Experiment-driven atomistic materials modeling: A case study combining X-ray photoelectron spectroscopy and machine learning potentials to infer the structure of oxygen-rich amorphous carbon
Tigany Zarrouk, Rina Ibragimova, Albert P. Bartók, Miguel A. Caro
An important yet challenging aspect of atomistic materials modeling is reconciling experimental and computational results. Conventional approaches involve generating numerous configurations through molecular dynamics or Monte Carlo structure optimization and selecting the one with the closest match to experiment. However, this inefficient process is not guaranteed to succeed. We introduce a general method to combine atomistic machine learning (ML) with experimental observables that produces atomistic structures compatible with experiment by design. We use this approach in combination with grand-canonical Monte Carlo within a modified Hamiltonian formalism, to generate configurations that agree with experimental data and are chemically sound (low in energy). We apply our approach to understand the atomistic structure of oxygenated amorphous carbon (a-CO$_{x}$), an intriguing carbon-based material, to answer the question of how much oxygen can be added to carbon before it fully decomposes into CO and CO$_2$. Utilizing an ML-based X-ray photoelectron spectroscopy (XPS) model trained from $GW$ and density functional theory (DFT) data, in conjunction with an ML interatomic potential, we identify a-CO$_{x}$ structures compliant with experimental XPS predictions that are also energetically favorable with respect to DFT. Employing a network analysis, we accurately deconvolve the XPS spectrum into motif contributions, both revealing the inaccuracies inherent to experimental XPS interpretation and granting us atomistic insight into the structure of a-CO$_{x}$. This method generalizes to multiple experimental observables and allows for the elucidation of the atomistic structure of materials directly from experimental data, thereby enabling experiment-driven materials modeling with a degree of realism previously out of reach.
An approach is presented for the atomistic study of phonon transport in real dielectric nanowires via Green functions. The formalism is applied to investigate the phonon flow through nanowires coated by an amorphous material. Examples for a simple model system, and for real Si nanowires coated by silica are given. New physical results emerge for these systems, regarding the character of the transition from ballistic to diffusive transport, the low temperature thermal conductance, and the influence of the wire-coating interface on the thermal transport. An efficient treatment of phonon scatteri…
We have analyzed the atomic rearrangements underlying self-diffusion in amorphous Si during annealing using tight-binding molecular dynamics simulations. Two types of amorphous samples with different structural features were used to analyze the influence of coordination defects. We have identified several types of atomic rearrangement mechanisms, and we have obtained an effective migration energy of around 1 eV. We found similar migration energies for both types of samples, but higher diffusivities in the one with a higher initial percentage of coordination defects.
We employ ab initio molecular dynamics to simulate the response of hydrogenated amorphous silicon to light exposure (Staebler-Wronski effect). We obtain improved microscopic understanding of PV operation, compute the motion of H atoms, and modes of light-induced degradation of photovoltaics. We clarify existing models of light-induced change in aSi:H and show that the Hydrogen collision model of Branz3 is correct in essentials.
The atomic structure of amorphous materials is believed to be well described by the continuous random network model. We present an algorithm for the generation of large, high-quality continuous random networks. The algorithm is a variation of the "sillium" approach introduced by Wooten, Winer, and Weaire. By employing local relaxation techniques, local atomic rearrangements can be tried that scale almost independently of system size. This scaling property of the algorithm paves the way for the generation of realistic device-size atomic networks.
