Machine learnt bond order potential to model metal-organic (Co-C) heterostructures.

A fundamental understanding of the inter-relationships between structure, morphology, atomic scale dynamics, chemistry, and physical properties of mixed metallic-covalent systems is essential to design novel functional materials for applications in flexible nano-electronics, energy storage and catalysis. To achieve such knowledge, it is imperative to develop robust and computationally efficient atomistic models that describe atomic interactions accurately within a single framework. Here, we present a unified Tersoff-Brenner type bond order potential (BOP) for a Co-C system, trained against lattice parameters, cohesive energies, equation of state, and elastic constants of different crystalline phases of cobalt as well as orthorhombic Co2C derived from density functional theory (DFT) calculations. The independent BOP parameters are determined using a combination of supervised machine learning (genetic algorithms) and local minimization via the simplex method. Our newly developed BOP accurately describes the structural, thermodynamic, mechanical, and surface properties of both the elemental components as well as the carbide phases, in excellent accordance with DFT calculations and experiments. Using our machine-learnt BOP potential, we performed large-scale molecular dynamics simulations to investigate the effect of metal/carbon concentration on the structure and mechanical properties of porous architectures obtained via self-assembly of cobalt nanoparticles and fullerene molecules. Such porous structures have implications in flexible electronics, where materials with high electrical conductivity and low elastic stiffness are desired. Using unsupervised machine learning (clustering), we identify the pore structure, pore-distribution, and metallic conduction pathways in self-assembled structures at different C/Co ratios. We find that as the C/Co ratio increases, the connectivity between the Co nanoparticles becomes limited, likely resulting in low electrical conductivity; on the other hand, such C-rich hybrid structures are highly flexible (i.e., low stiffness). The BOP model developed in this work is a valuable tool to investigate atomic scale processes, structure-property relationships, and temperature/pressure response of Co-C systems, as well as design organic-inorganic hybrid structures with a desired set of properties.

Unraveling the Planar-Globular Transition in Gold Nanoclusters through Evolutionary Search.

Au nanoclusters are of technological relevance for catalysis, photonics, sensors, and of fundamental scientific interest owing to planar to globular structural transformation at an anomalously high number of atoms i.e. in the range 12-14. The nature and causes of this transition remain a mystery. In order to unravel this conundrum, high throughput density functional theory (DFT) calculations, coupled with a global structural optimization scheme based on a modified genetic algorithm (GA) are conducted. More than 20,000 Au12, Au13, and Au14 nanoclusters are evaluated. With any DFT functional, globular and planar structures coexist across the size range of interest. The planar-globular transition is gradual at room temperature rather than a sharp transition as previously believed. The effects of anionicity, s-d band hybridization and long range interactions on the dimensional transition are quantified by using the structures adjacent to the minima. Anionicity marginally changes the relative stability of the clusters. The degree of s-d hybridization is varied via changing the Hubbard U value which corroborate that s-d hybridization alone does not stabilize planar structures. van der Waals interactions, on the other hand, stabilize globular structures. These results elucidate the balance between the different reasons of the dimensional transition in gold nanoclusters.

Ab Initio-Based Bond Order Potential to Investigate Low Thermal Conductivity of Stanene Nanostructures.

We introduce a bond order potential (BOP) for stanene based on an ab initio derived training data set. The potential is optimized to accurately describe the energetics, as well as thermal and mechanical properties of a free-standing sheet, and used to study diverse nanostructures of stanene, including tubes and ribbons. As a representative case study, using the potential, we perform molecular dynamics simulations to study stanene's structure and temperature-dependent thermal conductivity. We find that the structure of stanene is highly rippled, far in excess of other 2-D materials (e.g., graphene), owing to its low in-plane stiffness (stanene: ∼ 25 N/m; graphene: ∼ 480 N/m). The extent of stanene's rippling also shows stronger temperature dependence compared to that in graphene. Furthermore, we find that stanene based nanostructures have significantly lower thermal conductivity compared to graphene based structures owing to their softness (i.e., low phonon group velocities) and high anharmonic response. Our newly developed BOP will facilitate the exploration of stanene based low dimensional heterostructures for thermoelectric and thermal management applications.

Visualizing Redox Dynamics of a Single Ag/AgCl Heterogeneous Nanocatalyst at Atomic Resolution.

