Tersoff-style three-body potential for Ge developed by Mahdizadeh and Akhlamadi (2017) v000

Sayyed Jalil Mahdizadeh; Golnoosh Akhlamadi

doi:10.25950/e426db32

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Tersoff_LAMMPS_MahdizadehAkhlamadi_2017_Ge__MO_344019981553_000

Interatomic potential for Germanium (Ge).
Use this Potential

Title A single sentence description.	Tersoff-style three-body potential for Ge developed by Mahdizadeh and Akhlamadi (2017) v000
Description A short description of the Model describing its key features including for example: type of model (pair potential, 3-body potential, EAM, etc.), modeled species (Ac, Ag, ..., Zr), intended purpose, origin, and so on.	This is a re-parameterization of the Tersoff empirical potential for the 2D nanomaterial ‘germanene’. The well-known chi-square minimization procedure was used to optimize the original Tersoff potential parameters.
Species The supported atomic species.	Ge
Disclaimer A statement of applicability provided by the contributor, informing users of the intended use of this KIM Item.	None
Content Origin	https://www.ctcms.nist.gov/potentials/entry/2017--Mahdizadeh-S-J-Akhlamadi-G--Ge/

Contributor	I Nikiforov
Maintainer	I Nikiforov
Developer	Sayyed Jalil Mahdizadeh Golnoosh Akhlamadi
Published on KIM	2022
How to Cite	This Model originally published in [1] is archived in OpenKIM [2-5]. [1] Mahdizadeh SJ, Akhlamadi G. Optimized Tersoff empirical potential for germanene. Journal of Molecular Graphics and Modelling [Internet]. 2017;72:1–5. Available from: https://www.sciencedirect.com/science/article/pii/S1093326316303047 doi:10.1016/j.jmgm.2016.11.009 — (Primary Source) A primary source is a reference directly related to the item documenting its development, as opposed to other sources that are provided as background information. [2] Mahdizadeh SJ, Akhlamadi G. Tersoff-style three-body potential for Ge developed by Mahdizadeh and Akhlamadi (2017) v000. OpenKIM; 2022. doi:10.25950/e426db32 [3] Brink T, Thompson AP, Farrell DE, Wen M, Tersoff J, Nord J, et al. Model driver for Tersoff-style potentials ported from LAMMPS v005. OpenKIM; 2021. doi:10.25950/9a7dc96c [4] Tadmor EB, Elliott RS, Sethna JP, Miller RE, Becker CA. The potential of atomistic simulations and the Knowledgebase of Interatomic Models. JOM. 2011;63(7):17. doi:10.1007/s11837-011-0102-6 [5] Elliott RS, Tadmor EB. Knowledgebase of Interatomic Models (KIM) Application Programming Interface (API). OpenKIM; 2011. doi:10.25950/ff8f563a Click here to download the above citation in BibTeX format.
Citations This panel presents information regarding the papers that have cited the interatomic potential (IP) whose page you are on. The OpenKIM machine learning based Deep Citation framework is used to determine whether the citing article actually used the IP in computations (denoted by "USED") or only provides it as a background citation (denoted by "NOT USED"). For more details on Deep Citation and how to work with this panel, click the documentation link at the top of the panel. The word cloud to the right is generated from the abstracts of IP principle source(s) (given below in "How to Cite") and the citing articles that were determined to have used the IP in order to provide users with a quick sense of the types of physical phenomena to which this IP is applied. The bar chart shows the number of articles that cited the IP per year. Each bar is divided into green (articles that USED the IP) and blue (articles that did NOT USE the IP). Users are encouraged to correct Deep Citation errors in determination by clicking the speech icon next to a citing article and providing updated information. This will be integrated into the next Deep Citation learning cycle, which occurs on a regular basis. OpenKIM acknowledges the support of the Allen Institute for AI through the Semantic Scholar project for providing citation information and full text of articles when available, which are used to train the Deep Citation ML algorithm.	This panel provides information on past usage of this interatomic potential (IP) powered by the OpenKIM Deep Citation framework. The word cloud indicates typical applications of the potential. The bar chart shows citations per year of this IP (bars are divided into articles that used the IP (green) and those that did not (blue)). The complete list of articles that cited this IP is provided below along with the Deep Citation determination on usage. See the Deep Citation documentation for more information. 