There is an increasing interest in the amorphous states of metal-organic frameworks (MOFs) and porous coordination polymers, which can be produced by pressure-induced amorphization, temperature-induced amorphization, melt-quenching, ball-milling, irradiation, etc. They can exhibit useful physical and chemical properties, distinct from those achievable in the crystalline states, along with greater ease of processing, and intrinsic advantages over crystals and powders, such as high transparency and mechanical robustness. However, these amorphous states are particularly challenging to characteriz…
We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu-Zr materials, an example of a binary alloy system that can coexist in several ordered intermetallics and as an amorphous phase. The complex phase diagram for Cu-Zr makes it a challenging system for traditional atomistic force-fields that fail to describe well the different properties and phases. Instead, we show that a DP approach using a large database with ~300k configurations can render results generally on par with DFT. The training set includes configuratio…
One of the major theoretical riddles in shear banding instabilities is the angle that the shear band chooses spontaneously with respect to the principal stress axis. Here we employ our recent atomistic theory to compute analytically the angle in terms of the characteristics of the Eshelby inclusion that models faithfully the eigenfunction of the Hessian matrix that goes soft at the plastic instability. We show that loading protocols that do not conserve volume result in shear bands at angles different from 45$^o$ to the strain axis; only when the external strains preserve volume like in pure s…
Amorphous silicon (a-Si) is a widely studied non-crystalline material, and yet the subtle details of its atomistic structure are still unclear. Here, we show that accurate structural models of a-Si can be obtained by harnessing the power of machine-learning algorithms to create interatomic potentials. Our best a-Si network is obtained by cooling from the melt in molecular-dynamics simulations, at a rate of 10$^{11}$ K/s (that is, on the 10 ns timescale). This structure shows a defect concentration of below 2% and agrees with experiments regarding excess energies, diffraction data, as well as $…
Germanium is the base element in many phase-change materials, i.e. systems that can undergo reversible transformations between their crystalline and amorphous phases. They are widely used in current digital electronics and hold great promise for the next generation of non-volatile memory devices. However, the ultra fast phase transformations required for these applications can be exceedingly complex even for single component systems, and a full physical understanding of these phenomena is still lacking. In this paper we study nucleation and growth of crystalline Ge from amorphous thin films at…
Molecular dynamics simulations are performed to provide a detailed understanding of the functional degradation of shape memory alloys at small scale. The origin of the experimentally reported accumulation of plastic deformation and the anomalous sudden increase of the residual strain under cyclic mechanical loading are explained by detailed insights into the relevant atomic scale processes. Our work reveals that the mechanical response of shape-memory-alloy pillars under cyclic compression is significantly influenced by the presence of an amorphous-like surface region as experimentally induced…
Exponential band edges have been observed in a variety of materials, both crystalline and amorphous. In this paper, we infer the structural origins of these tails in amorphous and defective crystalline Si by direct calculation with current {\it ab initio} methods. We find that exponential tails appear in relaxed models of diamond with suitable point defects. In amorphous silicon (a-Si), we find that structural filaments of short bonds and long bonds exist in the network, and that the tail states near the extreme edges of both band tails are are also filamentary, with much localization on the s…
The annealing treatment in the advanced manufacturing process, e.g., laser-assisted manufacturing, determines the final state of glasses which is critical to its thermal, electrical and mechanical properties. Energy barriers analysis based on the potential energy surface offers an effective way to study the microscopic evolution of the inherent structures during the annealing process in a broadening timescale range, i.e., from atomistic timescale ( ~ ps) to experimental timescale (~ s). Here, we find the distribution activation energy barriers in the potential energy surface can be divided int…
Atomistic Insights into Cu/amorphous-Ta$_x$N Interfacial Adhesion via Machine Learning Interatomic Potentials: Effects of Stoichiometry and Interface Construction
We present a first-principles-based multiscale simulation framework for quantitative predictions of the high-energy part of the Ultraviolet Photoelectron Spectroscopy (UPS) spectra of amorphous molecular solids. The approach combines a deposition simulation, many-body Green's Function Theory, polarizable film-embedding, and multimode electron-vibrational coupling and provides a molecular-level view on the interactions and processes giving rise to spectral features. This insight helps bridging the current gap between experimental UPS and theoretical models as accurate analyses are hampered by t…
We present an information-based total-energy optimization method to produce nearly defect-free structural models of amorphous silicon. Using geometrical, structural and topological information from disordered tetrahedral networks, we have shown that it is possible to generate structural configurations of amorphous silicon, which are superior than the models obtained from conventional reverse Monte Carlo and molecular-dynamics simulations. The new data-driven hybrid approach presented here is capable of producing atomistic models with structural and electronic properties which are on a par with…
We study the statistical properties of the yielding transition in model amorphous solids in the limit of slow, athermal deformation. Plastic flow occurs via alternating phases of elastic loading punctuated by rapid dissipative events in the form of collective avalanches. We investigate their characterization through energy vs. stress drops and at multiple stages of deformation, thus revealing a change of spatial extent of the avalanches and degree of stress correlations as deformation progresses. We show that the statistics of stress and energy drops only become comparable for large events in …
Molecular dynamics (MD) simulations enable the description of ma- terial properties and processes with atomistic detail by numerically solv- ing the time evolution of every atom in the system. We introduce Poly- merModeler, a general-purpose, online simulation tool to build atomistic structures of amorphous polymers and perform MD simulations on the re- sulting configurations to predict their thermo-mechanical properties. Poly- merModeler is available, free of charge, at nanoHUB.org via an interactive web interface, and the actual simulations are performed in the cloud us- ing nanoHUB.org reso…
Drawing inspiration from nature, where some organisms can control the short range order of amorphous minerals, we successfully manipulated the short range order of amorphous alumina by surface and size effects. By utilizing the Atomic Layer Deposition (ALD) method to grow amorphous nanometrically thin films, combined with state-of-the-art electron energy loss spectroscopy (EELS) and X-ray photoelectron spectroscopy (XPS), we showed experimentally that the short range order in such films is strongly influenced by size. This phenomenon is equivalent to the well-known size effect on lattice param…
The thermally-induced structural evolution of silicon- and oxygen-containing hydrogenated amorphous carbon (a-C:H:Si:O) was investigated by X-ray photoelectron and absorption spectroscopy, as well as molecular dynamics (MD) simulations. The spectroscopic results indicate that the introduction of Si and O in hydrogenated amorphous carbon (a-C:H) increases the activation energy for the conversion of sp3- to sp2-bonded C. MD simulations indicate that the higher thermal stability of a-C:H:Si:O compared to a-C:H derives from the lower fraction of strained C-C sp3 bonds in a-C:H:Si:O.
