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This paper investigates the adsorption of carbon adatoms on graphene and its nanoribbons using first-principles plane wave calculations within density functional theory. The stability at high carbon adatom coverage, migration, and cluster formation of carbon atoms are analyzed. Carbon adatoms give rise to important changes in electronic and magnetic properties even at low coverage. While bare graphene is nonmagnetic semimetal, it is metallized and acquires magnetic moment upon coverage of carbon adatoms. Calculated magnetic moments vary depending on the coverage of adatoms even for large adatom-adatom distances. Electronic and magnetic properties of hydrogen passivated armchair and zigzag nanoribbons show strong dependence on the adsorption site. We also predict a new type of carbon impurity defect in graphene, which has a small formation energy. Interactions between distant carbon adatoms imply a long ranged interaction. [ABSTRACT FROM AUTHOR]

Based on first-principles density functional theory and finite temperature molecular dynamics calculations, we predict that H2O can be dissociated into its constituents O and H at specific vacancy defects of single-layer M0S2 honeycomb structure, which subsequently are bound to fourfolded Mo and twofolded S atoms surrounding the vacancy, respectively. This exothermic and spontaneous process occurs, since the electronegativity and ionization energy of Mo are smaller than those of H. Once desorbed from twofolded S atoms, H atoms migrate readily on the M0S2 surface and eventually form free H2 molecules to be released from the surface. Present results are critical for acquiring clean and sustainable energy from hydrogen. [ABSTRACT FROM AUTHOR]

The frequency-dependent optical spectrum is pivotal for a broad range of applications from material characterization to optoelectronics and energy harvesting. Data-driven surrogate models, trained on density functional theory (DFT) data, have effectively alleviated the scalability limitations of DFT while preserving its chemical accuracy, expediting material discovery. However, prevailing machine learning (ML) efforts often focus on scalar properties such as the band gap, overlooking the complexities of optical spectra. In this work, we employ deep graph neural networks (GNNs) to predict the frequency-dependent complex-valued dielectric function across the infrared, visible, and ultraviolet spectra directly from the crystal structures. We explore multiple architectures for the spectral multioutput representation of the dielectric function and utilize various multifidelity learning strategies, such as transfer learning and fidelity embedding, to address the challenges associated with the scarcity of high-fidelity DFT data. Additionally, we model key solar cell absorption efficiency metrics, demonstrating that learning these parameters is enhanced when integrated through a learning bias within the learning of the frequency-dependent absorption coefficient. This study demonstrates that leveraging multioutput and multifidelity ML techniques enables accurate predictions of optical spectra from crystal structures, providing a versatile tool for rapidly screening materials for optoelectronics, optical sensing, and solar energy applications across an extensive frequency spectrum.

Previous works have controversially claimed near-room-temperature ferromagnetism in two-dimensional (2D) VSe 2 , with conflicting results throughout the literature. These discrepancies in magnetic properties between both phases (T and H) of 2D VSe 2 are most likely due to the structural parameters being coupled to the magnetic properties. Specifically, both phases have a close lattice match and similar total energies, which makes it difficult to determine which phase is being observed experimentally. In this study, we used a combination of density functional theory, highly accurate diffusion Monte Carlo (DMC), and a surrogate Hessian line-search optimization technique to resolve the previously reported discrepancy in structural parameters and relative phase stability. With DMC accuracy, we determined the free-standing geometry of both phases and constructed a phase diagram. Our findings demonstrate the successes of the DMC method coupled with the surrogate Hessian structural optimization technique when applied to a 2D magnetic system.