21 Citations (3 used) Show Model Used Show All Help us to determine which of the papers that cite this potential actually used it to perform calculations. If you know, click the . H. M. Chen, G. X. Li, J. Zhao, and H. Wang, “Temperature and composition dependence of thermophysical properties within a wide temperature range for ternary Si–Ge–Ag alloys,” Journal of Applied Physics. 2023. link Times cited: 0 Abstract: The thermophysical properties of Si–Ge–Ag alloys in a broad … read more Abstract: The thermophysical properties of Si–Ge–Ag alloys in a broad temperature range are essential for the design of electronic devices. In this work, relationships between specific heat, thermal expansion, thermal conductivity and temperature, as well as chemical composition of Si–Ge–Ag alloys were clarified. Moreover, various thermophysical properties’ prediction strategies of multicomponent alloys from pure elements were evaluated. The specific heat of Ag–Si, Ag–Ge, Si–Ge, and Si–Ge–Ag alloys was determined by the differential scanning method. The results showed a significant increase with rising temperature at low temperatures followed by a gradual rise at high temperatures. The specific heat reached the maximum value when a small amount of Si/Ge was introduced to Ag. The coefficient of thermal expansion was obtained by a dilatometric method and increased slightly with the increasing temperature, while decreased linearly with the increase in the Si/Ge content. Furthermore, the thermal conductivity was investigated via a laser flash apparatus. It decreased with rising temperature when the Ag content is smaller than 50%, whereas it increased with rising temperature when the Ag content exceeds 50%. The thermal conductivity of Si–Ge alloys decreased with rising temperature and reached the local minimum for Si–Ge alloys with an equiatomic ratio of Si and Ge. More importantly, the experimental results reveal that the thermal expansion that is related to volume can be estimated approximately by pure metals in Si–Ge–Ag alloys. However, this rule cannot be applied to specific heat and thermal conductivity, which is due to the influence of lattice vibration, electronic scattering, and microstructure. read less M. Z. Dehaghani et al., “Fracture behavior of SiGe nanosheets: Mechanics of monocrystalline vs. polycrystalline structure,” Engineering Fracture Mechanics. 2021. link Times cited: 15 M.-Q. Le, “Fracture of monolayer germanene: A molecular dynamics study,” International Journal of Modern Physics B. 2018. link Times cited: 12 Abstract: Molecular dynamics simulations with Tersoff potential were p… read more Abstract: Molecular dynamics simulations with Tersoff potential were performed to study the fracture properties of monolayer germanene at 300 K. The two-dimensional (2D) Young’s modulus, 2D tensile strength and axial strain at the tensile strength of pristine monolayer germanene are about 36.0 and 37.5 N/m; 5.1 and 4.6 N/m; 21.4 and 15.9%, in the zigzag and armchair directions, respectively. Griffith theory was applied to compute the critical stress intensity factor. Compared to monolayer graphene, the critical stress intensity factor of monolayer germanene is much smaller. Fracture pattern and effects of the initial crack length on the fracture properties are also studied. Results are useful for future design and applications of this 2D material. read less W. Zhao, S. Wang, L. Zhou, and X. Du, “Reducing interfacial thermal resistance between polyethylene oxide-based solid-state polymer electrolyte and lithium anode by using IVA group two-dimensional materials: A molecular dynamics study,” International Journal of Heat and Mass Transfer. 2024. link Times cited: 0 M. Ma’zdziarz, “Transferability of interatomic potentials for germanene (2D germanium),” Journal of Applied Physics. 