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Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. Our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results., Comment: 42 pages, 8 figures, 6 tables. In review for a special issue in J. Chem. Phys

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ∼0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

Density Functional Tight Binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard Density Functional Theory approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. We have focused our workflow on TiH$_2$ as a model system and show that a relatively small training set based on unit-cell sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield accurate DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results., Comment: 45 pages, 7 tables, 7 figures. New version contains updated figures and light editorial changes. This version has been submitted as a revision to J Chem. Theory Comput

Postsynthetic strategies for modifying metal-organic frameworks (MOFs) have proven to be an incredibly powerful approach for expanding the scope and functionality of these materials. Previously, we reported on the postsynthetic exchange (PSE) of metal ions and ligands in the University of Oslo (UiO) series of MOFs. Detailed characterization by several analytical methods, most notably inductively coupled plasma mass spectrometry (ICP-MS) and transmission electron microscopy (TEM) reveal that metal ion deposition on the surface of these MOFs occurs in the form of nanoscale metal oxides, rather than yielding exchanged metal sites within the MOFs, as was previously reported. By contrast, these combined analytical methods do confirm that ligand-based PSE can occur in these MOFs. These findings provide new insight into the postsynthetic manipulation of MOF materials, highlight the importance of rigorously characterizing these materials to correctly assign their composition and structure, and provide a new route to making hybrid solids with a MOF@metal oxide architecture.

Metal-organic frameworks (MOFs) have emerged as a versatile platform for the rational design of multifunctional materials, combining large specific surface areas with flexible, periodic frameworks that can undergo reversible structural transitions, or "breathing", upon temperature and pressure changes, and through gas adsorption/desorption processes. Although MOF breathing can be inferred from the analysis of adsorption isotherms, direct observation of the structural transitions has been lacking, and the underlying processes of framework reorganization in individual MOF nanocrystals is largely unknown. In this study, we describe the characterization and elucidation of these processes through the combination of in situ environmental transmission electron microscopy (ETEM) and computer simulations. This combined approach enables the direct monitoring of the breathing behavior of individual MIL-53(Cr) nanocrystals upon reversible water adsorption and temperature changes. The ability to characterize structural changes in single nanocrystals and extract lattice level information through in silico correlation provides fundamental insights into the relationship between pore size/shape and host-guest interactions.

The spin-crossover behavior of the {Fe(pz)[Pt(CN)4]} metal–organic framework (MOF) upon pyrazine adsorption is investigated through hybrid Monte Carlo/molecular dynamics (MC/MD) simulations. In contrast to previous theoretical studies, which reported a transition temperature of ∼140 K, the present MC/MD simulations predict that the high-spin state is the most stable state at all temperatures, in agreement with the experimental observations. The MC/MD simulations also indicate that the pyrazine molecules adsorbed in the MOF pores lie nearly parallel but staggered by 60° relative to the pyrazine ligands of the framework. The analysis of the magnetization curve as a function of the temperature demonstrates that the staggered configuration assumed by the guest pyrazine molecules within the framework is responsible for the stabilization of the high-spin state. Both the guest pyrazine molecules and the pyrazine ligands of the framework are effectively locked into the minimum-energy configuration and do not disp...

Computer simulations are carried out to characterize the variation of spin crossover (SCO) behavior of the prototypical {Fe(pz)[Pt(CN)4]} metal-organic framework (MOF) upon adsorption of chemically and structurally different guest molecules. A detailed analysis of both strength and anisotropy of guest molecule-framework interactions reveals direct correlations between the mobility of the guest molecules inside the MOF pores, the rotational mobility of the pyrazine rings of the framework, and the stabilization of the low-spin state of the material. Based on these correlations, precise molecular criteria are established for predicting the spin state of {Fe(pz)[Pt(CN)4]} upon guest adsorption. Finally, predictions of the SCO temperature upon adsorption of various toxic gases demonstrate that in silico modeling can provide fundamental insights and design principles for the development of spin-crossover MOFs for applications in gas detection and chemical sensing.

Computer simulations are carried out to characterize the variation of spin crossover (SCO) behavior of the prototypical {Fe(pz)[Pt(CN)4]} metal-organic framework (MOF) upon adsorption of chemically and structurally different guest molecules. A detailed analysis of both strength and anisotropy of guest molecule-framework interactions reveals direct correlations between the mobility of the guest molecules inside the MOF pores, the rotational mobility of the pyrazine rings of the framework, and the stabilization of the low-spin state of the material. Based on these correlations, precise molecular criteria are established for predicting the spin state of {Fe(pz)[Pt(CN)4]} upon guest adsorption. Finally, predictions of the SCO temperature upon adsorption of various toxic gases demonstrate that in silico modeling can provide fundamental insights and design principles for the development of spin-crossover MOFs for applications in gas detection and chemical sensing.