Operando characterization of gas-solid reactions at the atomic scale is of great importance for determining the mechanism of catalysis. This is especially true in the study of heterostructures because of structural correlation between the different parts. However, such experiments are challenging and have rarely been accomplished. In this work, atomic scale redox dynamics of Ag/AgCl heterostructures have been studied using in situ environmental transmission electron microscopy (ETEM) in combination with density function theory (DFT) calculations. The reduction of Ag/AgCl to Ag is likely a result of the formation of Cl vacancies while Ag(+) ions accept electrons. The oxidation process of Ag/AgCl has been observed: rather than direct replacement of Cl by O, the Ag/AgCl nanocatalyst was first reduced to Ag, and then Ag was oxidized to different phases of silver oxide under different O2 partial pressures. Ag2O formed at low O2 partial pressure, whereas AgO formed at atmospheric pressure. By combining in situ ETEM observation and DFT calculations, this structural evolution is characterized in a distinct nanoscale environment.

Thermal transport properties of MoS2 and MoSe2 monolayers.

The isolation of single- to few-layer transition metal dichalcogenides opens new directions in the application of two-dimensional materials to nanoelectronics. The characterization of thermal transport in these new low-dimensional materials is needed for their efficient implementation, either for general overheating issues or specific applications in thermoelectric devices. In this study, the lattice thermal conductivities of single-layer MoS2 and MoSe2 are evaluated using classical molecular dynamics methods. The interactions between atoms are defined by Stillinger-Weber-type empirical potentials that are developed to represent the structural, mechanical, and vibrational properties of the given materials. In the parameterization of the potentials, a stochastic optimization algorithm, namely particle swarm optimization, is utilized. The final parameter sets produce quite consistent results with density functional theory in terms of lattice parameters, bond distances, elastic constants, and vibrational properties of both single-layer MoS2 and MoSe2. The predicted thermal properties of both materials are in very good agreement with earlier first-principles calculations. The discrepancies between the calculations and experimental measurements are most probably caused by the pristine nature of the structures in our simulations.

First-Principles Analysis of Defect Thermodynamics and Ion Transport in Inorganic SEI Compounds: LiF and NaF.

The formation mechanism and composition of the solid electrolyte interphase (SEI) in lithium ion batteries has been widely explored. However, relatively little is known about the function of the SEI as a transport medium. Such critical information is directly relevant to battery rate performance, power loss, and capacity fading. To partially bridge this gap in the case of inorganic SEI compounds, we report herein the results of first-principles calculations on the defect thermodynamics, the dominant diffusion carriers, and the diffusion pathways associated with crystalline LiF and NaF, which are stable components of the SEI in Li-ion and Na-ion batteries, respectively. The thermodynamics of common point defects are computed, and the dominant diffusion carriers are determined over a voltage range of 0-4 V, corresponding to conditions relevant to both anode and cathode SEI's. Our analyses reveal that for both compounds, vacancy defects are energetically more favorable, therefore form more readily than interstitials, due to the close-packed nature of the crystal structures. However, the vacancy concentrations are very small for the diffusion processes facilitated by defects. Ionic conductivities are calculated as a function of voltage, considering the diffusion carrier concentration and the diffusion barriers as determined by nudged elastic band calculations. These conductivities are more than ten orders of magnitude smaller in NaF than in LiF. As compared to the diffusivity of Li in other common inorganic SEI compounds, such as Li2CO3 and Li2O, the cation diffusivity in LiF and NaF is quite low, with at least three orders of magnitude lower ionic conductivities. The results quantify the extent to which fluorides pose rate limitations in Li and Na batteries.

First-principles analysis of defect-mediated Li adsorption on graphene.

To evaluate the possible utility of single layer graphene for applications in Li ion batteries, an extensive series of periodic density functional theory (DFT) calculations are performed on graphene sheets with both point and extended defects for a wide range of lithium coverages. Consistent with recent reports, it is found that Li adsorption on defect-free single layer graphene is not thermodynamically favorable compared to bulk metallic Li. However, graphene surfaces activated by defects are generally found to bind Li more strongly, and the interaction strength is sensitive to both the nature of the defects and their densities. Double vacancy defects are found to have much stronger interactions with Li as compared to Stone-Wales defects, and increasing defect density also enhances the interaction of the Stone-Wales defects with Li. Li interaction with one-dimensional extended defects on graphene is additionally found to be strong and leads to increased Li adsorption. A rigorous thermodynamic analysis of these data establishes the theoretical Li storage capacities of the defected graphene structures. In some cases, these capacities are found to approach, although not exceed, those of graphite. The results provide new insights into the fundamental physics of adsorbate interactions with graphene defects and suggest that careful defect engineering of graphene might, ultimately, provide anode electrodes of suitable capacity for lithium ion battery applications.

Defect evolution in graphene upon electrochemical lithiation.