2023. link Times cited: 0 Abstract: The capacities of various interatomic potentials available f… read more Abstract: The capacities of various interatomic potentials available for elemental germanium, with the scope to choose the potential suitable for the modeling of germanene (2D germanium) allotropes,f were investigated. Structural and mechanical properties of the flat, low-buckled, trigonal dumbbell, and large honeycomb dumbbell single-layer germanium (germanene) phases, were obtained using the density functional theory and molecular statics computations with Tersoff, modified embedded atom method, Stillinger–Weber, environment-dependent interatomic potential, ReaxFF, and machine-learning-based interatomic potentials. A systematic quantitative comparative study and discussion of the findings are given. read less B. Yao, Z. R. Liu, D. Legut, and R. F. Zhang, “Hybrid potential model with high feasibility and flexibility for metallic and covalent solids,” Physical Review B. 2023. link Times cited: 0 S. Jalwadi and T. Bhandakkar, “Development of Virtual Internal Bond method based material model for Carbon fiber and its application to Carbon fiber reinforced epoxy system,” Engineering Fracture Mechanics. 2023. link Times cited: 0 J. A. Vita and D. Trinkle, “Exploring the necessary complexity of interatomic potentials,” Computational Materials Science. 2021. link Times cited: 8 M. Noshin, A. I. Khan, R. Chakraborty, and S. Subrina, “Modeling and computation of thermal and optical properties in silicene supported honeycomb bilayer and heterobilayer nanostructures,” Materials Science in Semiconductor Processing. 2021. link Times cited: 8 M. Rahman, E. Chowdhury, D. A. Redwan, and S. Hong, “Computational characterization of thermal and mechanical properties of single and bilayer germanene nanoribbon,” Computational Materials Science. 2021. link Times cited: 13 N. H. Giang and V. V. Hoang, “Influences of cooling rate on formation of amorphous germanene,” Physica E-low-dimensional Systems & Nanostructures. 2021. link Times cited: 2 S. Nickabadi, R. Ansari, and S. Rouhi, “Evaluation of the Morse potential function coefficients for germanene by the first principles approach.,” Journal of molecular graphics & modelling. 2020. link Times cited: 7 M. A. Hassan and P. K. Das, “Thermal Conductivity of Silicene nanoribbon due to Ge and Sn doping,” 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI). 2019. link Times cited: 0 Abstract: Recently the two dimensional honeycomb structure of silicon … read more Abstract: Recently the two dimensional honeycomb structure of silicon namely silicene has captured a deep interest of the researchers fot its excellent electronic and inadequate thermal transportation properties. The lower value of thermal conductivity of silicene has made it a suitable material in case of thermoelectric applications. To enhance the thermoelectric figure of merit, the effect of chemical doping on silicene nanoribbon along zigzag direction has been investigated in this study. Two different atoms- Ge and Sn from the same group of silicon have been added as impurity atoms with various doping orientations. Our experimental data have revealed strong dependency of thermal conductivity on both doping amount and doping patterns. The thermal conductivity of 0.89% Ge doped zigzag silicene nanoribbon has been found to be around 7.32 W/mK whereas due to higher atomic mass of tin atom compared to germanium the value of the same parameter has been found to be around 6.2 W/mK for same doping concentration at room temperature. Also among different doping patterns, edge doping has shown lowest value of thermal conductivity for all doping concentrations due to elevated phonon scattering rate at the edges of the ribbon. Further investigation have revealed the strong width dependence of the doped nanoribbon structure that shows an increasing trend with ribbon width for any type of dopant atom. All these results suggest that zigzag silicene nanoribbon doped with both germanium and tin atoms have comparatively low thermal conductivity than the pristine structure and can be a potential thermoelectric material of the next generation. read less Y. Zuo et al., “A Performance and Cost Assessment of Machine Learning Interatomic Potentials.,” The journal of physical chemistry. A. 2019. link Times cited: 413 Abstract: Machine learning of the quantitative relationship between lo… read more Abstract: Machine learning of the quantitative relationship between local environment descriptors and the potential energy surface of a system of atoms has emerged as a new frontier in the development of interatomic potentials (IAPs). Here, we