arXiv subjects

Haiyang Niu

Publications and source records attributed to Haiyang Niu.

17 recordsLinked to original sources

arXiv2024

Layer-by-layer phase transformation in Ti$_3$O$_5$ revealed by machine learning molecular dynamics simulations

Reconstructive phase transitions involving breaking and reconstruction of primary chemical bonds are ubiquitous and important for many technological applications. In contrast to displacive phase transitions, the dynamics of reconstructive phase transitions are usually slow due to the large energy barrier. Nevertheless, the reconstructive phase transformation from $β$- to $λ$-Ti$_3$O$_5$ exhibits an ultrafast and reversible behavior. Despite extensive studies, the underlying microscopic mechanism remains unclear. Here, we discover a kinetically favorable in-plane nucleated layer-by-layer transformation mechanism through metadynamics and large-scale molecular dynamics simulations. This is enabled by developing an efficient machine learning potential with near first-principles accuracy through an on-the-fly active learning method and an advanced sampling technique. Our results reveal that the $β$-$λ$ phase transformation initiates with the formation of two-dimensional nuclei in the $ab$-plane and then proceeds layer-by-layer through a multistep barrier-lowering kinetic process via intermediate metastable phases. Our work not only provides important insight into the ultrafast and reversible nature of the $β$-$λ$ transition, but also presents useful strategies and methods for tackling other complex structural phase transitions.

cond-mat.mtrl-sci↗

arXiv2023

Hardness and fracture toughness models by symbolic regression

Superhard materials with good fracture toughness have found wide industrial applications, which necessitates the development of accurate hardness and fracture toughness models for efficient materials design. Although several macroscopic models have been proposed, they are mostly semiempirical based on prior knowledge or assumptions, and obtained by fitting limited experimental data. Here, through an unbiased and explanatory symbolic regression technique, we built a macroscopic hardness model and fracture toughness model, which only require shear and bulk moduli as inputs. The developed hardness model was trained on an extended dataset, which not only includes cubic systems, but also contains non-cubic systems with anisotropic elastic properties. The obtained models turned out to be simple, accurate, and transferable. Moreover, we assessed the performance of three popular deep learning models for predicting bulk and shear moduli, and found that the crystal graph convolutional neural network and crystal explainable property predictor perform almost equally well, both better than the atomistic line graph neural network. By combining the machine-learned bulk and shear moduli with the hardness and fracture toughness prediction models, potential superhard materials with good fracture toughness can be efficiently screened out through high-throughput calculations.

cond-mat.mtrl-sci↗

arXiv2023

Unlocking the Structural Mystery of Vaterite CaCO3

Calcium carbonate (CaCO3), the most abundant biogenic mineral on earth, plays a crucial role in various fields. Of the four polymorphs, calcite, aragonite, vaterite, and amorphous CaCO3, vaterite is the most enigmatic one due to an ongoing debate regarding its structure that has persisted for nearly a century. In this work, based on systematic transmission electron microscopy characterizations, elaborate crystallographic analysis and machine learning aided molecular dynamics simulations with ab initio accuracy, we reveal that vaterite can be regarded as a polytypic structure. The basic phase is a monoclinic lattice possessing pseudohexagonal symmetry. Direct imaging and atomic-scale simulations provide evidence that a single grain of vaterite can have three orientation variants. Additionally, we find that vaterite undergoes a second-order phase transition. These atomic scale insights provide a comprehensive understanding of the structure of vaterite and offer new perspectives on the biomineralization process of calcium carbonate.

cond-mat.mtrl-sci↗

arXiv2023

Ab initio investigation of the crystallization mechanism of cadmium selenide

Cadmium selenide (CdSe) is an inorganic semiconductor with unique optical and electronic properties that made it useful in various applications, including solar cells, light-emitting diodes, and biofluorescent tagging. In order to synthesize high-quality crystals and subsequently integrate them into devices, it is crucial to understand the atomic scale crystallization mechanism of CdSe. Unfortunately, such studies are still absent in the literature.To overcome this limitation, we employed an enhanced sampling-accelerated active learning approach to construct a deep neural potential with ab initio accuracy for studying the crystallization of CdSe.Our brute-force molecular dynamics simulations revealed that a spherical-like nucleus formed spontaneously and stochastically, resulting in a stacking disordered structure where the competition between hexagonal wurtzite and cubic zinc blende polymorphs is temperature-dependent. We found that pure hexagonal crystal can only be obtained approximately above 1430 K, which is 35 K below its melting temperature. We observed that the solidification dynamics of Cd and Se atoms were distinct due to their different diffusion coefficients. The solidification process was initiated by lower mobile Se atoms forming tetrahedral frameworks, followed by Cd atoms occupying these tetrahedral centers and settling down until the third-shell neighbor of Se atoms sited on their lattice positions. Therefore, the medium-range ordering of Se atoms governs the crystallization process of CdSe. Our findings indicate that understanding the complex dynamical process is the key to comprehending the crystallization mechanism of compounds like CdSe, and can shed lights in the synthesis of high-quality crystals.