The study of alloys using computational methods has been a difficult task due to the usually unknown stoichiometry and local atomic ordering of the different structures experimentally. In order to combat this, first-principles methods have been coupled with statistical methods such as the cluster expansion formalism in order to construct the energy hull diagram, which helps to determine if an alloyed structure can exist in nature. Traditionally, density functional theory (DFT) has been used in such workflows. In this paper, we propose to use chemically accurate many-body variational Monte Carlo (VMC) and diffusion Monte Carlo (DMC) methods to construct the energy hull diagram of an alloy system due to the fact that such methods have a weaker dependence on the starting wavefunction and density functional, scale similarly to DFT with the number of electrons, and have had demonstrated success for a variety of materials. To carry out these simulations in a high-throughput manner, we propose a method called Jastrow sharing, which involves recycling the optimized Jastrow parameters between alloys with different stoichiometries. We show that this eliminates the need for extra VMC Jastrow optimization calculations and results in significant computational cost savings (on average 1/4 savings of total computational time). Since it is a novel post-transition metal chalcogenide alloy series that has been synthesized in its few-layer form, we used monolayer GaS x Se 1-x as a case study for our workflow. By extensively testing our Jastrow sharing procedure for monolayer GaS x Se 1-x and quantifying the cost savings, we demonstrate how a pathway toward chemically accurate high-throughput simulations of alloys can be achieved using many-body VMC and DMC methods.

Low-dimensional organic-inorganic hybrid perovskites have attracted much interest owing to their superior solar conversion performance, environmental stability, and excitonic properties compared to their three-dimensional (3D) counterparts. Among reduced-dimensional perovskites, guanidinium-based perovskites crystallize in layered one-dimensional (1D) and two-dimensional (2D). Here, our studies demonstrate how the dimensionality of the hybrid perovskite influences the chemical and physical properties under different pressures (i.e., bond distance, angle, vdW distance). Comprehensive studies show that 1D GuaPbI 3 does not undergo a phase transition even up to high pressures (∼13 GPa) and its band gap monotonically reduces with pressure. In contrast, 2D Gua 2 PbI 4 exhibits an early phase transition at 5.5 GPa and its band gap follow nonmonotonic pressure response associated with phase transition as well as other bond angle changes. Computational simulations reveal that the phase transition is related to the structural deformation and rotation of PbI 6 octahedra in 2D Gua 2 PbI 4 owing to a larger degree of freedom of deformation. The soft lattice allows them to uptake large pressures, which renders structural phase transitions possible. Overall the results offer the first insights into how layered perovskites with different dimensionality respond to structural changes driven by pressure.

The structural asymmetry of two-dimensional (2D) Janus transition-metal dichalcogenides (TMDs) produces internal dipole moments that result in interesting electronic properties. These properties differ from the regular (symmetric) TMD structures that the Janus structures are derived from. In this study, we, first, examine adsorption and diffusion of a single Li atom on regular MX 2 and Janus MXY (M = Mo, W; XY = S, Se, Te) TMD structures at various concentrations using first-principles calculations within density functional theory. Lithium adsorption energy and mobility differ on the top and bottom sides of each Janus material. The correlation between Li adsorption energy, charge transfer, and bond lengths at different coverage densities is carefully examined. To gain more physical insight and prepare for future investigations into regular TMD and Janus materials, we applied a supervised machine learning (ML) model that uses clusterwise linear regression to predict the adsorption energies of Li on top of 2D TMDs. We developed a universal representation with a few descriptors that take into account the intrinsic dipole moment and the electronic structure of regular and Janus 2D layers, the side where the adsorption takes place, and the concentration dependence of adatom doping. This representation can easily be generalized to be used for other impurities and 2D layer combinations, including alloys as well. At last, we focus on analyzing these structures as possible anodes in battery applications. We conducted Li diffusion, open-circuit voltage, and storage capacity simulations. We report that lithium atoms are found to easily migrate between transition-metal (Mo, W) top sites for each considered case, and in these respects, many of the examined Janus materials are comparable or superior to graphene and regular TMDs. In addition, we report that the side with higher electronegative chalcogen atoms is suitable for Li adsorption and only MoSSe and MoSeTe can be suitable for full coverage of Li atoms on the surface. Bilayer Li adsorption was hindered due to negative open-circuit voltage. Bilayer Janus structures are better suited for battery applications due to less volumetric expansion/contraction during the discharge/charge process and having higher storage capacity. Janus monolayers undergo a transition from semiconducting to metallic upon adsorption of a single Li ion, which would improve anode conductivity. The results imply that the examined Janus structures should perform well as electrodes in Li-ion batteries.