present a comprehensive evaluation of ML-IAPs based on four local environment descriptors --- atom-centered symmetry functions (ACSF), smooth overlap of atomic positions (SOAP), the Spectral Neighbor Analysis Potential (SNAP) bispectrum components, and moment tensors --- using a diverse data set generated using high-throughput density functional theory (DFT) calculations. The data set comprising bcc (Li, Mo) and fcc (Cu, Ni) metals and diamond group IV semiconductors (Si, Ge) is chosen to span a range of crystal structures and bonding. All descriptors studied show excellent performance in predicting energies and forces far surpassing that of classical IAPs, as well as predicting properties such as elastic constants and phonon dispersion curves. We observe a general trade-off between accuracy and the degrees of freedom of each model, and consequently computational cost. We will discuss these trade-offs in the context of model selection for molecular dynamics and other applications. read less X. Zhuang, B. He, B. Javvaji, and H. S. Park, “Intrinsic bending flexoelectric constants in two-dimensional materials,” Physical Review B. 2019. link Times cited: 45 Abstract: Flexoelectricity is a form of electromechanical coupling tha… read more Abstract: Flexoelectricity is a form of electromechanical coupling that has recently emerged because, unlike piezoelectricity, it is theoretically possible in any dielectric material. Two-dimensional (2D) materials have also garnered signiﬁcant interest because of their unusual electromechanical properties and high ﬂexibility, but the intrinsic ﬂexoelectric properties of these materials remain unresolved. In this work, using atomistic modeling accounting for charge-dipole interactions, we report the intrinsic ﬂexoelectric constants for a range of two-dimensional materials, including graphene allotropes, nitrides, graphene analogs of group-IV elements, and the transition metal dichalcogenides (TMDCs). We accomplish this through a proposed mechanical bending scheme that eliminates the piezoelectric contribution to the total polarization, which enables us to directly measure the ﬂexoelectric constants. While ﬂat 2D materials like graphene have low ﬂexoelectric constants due to weak π − σ interactions, buckling is found to increase the ﬂexoelectric constants in monolayer group-IV elements. Finally, due to signiﬁcantly enhanced charge transfer coupled with structural asymmetry due to bending, the TMDCs are found to have the largest ﬂexoelectric constants, including MoS 2 having a ﬂexoelectric constant ten times larger than graphene. read less B. Liu and K. Zhou, “Recent progress on graphene-analogous 2D nanomaterials: Properties, modeling and applications,” Progress in Materials Science. 2019. link Times cited: 208 R. Paul, T. Tasnim, S. Saha, and M. Motalab, “Atomistic analysis to characterize the impact of temperature and defects on the mechanical properties of germanene sheet,” Materials Research Express. 2018. link Times cited: 17 Abstract: Germanene, a monolayer buckled hexagonal form of germanium s… read more Abstract: Germanene, a monolayer buckled hexagonal form of germanium shows surprisingly superior electrical and physical properties in strained and defected form. However, mechanical characterization and effects of chirality, temperature, and defects on mechanical properties of germanene are yet to be comprehensively investigated. An attempt is made in this study using the application of molecular dynamics simulation with the optimized tersoff potential to analyze the uniaxial tensile properties of germanene sheet. The room temperature ultimate strength of pristine 152 Å × 152 Å zigzag and armchair germanene sheet is estimated to be 7.9 GPa and 6.8 GPa, respectively. A negative correlation of ultimate strength and fracture strain with temperature is found. Additionally, four types of structural defects were introduced in the germanene sheet namely; point vacancy, bi-vacancy, Stone–Wales (SW) types 1 and 2. Regarding bi-vacancy, the ultimate strength decreases substantially in both armchair and zigzag direction compared to point vacancy whereas the effect of SW defects shows chirality dependency. A SW-1 defect accounts for a larger decrease in ultimate strength in armchair direction than in zigzag direction where a reversed trend follows in SW-2 defect. read less H. Zhai and J. Yeo, “Multiscale mechanics of thermal gradient coupled graphene fracture: A molecular dynamics study,” International Journal of Applied Mechanics. 