cond-mat.mtrl-sci↗

arXiv2023

Imperfectly coordinated water molecules pave the way for homogeneous ice nucleation

Water freezing is ubiquitous on Earth, affecting many areas from biology to climate science and aviation technology. Probing the atomic structure in the homogeneous ice nucleation process from scratch is of great value but still experimentally unachievable. Theoretical simulations have found that ice originates from the low-mobile region with increasing abundance and persistence of tetrahedrally coordinated water molecules. However, a detailed microscopic picture of how the disordered hydrogen-bond network rearranges itself into an ordered network is still unclear. In this work, we use a deep neural network (DNN) model to "learn" the interatomic potential energy from quantum mechanical data, thereby allowing for large-scale and long molecular dynamics (MD) simulations with ab initio accuracy. The nucleation mechanism and dynamics at atomic resolution, represented by a total of 36 $μ$s-long MD trajectories, are deeply affected by the structural and dynamical heterogeneity in supercooled water. We find that imperfectly coordinated (IC) water molecules with high mobility pave the way for hydrogen-bond network rearrangement, leading to the growth or shrinkage of the ice nucleus. The hydrogen-bond network formed by perfectly coordinated (PC) molecules stabilizes the nucleus, thus preventing it from vanishing and growing. Consequently, ice is born through competition and cooperation between IC and PC molecules. We anticipate that our picture of the microscopic mechanism of ice nucleation will provide new insights into many properties of water and other relevant materials.

cond-mat.mtrl-sci↗

arXiv2019

Homogeneous nucleation of ice

Ice nucleation is a process of great relevance in physics, chemistry, technology and environmental sciences, much theoretical and experimental efforts have been devoted to its understanding, but still it remains a topic of intense research. We shed light on this phenomenon by performing atomistic based simulations. Using metadynamics and a carefully designed set of collective variables, reversible transitions between water and ice are able to be simulated. We find that water freezes into a stacking disordered structure with the all-atom TIP4P/Ice model, and the features of the critical nucleus of nucleation at the microscopic level are revealed. Our results are in agreement with recent experimental and other theoretical works and confirm that nucleation is preceded by a large increase in tetrahedrally coordinated water molecules.

cond-mat.soft↗

arXiv2018

Combining Metadynamics and Integrated Tempering Sampling

The simulation of rare events is one of the key problems in atomistic simulations. Towards its solution a plethora of methods have been proposed. Here we combine two such methods metadynamics and inte-grated tempering sampling. In metadynamics the fluctuations of a carefully chosen collective variable are amplified, while in integrated tempering sampling the system is pushed to visit an approximately uniform interval of energies and allows exploring a range of temperatures in a single run. We describe our ap-proach and apply it to the two prototypical systems a SN2 chemical reaction and to the freezing of silica. The combination of metadynamics and integrated tempering sampling leads to a powerful method. In par-ticular in the case of silica we have measured more than one order of magnitude acceleration.

physics.chem-ph↗

arXiv2018

Finding Efficient Collective Variables: The Case of Crystallization

Several enhanced sampling methods such as umbrella sampling or metadynamics rely on the identification of an appropriate set of collective variables. Recently two methods have been proposed to alleviate the task of determining efficient collective variables. One is based on linear discriminant analysis, the other on a variational approach to conformational dynamics, and uses time-lagged independent component analysis. In this paper, we compare the performance of these two approaches in the study of the homogeneous crystallization of two simple metals. We focus on Na and Al and search for the most efficient collective variables that can be expressed as a linear combination of X-ray diffraction peak intensities. We find that the performances of the two methods are very similar. However, the method based on linear discriminant analysis, in its harmonic version, is to be preferred because it is simpler and much less computationally demanding.