Conformation-specific direct interfacial electron transfer is observed by the first ultrafast electric field–induced VSFG., The ability to control direct electron transfer can facilitate the development of new molecular electronics, light-harvesting materials, and photocatalysis. However, control of direct electron transfer has been rarely reported, and the molecular conformation–electron dynamics relationships remain unclear. We describe direct electron transfer at buried interfaces between an organic polymer semiconductor film and a gold substrate by observing the first dynamical electric field–induced vibrational sum frequency generation (VSFG). In transient electric field–induced VSFG measurements on this system, we observe dynamical responses (

Many-body effects in ice are investigated through a systematic analysis of the lattice energies of several proton ordered and disordered phases, which are calculated with different flexible water models, ranging from pairwise additive (q-TIP4P/F) to polarizable (TTM3-F and AMOEBA) and explicit many-body (MB-pol) potential energy functions. Comparisons with available experimental and diffusion Monte Carlo data emphasize the importance of an accurate description of the individual terms of the many-body expansion of the interaction energy between water molecules for the correct prediction of the energy ordering of the ice phases. Further analysis of the MB-pol results, in terms of fundamental energy contributions, demonstrates that the differences in lattice energies between different ice phases are sensitively dependent on the subtle balance between short-range two-body and three-body interactions, many-body induction, and dispersion energy. By correctly reproducing many-body effects at both short range and long range, it is found that MB-pol accurately predicts the energetics of different ice phases, which provides further support for the accuracy of MB-pol in representing the properties of water from the gas to the condensed phase.

Energy band structure of the bilayer graphene superlattices with zero-averaged periodic $\delta$-function potentials are studied within the four-band continuum model. Using the transfer matrix method, studies are mainly focused on examining the touching points between adjacent minibands. For the zero-energy touching points the dispersion relation derived shows the Dirac-like double-cone shape with the group velocity which is periodic in the potential strength $P$ with the period of $\pi$ and becomes anisotropic at relatively large $P$. From the finite-energy touching points we have identified those located at zero wave-number. It was shown that for these finite-energy touching points the dispersion is direction-dependent in the sense that it is linear or parabolic in the direction parallel or perpendicular to the superlattice direction, respectively. We have also calculated the density of states and the conductivity that demonstrate a manifestation of the touching points of interest., Comment: Submitted to JPCM

The MB-pol many-body potential has recently emerged as an accurate molecular model for water simulations from the gas to the condensed phase. In this study, the accuracy of MB-pol is systematically assessed across the three phases of water through extensive comparisons with experimental data and high-level ab initio calculations. Individual many-body contributions to the interaction energies as well as vibrational spectra of water clusters calculated with MB-pol are in excellent agreement with reference data obtained at the coupled cluster level. Several structural, thermodynamic, and dynamical properties of the liquid phase at atmospheric pressure are investigated through classical molecular dynamics simulations as a function of temperature. The structural properties of the liquid phase are in nearly quantitative agreement with X-ray diffraction data available over the temperature range from 268 to 368 K. The analysis of other thermodynamic and dynamical quantities emphasizes the importance of explicitly including nuclear quantum effects in the simulations, especially at low temperature, for a physically correct description of the properties of liquid water. Furthermore, both densities and lattice energies of several ice phases are also correctly reproduced by MB-pol. Following a recent study of DFT models for water, a score is assigned to each computed property, which demonstrates the high and, in many respects, unprecedented accuracy of MB-pol in representing all three phases of water.

Using the T-matrix approach, we study the effect of a Kronig–Penney periodic potential on the electronic states and the transport properties of graphene. The energy band structure and the group velocity of charge carriers are calculated and discussed in detail for potentials with varying amplitudes and barrier-to-well width ratios. The periodic potential is shown to cause a resonant structure and to enhance the magnitude of the conductivity.

An exact expression of the transmission probability through a finite graphene superlattice with an arbitrary number of potential barriers $n$ is derived in two cases of the periodic potential: rectangular electric potential and $\delta$-function magnetic potential. Obtained transmission probabilities show two types of resonance energy: barrier-induced resonance energies unchanged as $n$ varies and well-induced resonance energies undergone the $(n - 1)$-fold splitting as $n$ increases. Supported by numerical calculations for various types of graphene superlattices, these analytical findings are assumed to be in equal applied to all of finite graphene superlattices regardless of potential natures [electric or magnetic] as well as potential barrier shapes., Comment: 21 pages, 6 figures

Energy band structure of the bilayer graphene superlattices with $\delta$-function magnetic barriers and zero average magnetic flux is studied within the four-band continuum model, using the transfer matrix method. The periodic magnetic potential effects on the zero-energy Dirac point of pristine bilayer graphene are exactly analyzed. Magnetic potential is shown also to generate finite-energy Dirac points at the edges of Brillouin zone the positions of which and the related dispersions are determined in the case of symmetric potentials.

Using the nearest-neighbor tight-binding approach we study the electronic band structures of graphene nanoribbons with self-passivating edge reconstructions. For zigzag ribbons the edge reconstruction moves both the Fermi energy and the flat band down by several hundred meV, and the flat band is always found to be below the Fermi energy. The states featured by the flat band are shown to be mainly localized at the atoms belonging to several lattice lines closest to the edges. For armchair ribbons the edge reconstruction strongly modifies the band structure in the region close to the Fermi energy, leading to the appearance of a band gap even for ribbons which were predicted to be metallic in the model of standard armchair edges. The gap widths are, however, strongly different in magnitude and behave in different ways regarding the ribbon width.

In this letter, a dynamic generalization of static critical curves (sCCs) for synthetic antiferromagnet (SAF) structures is presented, analyzing the magnetization switching of SAF elements subjected to pulsed magnetic fields. The dependence of dynamic critical curves (dCCs) on field pulse’s shape and length, on damping, and on magnetostatic coupling is investigated. Comparing sCCs, which are currently used for studying the switching in toggle magnetic random access memories, with dCCs, it is shown that a consistent switching can be achieved only under specific conditions that take into account the dynamics of the systems. The study relies on the Landau–Lifshitz–Gilbert equation.