In this manuscript, we combine experimental and computational approaches to study the atomic layer deposition (ALD) of dielectrics on MoS 2 surfaces for a very common class of ALD precursors, the alkylamines. More specifically, we study the thermal ALD of TiO 2 from TDMAT and H 2 O. Depositions on as-produced chemical vapor deposition MoS 2 flakes result in discontinuous films. Surface treatment with mercaptoethanol (ME) does not improve the surface coverage, and DFT calculations show that ME reacts very weakly with the MoS 2 surface. However, creation of sulfur vacancies on the MoS 2 surface using Ar ion beam irradiation results in much improved surface coverage for films with a nominal thickness of 6 nm, and the calculations show that TDMAT reacts moderately with either single or extended sulfur vacancies. ME also reacts with the vacancies, and defect-rich surfaces treated with ME provide an equally good surface for the nucleation of ALD TiO 2 films. The computational studies however reveal that the creation of surface vacancies results in the introduction of gap states that may deteriorate the electronic properties of the stack. Treatment with ME results in the complete removal of the gap states originating from the most commonly found single vacancies and reduces substantially the density of states for double and line vacancies. As a result, we provide a pathway for the deposition of high-quality ALD dielectrics on the MoS 2 surfaces, which is required for the successful integration of these 2D materials in functional devices.

Two-dimensional (2D) post-transition metal chalcogenides (PTMCs) have attracted attention due to their suitable bandgaps and lower exciton binding energies, making them more appropriate for electronic, optical, and water-splitting devices than graphene and monolayer transition metal dichalcogenides. Of the predicted 2D PTMCs, GaSe has been reliably synthesized and experimentally characterized. Despite this fact, quantities such as lattice parameters and band character vary significantly depending on which density functional theory (DFT) functional is used. Although many-body perturbation theory (GW approximation) has been used to correct the electronic structure and obtain the excited state properties of 2D GaSe, and solving the Bethe-Salpeter equation (BSE) has been used to find the optical gap, we find that the results depend strongly on the starting wavefunction. In an attempt to correct these discrepancies, we employed the many-body Diffusion Monte Carlo (DMC) method to calculate the ground and excited state properties of GaSe because DMC has a weaker dependence on the trial wavefunction. We benchmark these results with available experimental data, DFT [local-density approximation, Perdew-Burke-Ernzerhof (PBE), strongly constrained and appropriately normed (SCAN) meta-GGA, and hybrid (HSE06) functionals] and GW-BSE (using PBE and SCAN wavefunctions) results. Our findings confirm that monolayer GaSe is an indirect gap semiconductor (Γ-M) with a quasiparticle electronic gap in close agreement with experiment and low exciton binding energy. We also benchmark the optimal lattice parameter, cohesive energy, and ground state charge density with DMC and various DFT methods. We aim to present a terminal theoretical benchmark for pristine monolayer GaSe, which will aid in the further study of 2D PTMCs using DMC methods.

