapidly incorporated at island descending steps, and primarily contribute to layer-by-layer growth. In contrast, TiN3 tetramers are found to be essentially stationary on both TiN(001) terraces and islands, and thus constitute the critical nuclei for three-dimensional growth