2022. link Times cited: 2 Abstract: The thermo-mechanical coupling mechanism of graphene fractur… read more Abstract: The thermo-mechanical coupling mechanism of graphene fracture under thermal gradients possesses rich applications whereas is hard to study due to its coupled non-equilibrium nature. We employ non-equilibrium molecular dynamics to study the fracture of graphene by applying a fixed strain rate under different thermal gradients by employing different potential fields. It is found that for AIREBO and AIREBO-M, the fracture stresses do not strictly follow the positive correlations with the initial crack length. Strain-hardening effects are observed for"REBO-based"potential models of small initial defects, which is interpreted as blunting effect observed for porous graphene. The temperature gradients are observed to not show clear relations with the fracture stresses and crack propagation dynamics. Quantized fracture mechanics verifies our molecular dynamics calculations. We provide a unique perspective that the transverse bond forces share the loading to account for the nonlinear increase of fracture stress with shorter crack length. Anomalous kinetic energy transportation along crack tips is observed for"REBO-based"potential models, which we attribute to the high interatomic attractions in the potential models. The fractures are honored to be more"brittle-liked"carried out using machine learning interatomic potential (MLIP), yet incapable of simulating post-fracture dynamical behaviors. The mechanical responses using MLIP are observed to be not related to temperature gradients. The temperature configuration of equilibration simulation employing the dropout uncertainty neural network potential with a dropout rate of 0.1 is reported to be the most accurate compared with the rest. This work is expected to inspire further investigation of non-equilibrium dynamics in graphene with practical applications in various engineering fields. read less M. Kotoul et al., “A novel multiscale approach to brittle fracture of nano/micro‐sized components,” Fatigue & Fracture of Engineering Materials & Structures. 2020. link Times cited: 5 K. Momeni et al., “Multiscale computational understanding and growth of 2D materials: a review,” npj Computational Materials. 2020. link Times cited: 85 M. R. Arshee, S. Adnan, M. Motalab, and P. Bose, “Inherent mechanical properties of bilayer germanene coupled by covalent bonding,” RSC Advances. 2019. link Times cited: 12 Abstract: Germanene, a two-dimensional buckled hexagonal structure of … read more Abstract: Germanene, a two-dimensional buckled hexagonal structure of germanium atoms, has attractive mechanical, optical, thermal and electronic features. Recently it has been reported that covalent bonding between two monolayer germanene sheets leads to the integration of intrinsic magnetism and band gap opening that makes it attractive to future nanoelectronics. In order to use the captivating features of this structure, its mechanical characterization needs to be studied. In this study, molecular dynamics simulations have been performed using optimized Tersoff potential to analyze the effect of chirality, temperature and strain rate on the uniaxial tensile properties of this structure. This study suggests that bonded bilayer germanene shows higher mechanical strength compared to monolayer germanene. Uniaxial loading in the armchair direction shows higher fracture strength and strain compared to the zigzag direction which is contrary to the monolayer germanene. It also reports that with increasing temperature, both the fracture strength and strain of the structure decrease. It has been found that at a higher strain rate, the material exhibits higher fracture strength and strain. Mechanical properties and fracture mechanisms of defected structures have also been reported below the curie temperature. Moreover, the interlayer shear characteristics of the bilayer structure have been looked into. These results will provide significant insight to the investigation of this structure as a potential nano-electronics substitute. read less
Funding	Not available