physics.comp-ph↗

arXiv2018

Simple and accurate model of fracture toughness of solids

Fracture toughness $K_{IC}$ plays an important role in materials design. Along with numerous experimental methods to measure fracture toughness of materials, its understanding and theoretical prediction is very important. However, theoretical prediction of fracture toughness is challenging. By investigating the correlation between fracture toughness and elastic properties of materials, we have constructed a fracture toughness model for covalent and ionic crystals. Furthermore, by introducing an enhancement factor, which is determined by the density of states at the Fermi level and atomic electronegativities, we have constructed a universal model of fracture toughness for covalent and ionic crystals, metals and intermetallics. The predicted fracture toughnesses are in good agreement with experimental values for a series of materials. All the parameters in the proposed model of fracture toughness can be obtained from first-principles calculations, which makes it suitable for practical applications.

cond-mat.mtrl-sci↗

arXiv2016

Diverse Chemistry of Stable Hydronitrogens, and Implications for Planetary and Materials Sciences

Nitrogen hydrides, including ammonia (NH3), hydrazine (N2H4), hydrazoic acid (HN3) and etc, are compounds of great fundamental and applied importance. Their high-pressure behavior is important because of their abundance in giant planets and because of the hopes of discoverying high-energy-density materials. Here, we have performed a systematic investi- gation on the structural stability of N-H system in a pressure range up to 800 GPa through evolutionary structure prediction simulations. Surprisingly, we found that high pressure stabilizes a series of previously unreported compounds with peculiar structural and electronic properties, such as the N4H, N3H, N2H and NH phases composed of nitrogen backbones, the N9H4 phase containing two dimensional metallic nitrogen planes and novel N8H, NH2, N3H7, NH4 and NH5 molecular phases. Another surprise is that NH3 becomes thermodynamically unstable above ~460 GPa. We found that high-pressure chemistry is much more diverse that hydrocarbon chemistry at normal conditions, leading to expectations that N-H-O and N-H-O-S systems under pressure are likely to possess richer chemistry than the known organic chemistry. This, in turn, opens a possibility of nitrogen-based life at high pressure. The predicted phase diagram of the N-H system also provides a reference for synthesis of high-energy-density materials.

cond-mat.mtrl-sci↗

arXiv2015

Prediction of novel stable compounds in the Mg-Si-O system under exoplanet pressures

The Mg-Si-O system is the major Earth and rocky planet-forming system. Here, through quantum variable-composition evolutionary structure explorations, we have discovered several unexpected stable binary and ternary compounds in the Mg-Si-O system. Besides the well-known SiO2 phases, we have found two extraordinary silicon oxides, SiO3 and SiO, which become stable at pressures above 0.51 TPa and 1.89 TPa, respectively. In the Mg-O system, we have found one new compound, MgO3, which becomes stable at 0.89 TPa. We find that not only the (MgO)x(SiO2)y compounds, but also two (MgO3)x(SiO3)y compounds, MgSi3O12 and MgSiO6, have stability fields above 2.41 TPa and 2.95 TPa, respectively. The highly oxidized MgSi3O12 can form in deep mantles of mega-Earths with masses above 20 M+ (M+:Earth's mass). Furthermore, the dissociation pathways of pPv-MgSiO3 are also clarified, and found to be different at low and high temperatures. The low-temperature pathway is MgSiO3 -> Mg2SiO4 + MgSi2O5 -> SiO2 + Mg2SiO4 -> MgO + SiO2, while the high-temperature pathway is MgSiO3 -> Mg2SiO4 + MgSi2O5 -> MgO + MgSi2O5 -> MgO + SiO2. Present results are relevant for models of the internal structure of giant exoplanets, and for understanding the high-pressure behavior of materials.

physics.geo-ph↗

arXiv2015

Novel phase of beryllium fluoride at high pressure

A previously unknown thermodynamically stable high-pressure phase of BeF$_{2}$ has been predicted using the evolutionary algorithm USPEX. This phase occurs in the pressure range 18-27 GPa. Its structure has $C2/c$ space group symmetry and contains 18 atoms in the primitive unit cell. Given the analogy between BeF$_{2}$ and SiO$_{2}$, silica phases have been investigated as well, but the new phase has not been observed to be thermodynamically stable for this system. However, it is found to be metastable and to have comparable energy to the known metastable phases of SiO$_{2}$, suggesting a possibility of its synthesis.