Recently, two-dimensional (2D) group-III nitride semiconductors such as h-BN, h-AlN, h-GaN, and h-InN have attracted attention because of their exceptional electronic, optical, and thermoelectric properties. It has also been demonstrated, theoretically and experimentally, that properties of 2D materials can be controlled by alloying. In this study, we performed density functional theory (DFT) calculations to investigate 2D B 1- x Al x N, Al 1- x Ga x N, and Ga 1- x In x N alloyed structures. We also calculated the thermoelectric properties of these structures using Boltzmann transport theory based on DFT and the optical properties using the GW method and the Bethe-Salpeter equation. We find that by changing the alloying concentration, the band gap and exciton binding energies of each structure can be tuned accordingly, and for certain concentrations, a high thermoelectric performance is reported with strong dependence on the effective mass of the given alloyed monolayer. In addition, the contribution of each e-h pair is explained by investigating the e-h coupling strength projected on the electronic band structure, and we find that the exciton binding energy decreases with increase in sequential alloying concentration. With the ability to control such properties by alloying 2D group-III nitrides, we believe that this work will play a crucial role for experimentalists and manufacturers focusing on next-generation electronic, optoelectronic, and thermoelectric devices.

Recently, 2D tellurene (Te) structures have been experimentally synthesized. These structures possess high carrier mobility and stability which make them ideal candidates for applications in electronics, optoelectronics and energy devices. We performed density functional theory (DFT) and molecular dynamics (MD) simulations to investigate the stability and electronic structure of 2D α- and β-Te sheets, and hydrogen, oxygen, and fluorine functionalized counterparts, including spin-orbit coupling effects. Our calculations show that bare α and β-Te sheets are stable with band gaps of 0.44 eV and 1.02 eV respectively. When functionalized, α and β monolayers exhibit metallic properties, except for hydrogenated β-Te, which exhibits semiconducting properties with a band gap of 1.37 eV. We see that H, O and F destabilize the structure of α-Te. We also find that F and H cause β-Te layers to separate into functionalized atomic chains and O causes β-Te to transform into a Te3O2-like structure. We also studied single atom and molecule binding on the Te surface, the effects of adatom coverage, and the effects of functionalized Te on a GaSe substrate. Our results indicate that tellurene monolayers and functionalized counterparts are not only suitable for future optoelectronic devices, but can be used as metallic contacts in nanoscale junctions.

The application of high pressure allows control over the unit cell and interatomic spacing of materials without any need for new growth methods or processing while accessing their materials properties in situ. Under these extreme pressures, materials may assume new structural phases and reveal novel properties. Here, unusual phase transition and band renormalization effects in 2D van der Waals Ruddlesden-Popper hybrid lead halide perovskites, which have shown extraordinary optical properties and immense potential in light emission and conversion technologies, are reported. The results show that (CH 3 (CH 2 ) 3 NH 3 ) 2 (CH 3 NH 3 )Pb 2 Br 7 (n = 2) layers undergo two distinct phase transitions related to PbBr 6 octahedra, butylammonium (BA), and methylammonium (MA) molecule tilting motion that leads to rather unique/anomalous bandgap variation with pressure. In contrast, (CH 3 (CH 2 ) 3 NH 3 )PbBr 4 (n = 1) lacks MA molecules and possesses only one pressure-induced phase transition related to PbBr 6 octahedra and BA tilting. In this range, the bandgap reduces monotonically, much similar to other inorganic semiconductors and display surprisingly large redshift from 3 to 2.4 eV. Together with theoretical calculations, this study offers unique insights into these pressure-induced changes and extends the understanding of these highly anisotropic layered soft organic perovskite materials under extreme conditions., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Neutral molecules with sufficiently large dipole moments can bind electrons in diffuse nonvalence orbitals with most of their charge density far from the nuclei, forming so-called dipole-bound anions. Because long-range correlation effects play an important role in the binding of an excess electron and overall binding energies are often only on the order of 10s-100s of wave numbers, predictively modeling dipole-bound anions remains a challenge. Here, we demonstrate that quantum Monte Carlo methods can accurately characterize molecular dipole-bound anions with near-threshold dipole moments. We also show that correlated sampling Auxiliary Field Quantum Monte Carlo is particularly well-suited for resolving the fine energy differences between the neutral and anionic species. These results shed light on the fundamental limitations of quantum Monte Carlo methods and pave the way toward using them for the study of weakly bound species that are too large to model using traditional electron structure methods.