We study propagating mode-I fracture in two dimensional amorphous materials using atomistic simulations. We used the continuous random network (CRN) model of an amorphous material, creating samples using a two dimensional analogue of the WWW (Wooten, Winer & Weaire) Monte-Carlo algorithm. For modeling fracture, molecular-dynamics simulations were run on the resulting samples. The results of our simulations reproduce the main experimental features. In addition to achieving a steady-state crack under a constant driving displacement (which had not yet been achieved by other atomistic models for a…
Localized basis ab initio molecular dynamics simulation within the density functional framework has been used to generate realistic configurations of amorphous silicon carbide (a-SiC). Our approach consists of constructing a set of smart initial configurations that conform essential geometrical and structural aspects of the materials obtained from experimental data, which is subsequently driven via first-principles force-field to obtain the best solution in a reduced solution space. A combination of a priori information (primarily structural and topological) along with the ab-initio optimizati…
We discuss an inverse approach for atomistic modeling of glassy materials. The focus is on structural modeling and electronic properties of hydrogenated amorphous silicon and glassy GeSe2 alloy. The work is based upon a new approach "experimentally constrained molecular relaxation (ECMR)". Unlike conventional approaches (such as molecular dynamics (MD) and Monte Carlo simulations(MC), where a potential function is specified and the system evolves either deterministically (MD) or stochastically (MC), we develop a novel scheme to model structural configurations using experimental data in associa…
The deposition of boron-doped amorphous carbon thin films on SiO2 substrate was achieved via a focused ion beam-assisted chemical vapor deposition of triphenyl borane (C18H15B) and triphenyl borate (C18H15BO3). The existence of boron in the deposited film from triphenyl borane, with a precursor temperature of 90 °C, was confirmed by a core level X-ray photoelectron spectroscopy analysis. The film exhibited a semiconducting behavior with a band gap of 285 meV. Although the band gap was decreased to 197 meV after an annealing process, the film was still semiconductor. Additionally, a drastic red…
The size-dependent phase stability of gamma-Al2O3 was studied by large-scale molecular dynamics simulations over a wide temperature range from 300 to 900 K. For the gamma-Al2O3 crystal, a bulk transformation to alpha-Al2O3 by an FCC-to-HCP transition of the O sublattice is still kinetically hindered at 900 K. However, local distortions of the FCC O-sublattice by the formation of quasi-octahedral Al local coordination spheres become thermally activated, as driven by the partial covalency of the Al-O bond. On the contrary, spherical gamma-Al2O3 NPs (with sizes of 6 and 10 nm) undergo a crystalli…
We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine-learning representation of the density-functional theory (DFT) potential-energy surface, such interatomic potentials enable materials simulations with close-to DFT accuracy but at much lower computational cost. We first determine the maximum accuracy that any finite-range potential can achieve in carbon structures; then, using a novel hierarchical set of two-, three-, and many-body structural descriptors, we construct a GAP model that can indeed reach the…
We propose here a method to generate random networked amorphous structure using only readily available short-range properties like bond lengths, bond angles and connectivity of the constituents. This method is a variant of Monte-Carlo (MC) method wherein the basic constituents of an amorphous network i.e. rigid polyhedral units are connected randomly obeying certain steric constraints. The algorithm is designed to reproduce the medium-range order universally observed in glasses. The method somewhat resembles the reverse MC (RMC) method where a random move of an atom inside a box is accepted or…
Design principles for amorphous solid-state electrolytes
Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences（中国科学院物理研究所凝聚态物理国家实验室）；Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences（中国科学院大学材料科学与光电技术学院）；School of Physical Sciences, University of Chinese Academy of Sciences（中国科学院大学物理科学学院）；School of Materials Science and Engineering, Key Laboratory of Aerospace Materials and Performance (Ministry of Education), Beihang University（北京航空航天大学材料科学与工程学院航空航天材料性能教育部重点实验室）