cond-mat.mtrl-sci↗

arXiv2013

Interstitial-Boron Solution Strengthened WB$_{3+x}$

By means of variable-composition evolutionary algorithm coupled with density functional theory and in combination with aberration-corrected high-resolution transmission electron microscopy experiments, we have studied and characterized the composition, structure and hardness properties of WB$_{3+x}$ ($x$ $<$ 0.5). We provide robust evidence for the occurrence of stoichiometric WB$_3$ and non-stoichiometric WB$_{3+x}$ both crystallizing in the metastable $hP$16 ($P6_3/mmc$) structure. No signs for the formation of the highly debated WB$_4$ (both $hP$20 and $hP$10) phases were found. Our results rationalize the seemingly contradictory high-pressure experimental findings and suggest that the interstitial boron atom is located in the tungsten layer and vertically interconnect with four boron atoms, thus forming a typical three-center boron net with the upper and lower boron layers in a three-dimensional covalent network, which thereby strengthen the hardness.

cond-mat.mtrl-sci↗

arXiv2012

Structure, bonding, and hardness of CrB$_4$: a superhard material?

By electron and X-ray diffraction we establish that the CrB$_4$ compound discovered over 40 years ago crystallizes in the $oP10$ (\emph{Pnnm}) structure, in disagreement with previous experiments but in agreement with a recent first-principles prediction. The 3D boron network in the new structure is a distorted version of the rigid carbon $sp^3$ network proposed recently for the high-pressure C$_4$ allotrope. According to our density functional theory calculations and the analysis of the bonding, CrB$_4$ is a potentially superhard material. In fact, the calculated weakest shear and tensile stresses exceed 50 GPa and its Vickers hardness is estimated to be 48 GPa.

cond-mat.mtrl-sci↗

arXiv2012

Families of superhard crystalline carbon allotropes induced via cold-compressed graphite and nanotubes

We report a general scheme to systematically construct two classes of structural families of superhard sp3 carbon allotropes of cold compressed graphite through the topological analysis of odd 5+7 or even 4+8 membered carbon rings stemmed from the stacking of zigzag and armchair chains. Our results show that the previously proposed M, bct-C4, W and Z allotropes belong to our currently proposed families and that depending on the topological arrangement of the native carbon rings numerous other members are found that can help us understand the structural phase transformation of cold-compressed graphite and carbon nanotubes (CNTs). In particular, we predict the existence of two simple allotropes, R- and P-carbon, which match well the experimental X-ray diffraction patterns of cold-compressed graphite and CNTs, respectively, display a transparent wide-gap insulator ground state and possess a large Vickers hardness comparable to diamond.

cond-mat.mtrl-sci↗

arXiv2011

Hardness of T-carbon: Density functional theory calculations

We revisit and interpret the mechanical properties of the recently proposed allotrope of carbon, T-carbon [Sheng \emph{et al.}, Phys. Rev. Lett., \textbf{106}, 155703 (2011)], using density functional theory in combination with different empirical hardness models. In contrast with the early estimation based on the Gao's model, which attributes to T-carbon an high Vickers hardness of 61 GPa comparable to that of superhard cubic boron nitride (\emph{c}-BN), we find that T-carbon is not a superhard material, since its Vickers hardenss does not exceed 10 GPa. Besides providing clear evidence for the absence of superhardenss in T-carbon, we discuss the physical reasons behind the failure of Gao's and Šim$\rm\mathring{u}$nek and Vackář's (SV) models in predicting the hardness of T-carbon, residing on their improper treatment of the highly anisotropic distribution of quasi-\emph{sp}$^3$-like C-C hybrids. A possible remedy to the Gao and SV models based on the concept of superatom is suggest, which indeed yields a Vickers hardness of about 8 GPa.

cond-mat.mtrl-sci↗

arXiv2011

Intrinsic Correlation between Hardness and Elasticity in Polycrystalline Materials and Bulk Metallic Glasses

Though extensively studied, hardness, defined as the resistance of a material to deformation, still remains a challenging issue for a formal theoretical description due to its inherent mechanical complexity. The widely applied Teter's empirical correlation between hardness and shear modulus has been considered to be not always valid for a large variety of materials. Here, inspired by the classical work on Pugh's modulus ratio, we develop a theoretical model which establishes a robust correlation between hardness and elasticity for a wide class of materials, including bulk metallic glasses, with results in very good agreement with experiment. The simplified form of our model also provides an unambiguous theoretical evidence for Teter's empirical correlation.

cond-mat.mtrl-sci↗