Short KIM ID The unique KIM identifier code.	MO_344019981553_000
Extended KIM ID The long form of the KIM ID including a human readable prefix (100 characters max), two underscores, and the Short KIM ID. Extended KIM IDs can only contain alpha-numeric characters (letters and digits) and underscores and must begin with a letter.	Tersoff_LAMMPS_MahdizadehAkhlamadi_2017_Ge__MO_344019981553_000
DOI	10.25950/e426db32 https://doi.org/10.25950/e426db32 https://commons.datacite.org/doi.org/10.25950/e426db32
KIM Item Type Specifies whether this is a Portable Model (software implementation of an interatomic model); Portable Model with parameter file (parameter file to be read in by a Model Driver); Model Driver (software implementation of an interatomic model that reads in parameters).	Portable Model using Model Driver Tersoff_LAMMPS__MD_077075034781_005
Driver	Tersoff_LAMMPS__MD_077075034781_005
KIM API Version	2.2
Potential Type	tersoff

Verification Check Dashboard

(Click here to learn more about Verification Checks)

Grade	Name	Category	Brief Description	Full Results	Aux File(s)
P All elements claimed by model are supported in at least one of the tested configurations.	vc-species-supported-as-stated	mandatory	The model supports all species it claims to support; see full description.	Results	Files
P Periodic boundary conditions were correctly supported for all configurations that the model was able to compute.	vc-periodicity-support	mandatory	Periodic boundary conditions are handled correctly; see full description.	Results	Files
P Model energy has permutation symmetry for all configurations the model was able to compute.	vc-permutation-symmetry	mandatory	Total energy and forces are unchanged when swapping atoms of the same species; see full description.	Results	Files
A The letter grade A was assigned because the normalized error in the computation was 7.90126e-11 compared with a machine precision of 2.22045e-16. The letter grade was based on 'score=log10(error/eps)', with ranges A=[0, 7.5], B=(7.5, 10.0], C=(10.0, 12.5], D=(12.5, 15.0), F>15.0. 'A' is the best grade, and 'F' indicates failure.	vc-forces-numerical-derivative	consistency	Forces computed by the model agree with numerical derivatives of the energy; see full description.	Results	Files
P The model is C^1 continuous. This means that the model has continuous energy and continuous first derivative.	vc-dimer-continuity-c1	informational	The energy versus separation relation of a pair of atoms is C1 continuous (i.e. the function and its first derivative are continuous); see full description.	Results	Files
P Model energy and forces are invariant with respect to rigid-body motion (translation and rotation) for all configurations the model was able to compute.	vc-objectivity	informational	Total energy is unchanged and forces transform correctly under rigid-body translation and rotation; see full description.	Results	Files
P Model energy has inversion symmetry for all configurations the model was able to compute.	vc-inversion-symmetry	informational	Total energy is unchanged and forces change sign when inverting a configuration through the origin; see full description.	Results	Files
P No memory leak detected.	vc-memory-leak	informational	The model code does not have memory leaks (i.e. it releases all allocated memory at the end); see full description.	Results	Files
P All threads give identical results for tested case. Model appears to be thread-safe.	vc-thread-safe	mandatory	The model returns the same energy and forces when computed in serial and when using parallel threads for a set of configurations. Note that this is not a guarantee of thread safety; see full description.	Results	Files
N/A Unable to perform verification check due to an error.	vc-unit-conversion	mandatory	The model is able to correctly convert its energy and/or forces to different unit sets; see full description.	Results	Files

This bar chart plot shows the mono-atomic body-centered cubic (bcc) lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Ge

Cohesive Energy Graph

This graph shows the cohesive energy versus volume-per-atom for the current mode for four mono-atomic cubic phases (body-centered cubic (bcc), face-centered cubic (fcc), simple cubic (sc), and diamond). The curve with the lowest minimum is the ground state of the crystal if stable. (The crystal structure is enforced in these calculations, so the phase may not be stable.) Graphs are generated for each species supported by the model.

Species: Ge

Diamond Lattice Constant

This bar chart plot shows the mono-atomic face-centered diamond lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Ge

Dislocation Core Energies

This graph shows the dislocation core energy of a cubic crystal at zero temperature and pressure for a specific set of dislocation core cutoff radii. After obtaining the total energy of the system from conjugate gradient minimizations, non-singular, isotropic and anisotropic elasticity are applied to obtain the dislocation core energy for each of these supercells with different dipole distances. Graphs are generated for each species supported by the model.

(No matching species)

FCC Elastic Constants

This bar chart plot shows the mono-atomic face-centered cubic (fcc) elastic constants predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Ge

FCC Lattice Constant

This bar chart plot shows the mono-atomic face-centered cubic (fcc) lattice constant predicted by the current model (shown in red) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Ge

FCC Stacking Fault Energies

This bar chart plot shows the intrinsic and extrinsic stacking fault energies as well as the unstable stacking and unstable twinning energies for face-centered cubic (fcc) predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

(No matching species)

FCC Surface Energies

This bar chart plot shows the mono-atomic face-centered cubic (fcc) relaxed surface energies predicted by the current model (shown in blue) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

(No matching species)

SC Lattice Constant

This bar chart plot shows the mono-atomic simple cubic (sc) lattice constant predicted by the current model (shown in the unique color) compared with the predictions for all other models in the OpenKIM Repository that support the species. The vertical bars show the average and standard deviation (one sigma) bounds for all model predictions. Graphs are generated for each species supported by the model.