Owing to the advances in computational techniques and the increase in computational power, atomistic simulations of materials can simulate large systems with higher accuracy. Complex phenomena can be observed in such state-of-the-art atomistic simulations. However, it has become increasingly difficult to understand what is actually happening and mechanisms, for example, in molecular dynamics (MD) simulations. We propose an unsupervised machine learning method to analyze the local structure around a target atom. The proposed method, which uses the two-step locality preserving projections (TS-LP…
The general and practical inversion of diffraction data-producing a computer model correctly representing the material explored - is an important unsolved problem for disordered materials. Such modeling should proceed by using our full knowledge base, both from experiment and theory. In this paper, we describe a robust method to jointly exploit the power of ab initio atomistic simulation along with the information carried by diffraction data. The method is applied to two very different systems: amorphous silicon and two compositions of a solid electrolyte memory material silver-doped GeSe3 . T…
We show that ZIF-4, a metal-organic framework (MOF) with a zeolitic structure, undergoes a crystal--amorphous transition on heating to 300 $^\circ$C. The amorphous form, which we term a-ZIF, is recoverable to ambient conditions or may be converted to a dense crystalline phase of the same composition by heating to 400 $^\circ$C. Neutron and X-ray total scattering data collected during the amorphization process are used as a basis for reverse Monte Carlo refinement of an atomistic model of the structure of a-ZIF. We show that the structure is best understood in terms of a continuous random netwo…
We present the results of an experiment where amorphous carbon was irradiated by femtosecond x-ray free electron laser pulses. The 830 eV laser pulses induce a phase transition in the material which is characterized ex-situ. The phase transition energy threshold is determined by measuring the surface of each irradiated area using an optical Nomarski microscope. The threshold fluence is found to be 282 +/- 11 mJ/cm^2, corresponding to an absorbed dose at the surface of 131 +/-5 meV/atom. Atomic force microscopy measurements show volume expansion of the irradiated sample area, suggesting a solid…
The band offsets between crystalline and hydrogenated amorphous silicon (a-Si:H) are key parameters governing the charge transport in modern silicon hetrojunction solar cells. They are an important input for macroscopic simulators that are used to further optimize the solar cell. Past experimental studies, using X-ray photoelectron spectroscopy (XPS) and capacitance-voltage measurements, have yielded conflicting results on the band offset. Here we present a computational study on the band offsets. It is based on atomistic models and density-functional theory (DFT). The amorphous part of the in…
Amorphous calcium carbonate (ACC) is an important precursor for biomineralisation in marine organisms. Among the key outstanding problems regarding ACC are how best to understand its structure and how to rationalise its metastability as an amorphous phase. Here, we report high-quality atomistic models of ACC generated by using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently-developed inversion approach, we extract from these models the effective Ca$\boldsymbol\cdots$Ca interaction potential governing ACC formation. This potential…
We investigate the amorphous structure, chemical bonding, and electrical properties of magnetron sputtered Fe1-xCx (0.21<x<0.72) thin films. X-ray, electron diffraction and transmission electron microscopy show that the Fe1-xCx films are amorphous nanocomposites, consisting of a two-phase domain structure with Fe-rich carbidic FeCy, and a carbon-rich matrix. Pair distribution function analysis indicates a close-range order similar to those of crystalline Fe3C carbides in all films with additional graphene-like structures at high carbon content (71.8 at% C). From X-ray photoelectron spectroscop…
1. Introduction 2. Molecular dynamics simulation of amorphous carbon structures 3. Atomistic simulation of the bombardment process during the BEN phase of diamond CVD 4. Growth of amorphous silicon 5. One-dimensional hopping in disordered organic solids
Amorphous carbon (a-C) materials have diverse interesting and useful properties, but the understanding of their atomic-scale structures is still incomplete. Here, we report on extensive atomistic simulations of the deposition and growth of a-C films, describing interatomic interactions using a machine learning (ML) based Gaussian Approximation Potential (GAP) model. We expand widely on our initial work [Phys. Rev. Lett. 120, 166101 (2018)] by now considering a broad range of incident ion energies, thus modeling samples that span the entire range from low-density ($sp^{2}$-rich) to high-density…