Despite rapidly growing interest in the application of graphene in lithium ion batteries, the interaction of the graphene with lithium ions and electrolyte species during electrochemical cycling is not fully understood. In this work, we use Raman spectroscopy in a model system of monolayer graphene transferred on a Si(111) substrate and density functional theory (DFT) to investigate defect formation as a function of lithiation. This model system enables the early stages of defect formation to be probed in a manner previously not possible with commonly used reduced graphene oxide or multilayer graphene substrates. Using ex situ and Ar-atmosphere Raman spectroscopy, we detected a rapid increase in graphene defect level for small increments in the number of lithiation/delithiation cycles until the I(D)/I(G) ratio reaches ∼1.5-2.0 and the 2D peak intensity drops by ∼50%, after which the Raman spectra show minimal changes upon further cycling. Using DFT, the interplay between graphene topological defects and chemical functionalization is explored, thus providing insight into the experimental results. In particular, the DFT results show that defects can act as active sites for species that are present in the electrochemical environment such as Li, O, and F. Furthermore, chemical functionalization with these species lowers subsequent defect formation energies, thus accelerating graphene degradation upon cycling. This positive feedback loop continues until the defect concentration reaches a level where lithium diffusion through the graphene can occur in a relatively unimpeded manner, with minimal further degradation upon extended cycling. Overall, this study provides mechanistic insight into graphene defect formation during lithiation, thus informing ongoing efforts to employ graphene in lithium ion battery technology.

Equilibrium limit of thermal conduction and boundary scattering in nanostructures.

Determining the lattice thermal conductivity (κ) of nanostructures is especially challenging in that, aside from the phonon-phonon scattering present in large systems, the scattering of phonons from the system boundary greatly influences heat transport, particularly when system length (L) is less than the average phonon mean free path (MFP). One possible route to modeling κ in these systems is through molecular dynamics (MD) simulations, inherently including both phonon-phonon and phonon-boundary scattering effects in the classical limit. Here, we compare current MD methods for computing κ in nanostructures with both L ⩽ MFP and L ≫ MFP, referred to as mean free path constrained (cMFP) and unconstrained (uMFP), respectively. Using a (10,0) CNT (carbon nanotube) as a benchmark case, we find that while the uMFP limit of κ is well-defined through the use of equilibrium MD and the time-correlation formalism, the standard equilibrium procedure for κ is not appropriate for the treatment of the cMFP limit because of the large influence of boundary scattering. To address this issue, we define an appropriate equilibrium procedure for cMFP systems that, through comparison to high-fidelity non-equilibrium methods, is shown to be the low thermal gradient limit to non-equilibrium results. Further, as a means of predicting κ in systems having L ≫ MFP from cMFP results, we employ an extrapolation procedure based on the phenomenological, boundary scattering inclusive expression of Callaway [Phys. Rev. 113, 1046 (1959)]. Using κ from systems with L ⩽ 3 µm in the extrapolation, we find that the equilibrium uMFP κ of a (10,0) CNT can be predicted within 5%. The equilibrium procedure is then applied to a variety of carbon-based nanostructures, such as graphene flakes (GF), graphene nanoribbons (GNRs), CNTs, and icosahedral fullerenes, to determine the influence of size and environment (suspended versus supported) on κ. Concerning the GF and GNR systems, we find that the supported samples yield consistently lower values of κ and that the phonon-boundary scattering remains dominant at large lengths, with L = 0.4 µm structures exhibiting a third of the periodic result. We finally characterize the effect of shape in CNTs and fullerenes on κ, showing the angular components of conductivity in CNTs and icosahedral fullerenes are similar for a given circumference.

Control of thermal and electronic transport in defect-engineered graphene nanoribbons.

The influence of the structural detail and defects on the thermal and electronic transport properties of graphene nanoribbons (GNRs) is explored by molecular dynamics and non-equilibrium Green's function methods. A variety of randomly oriented and distributed defects, single and double vacancies, Stone-Wales defects, as well as two types of edge form (armchair and zigzag) and different edge roughnesses are studied for model systems similar in sizes to experiments (>100 nm long and >15 nm wide). We observe substantial reduction in thermal conductivity due to all forms of defects, whereas electrical conductance reveals a peculiar defect-type-dependent response. We find that a 0.1% single vacancy concentration and a 0.23% double vacancy or Stone-Wales concentration lead to a drastic reduction in thermal conductivity of GNRs, namely, an 80% reduction from the pristine one of the same width. Edge roughness with an rms value of 7.28 Å leads to a similar reduction in thermal conductivity. Randomly distributed bulk vacancies are also found to strongly suppress the ballistic nature of electrons and reduce the conductance by 2 orders of magnitude. However, we have identified that defects close to the edges and relatively small values of edge roughness preserve the quasi-ballistic nature of electronic transport. This presents a route of independently controlling electrical and thermal transport by judicious engineering of the defect distribution; we discuss the implications of this for thermoelectric performance.