Species: Ge

Cubic Crystal Basic Properties Table

Species: Ge

Tests

CohesiveEnergyVsLatticeConstant__TD_554653289799_003

Cohesive energy versus lattice constant curve for monoatomic cubic lattices v003

Creators:
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/64cb38c5

This Test Driver uses LAMMPS to compute the cohesive energy of a given monoatomic cubic lattice (fcc, bcc, sc, or diamond) at a variety of lattice spacings. The lattice spacings range from a_min (=a_min_frac*a_0) to a_max (=a_max_frac*a_0) where a_0, a_min_frac, and a_max_frac are read from stdin (a_0 is typically approximately equal to the equilibrium lattice constant). The precise scaling and number of lattice spacings sampled between a_min and a_0 (a_0 and a_max) is specified by two additional parameters passed from stdin: N_lower and samplespacing_lower (N_upper and samplespacing_upper). Please see README.txt for further details.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Cohesive energy versus lattice constant curve for bcc Ge v004	view	2327
Cohesive energy versus lattice constant curve for diamond Ge v004	view	2924
Cohesive energy versus lattice constant curve for fcc Ge v004	view	2356
Cohesive energy versus lattice constant curve for sc Ge v004	view	2377

ElasticConstantsCubic__TD_011862047401_006

Elastic constants for cubic crystals at zero temperature and pressure v006

Creators: Junhao Li and Ellad Tadmor
Contributor: tadmor
Publication Year: 2019
DOI: https://doi.org/10.25950/5853fb8f

Computes the cubic elastic constants for some common crystal types (fcc, bcc, sc, diamond) by calculating the hessian of the energy density with respect to strain. An estimate of the error associated with the numerical differentiation performed is reported.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Elastic constants for bcc Ge at zero temperature v006	view	21812
Elastic constants for diamond Ge at zero temperature v001	view	20984
Elastic constants for fcc Ge at zero temperature v006	view	31002
Elastic constants for sc Ge at zero temperature v006	view	18897

EquilibriumCrystalStructure__TD_457028483760_002

Equilibrium structure and energy for a crystal structure at zero temperature and pressure v002

Creators:
Contributor: ilia
Publication Year: 2024
DOI: https://doi.org/10.25950/2f2c4ad3

Computes the equilibrium crystal structure and energy for an arbitrary crystal at zero temperature and applied stress by performing symmetry-constrained relaxation. The crystal structure is specified using the AFLOW prototype designation. Multiple sets of free parameters corresponding to the crystal prototype may be specified as initial guesses for structure optimization. No guarantee is made regarding the stability of computed equilibria, nor that any are the ground state.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_cF136_227_aeg v002	view	6537059
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_cF4_225_a v002	view	53347
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_cF8_227_a v002	view	103535
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_cI16_206_c v002	view	86651
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_cI2_229_a v002	view	73105
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_hP2_194_c v002	view	62798
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_hP4_194_f v002	view	72369
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_hP8_194_ef v002	view	60001
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_hR8_148_cf v002	view	61428
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_oC16_64_df v002	view	102502
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_tI4_141_a v002	view	44659
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_tP12_96_ab v002	view	41438

LatticeConstantCubicEnergy__TD_475411767977_007

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure v007

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/2765e3bf

Equilibrium lattice constant and cohesive energy of a cubic lattice at zero temperature and pressure.