Chemical segregation and structural transitions at interfaces are important nanoscale phenomena, making them natural targets for atomistic modeling, yet interatomic potentials must be fit to secondary physical properties. To isolate the important factors that interatomic potentials must capture in order to accurately model such behavior, the performance of four interatomic potentials was evaluated for the Cu-Zr system, with experimental observations used to provide validation. While experimental results show strong Zr segregation to grain boundary regions and the formation of nanoscale amorpho…
Amorphous phosphorus (a-P) has long attracted interest because of its complex atomic structure, and more recently as an anode material for batteries. However, accurately describing and understanding a-P at the atomistic level remains a challenge. Here we show that large-scale molecular-dynamics simulations, enabled by a machine learning (ML)-based interatomic potential for phosphorus, can give new insights into the atomic structure of a-P and how this structure changes under pressure. The structural model so obtained contains abundant five-membered rings, as well as more complex seven- and eig…
Grain boundary engineering via dopant segregation can dramatically change the properties of a material. For metallic systems, most current studies concerning interfacial segregation and subsequent transitions of grain boundary structure are limited to binary alloys, yet many important alloy systems contain more than one type of dopant. In this work, hybrid Monte Carlo/molecular dynamics simulations are performed to investigate the behavior of dopants at interfaces in two model ternary alloy systems: Cu-Zr-Ag and Al-Zr-Cu. Trends in boundary segregation are studied, as well as the propensity fo…
Recently (C.-T. Toh et al., Nature 577, 199 (2020)), the first synthesis of free-standing monolayer amorphous carbon (MAC) was achieved. MAC is a pure carbon structure composed of five, six, seven and eight atom rings randomly distributed. MAC proved to be surprisingly stable and highly fracture resistant. Its electronic properties are similar to boron nitride. In this work, we have investigated the mechanical properties and thermal stability of MAC models using fully-atomistic reactive molecular dynamics simulations. For comparison purposes, the results are contrasted against pristine graphen…
Crystalline and amorphous nanoparticles of silicon in thin silica layers were examined by transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS) and x-ray photoelectron spectroscopy (XPS). We used XPS data in the form of the Auger parameter to separate initial and final state contributions to the Si$_{2p}$ energy shift. The electrostatic charging and electron screening issues as well as initial state effects were also addressed. We show that the chemical shift in the nanocrystals is determined by initial state rather than final state effects, and that the electron scr…
We demonstrate that the amorphous material PAF-1, C[(C6H4)2]2, forms a continuous random network in which tetrahedral carbon sites are connected by 4,4'-biphenyl linkers. Experimental neutron total scattering measurements on deuterated, hydrogenous, and null-scattering samples agree with molecular dynamics simulations based on this model. From the MD model, we are able for the first time to interrogate the atomistic structure. The small-angle scattering is consistent with Porod scattering from particle surfaces, of the form Q^{-4}, where Q is the scattering vector. We measure a distinct peak i…
Chalcogenide phase-change materials (PCMs) show a significant contrast in optical reflectivity and electrical resistivity upon crystallization from the amorphous phase and are leading candidates for non-volatile photonic and electronic applications. In addition to the flagship Ge2Sb2Te5 phase-change alloy, doped Sb2Te alloys, in particular AgInSbTe used in rewritable optical discs, have been widely investigated for decades, and nevertheless the theoretical insights on the optical properties of this important family of PCMs are scarce. Here, we carry out thorough ab initio simulations to gain a…
Machine-learned potential for amorphous Indium-Tin-Oxide alloys
Center for Alloy Innovation and Design (CAID), State Key Laboratory for Mechanical Behavior of Materials, Xi’an Jiaotong University（西安交通大学合金创新与设计中心、材料力学行为国家重点实验室）
We review the recent literature on the simulation of the structure and deformation of amorphous glasses, including oxide and metallic glasses. We consider simulations at different length and time scales. At the nanometer scale, we review studies based on atomistic simulations, with a particular emphasis on the role of the potential energy landscape and of the temperature. At the micrometer scale, we present the different mesoscopic models of amorphous plasticity and show the relation between shear banding and the type of disorder and correlations (e.g. elastic) included in the models. At the m…