Test	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium zero-temperature lattice constant for bcc Ge v007	view	6873
Equilibrium zero-temperature lattice constant for diamond Ge v007	view	3504
Equilibrium zero-temperature lattice constant for fcc Ge v007	view	9309
Equilibrium zero-temperature lattice constant for sc Ge v007	view	5330

LatticeConstantHexagonalEnergy__TD_942334626465_005

Equilibrium lattice constants for hexagonal bulk structures at zero temperature and pressure v005

Creators: Daniel S. Karls and Junhao Li
Contributor: karls
Publication Year: 2019
DOI: https://doi.org/10.25950/c339ca32

Calculates lattice constant of hexagonal bulk structures at zero temperature and pressure by using simplex minimization to minimize the potential energy.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Equilibrium lattice constants for hcp Ge v005		view	44359

LinearThermalExpansionCoeffCubic__TD_522633393614_002

Linear thermal expansion coefficient of cubic crystal structures v002

Creators:
Contributor: mjwen
Publication Year: 2024
DOI: https://doi.org/10.25950/9d9822ec

This Test Driver uses LAMMPS to compute the linear thermal expansion coefficient at a finite temperature under a given pressure for a cubic lattice (fcc, bcc, sc, diamond) of a single given species.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Linear thermal expansion coefficient of diamond Ge at 293.15 K under a pressure of 0 MPa v002		view	999320

VacancyFormationEnergyRelaxationVolume__TD_647413317626_001

Monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/fca89cea

Computes the monovacancy formation energy and relaxation volume for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Monovacancy formation energy and relaxation volume for diamond Ge		view	156738

VacancyFormationMigration__TD_554849987965_001

Vacancy formation and migration energies for cubic and hcp monoatomic crystals v001

Creators:
Contributor: efuem
Publication Year: 2023
DOI: https://doi.org/10.25950/c27ba3cd

Computes the monovacancy formation and migration energies for cubic and hcp monoatomic crystals.

Test	Test Results	Link to Test Results page	Benchmark time Usertime multiplied by the Whetstone Benchmark. This number can be used (approximately) to compare the performance of different models independently of the architecture on which the test was run. Measured in Millions of Whetstone Instructions (MWI)
Vacancy formation and migration energy for diamond Ge		view	3236873

Errors

ElasticConstantsHexagonal__TD_612503193866_004

Test	Error Categories	Link to Error page
Elastic constants for hcp Ge at zero temperature v004	other	view

EquilibriumCrystalStructure__TD_457028483760_000

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_hP2_194_c v000	other	view
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_oC16_64_df v000	other	view

EquilibriumCrystalStructure__TD_457028483760_002

Test	Error Categories	Link to Error page
Equilibrium crystal structure and energy for Ge in AFLOW crystal prototype A_oI4_74_e v002	other	view

No Driver

Verification Check	Error Categories	Link to Error page
PeriodicitySupport__VC_895061507745_004	other	view

Files

CMakeLists.txt
Ge.settings
Ge.tersoff
LICENSE
kimprovenance.edn
kimspec.edn

Download

Tersoff_LAMMPS_MahdizadehAkhlamadi_2017_Ge__MO_344019981553_000.txz	Tar+XZ	Linux and OS X archive
Tersoff_LAMMPS_MahdizadehAkhlamadi_2017_Ge__MO_344019981553_000.zip	Zip	Windows archive

Download Dependency

This Model requires a Model Driver. Archives for the Model Driver Tersoff_LAMMPS__MD_077075034781_005 appear below.

Tersoff_LAMMPS__MD_077075034781_005.txz	Tar+XZ	Linux and OS X archive
Tersoff_LAMMPS__MD_077075034781_005.zip	Zip	Windows archive

Wiki

Wiki is ready to accept new content.

Tersoff_LAMMPS_MahdizadehAkhlamadi_2017_Ge__MO_344019981553_000

Verification Check Dashboard

Visualizers (in-page)

BCC Lattice Constant

Cohesive Energy Graph

Diamond Lattice Constant

Dislocation Core Energies

FCC Elastic Constants

FCC Lattice Constant

FCC Stacking Fault Energies

FCC Surface Energies

SC Lattice Constant

Cubic Crystal Basic Properties Table

Tests

Errors

Files

Download

Download Dependency

Wiki