Excitons and their Fine Structure in Lead Halide Perovskite Nanocrystals from Atomistic GW/BSE Calculations

Atomistically detailed computational studies of nanocrystals, such as those derived from the promising lead-halide perovskites, are challenging due to the large number of atoms and lack of symmetries to exploit. Here, focusing on methylammonium lead iodide nanocrystals, we combine a real-space tight binding model with the GW approximation to the self-energy and obtain exciton wavefunctions and absorption spectra via solutions of the associated Bethe-Salpeter equation. We find that the size dependence of carrier confinement, dielectric contrast, electron-hole exchange, and exciton binding energies has a strong impact on the lowest excitation energy, which can be tuned by almost 1 eV over the diameter range of 2-6 nm. Our calculated excitation energies are about 0.2 eV higher than experimentally measured photoluminescence, and they display the same qualitative size dependence. Focusing on the fine structure of the band-edge excitons, we find that the lowest-lying exciton is spectroscopically dark and about 20-30 meV lower in energy than the higher-lying triplet of bright states, whose degeneracy is slightly broken by crystal field effects.Comment: 8 pages, 4 figure

Dielectric disorder in two-dimensional materials

Understanding and controlling disorder is key to nanotechnology and materials science. Traditionally, disorder is attributed to local fluctuations of inherent material properties such as chemical and structural composition, doping or strain. Here, we present a fundamentally new source of disorder in nanoscale systems that is based entirely on the local changes of the Coulomb interaction due to fluctuations of the external dielectric environment. Using two-dimensional semiconductors as prototypes, we experimentally monitor dielectric disorder by probing the statistics and correlations of the exciton resonances, and theoretically analyse the influence of external screening and phonon scattering. Even moderate fluctuations of the dielectric environment are shown to induce large variations of the bandgap and exciton binding energies up to the 100 meV range, often making it a dominant source of inhomogeneities. As a consequence, dielectric disorder has strong implications for both the optical and transport properties of nanoscale materials and their heterostructures

Semiempirical methods for excited states of nanomaterials

Density functional theory (DFT) provides an affordable computational tool to understand electronic structure of various molecules and solids. However, the use of DFT is still challenging to investigate nanomaterials of intermediate size that are too small to assume translational symmetry and too large to be considered as molecules. This thesis focuses on developing cost-effective but accurate computational methods for nanomaterials and using the methods to rationalize and predict experimental behaviors. A notable difference of a nanomaterial from its bulk counterpart is that its properties are exceptionally sensitive to the dielectric environment, requiring a proper treatment of the surrounding dielectrics for an accurate understanding. The consequences of heterogeneous dielectric screening on transition metal dichalcogenides are studied by developing a new theory based on classical electrostatics, which closely reproduced the band gaps and optical gaps calculated by the ab initio GW approximation and the Bethe-Salpeter equation (BSE). The relative insensitivity of the first optical transition energy observed by experiments was explained for the first time in terms of the cancellation effect of changes of the band gap and the exciton binding energy. The theory of heterogeneous dielectric environments is further developed to be used in an atomistic calculation of layered hybrid organic-inorganic lead halide perovskites via a tight-binding GW-BSE method. The binding energies of trions and biexcitons were also calculated using the stochastic variational method to give spectrum peak energies that show a good agreement with reported experimental measurements. Lastly, the tight-binding GW-BSE method is generalized into an atomistic, semiempirical approach to calculate the electronic structure and optical spectra of arbitrary nanomaterials, termed semiempirical GW (sGW) and BSE (sBSE)

Improving Gas Adsorption Modeling for MOFs by Local Calibration of Hubbard U Parameters

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal-organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, that hinder predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule–MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation (MAD) of adsorption energies reduces from 0.13 eV for a standard GGA treatment to 0.06 eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use CCSD(T) calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs

NMN-VD: A Neural Module Network for Visual Dialog

Visual dialog demonstrates several important aspects of multimodal artificial intelligence; however, it is hindered by visual grounding and visual coreference resolution problems. To overcome these problems, we propose the novel neural module network for visual dialog (NMN-VD). NMN-VD is an efficient question-customized modular network model that combines only the modules required for deciding answers after analyzing input questions. In particular, the model includes a Refer module that effectively finds the visual area indicated by a pronoun using a reference pool to solve a visual coreference resolution problem, which is an important challenge in visual dialog. In addition, the proposed NMN-VD model includes a method for distinguishing and handling impersonal pronouns that do not require visual coreference resolution from general pronouns. Furthermore, a new Compare module that effectively handles comparison questions found in visual dialogs is included in the model, as well as a Find module that applies a triple-attention mechanism to solve visual grounding problems between the question and the image. The results of various experiments conducted using a set of large-scale benchmark data verify the efficacy and high performance of our proposed NMN-VD model

NMN-VD: A Neural Module Network for Visual Dialog

Visual dialog demonstrates several important aspects of multimodal artificial intelligence; however, it is hindered by visual grounding and visual coreference resolution problems. To overcome these problems, we propose the novel neural module network for visual dialog (NMN-VD). NMN-VD is an efficient question-customized modular network model that combines only the modules required for deciding answers after analyzing input questions. In particular, the model includes a Refer module that effectively finds the visual area indicated by a pronoun using a reference pool to solve a visual coreference resolution problem, which is an important challenge in visual dialog. In addition, the proposed NMN-VD model includes a method for distinguishing and handling impersonal pronouns that do not require visual coreference resolution from general pronouns. Furthermore, a new Compare module that effectively handles comparison questions found in visual dialogs is included in the model, as well as a Find module that applies a triple-attention mechanism to solve visual grounding problems between the question and the image. The results of various experiments conducted using a set of large-scale benchmark data verify the efficacy and high performance of our proposed NMN-VD model

Gas-Phase and Solid-State Electronic Structure Analysis and DFT Benchmarking of HfCO

Ab initio multi-reference configuration interaction (MRCI) and coupled cluster singles doubles and perturbative triples [CCSD(T)] levels of theory were used to study ground and excited electronic states of HfCO. We report potential energy curves, dissociation energies (De), excitation energies, harmonic vibrational frequencies, and chemical bonding patterns of HfCO. The 3Ʃ– ground state of HfCO has an 1σ22σ21π2 electron configuration and a ~30 kcal/mol dissociation energy with respect to its lowest-energy fragments Hf(3F)+CO(X1Σ+). We further evaluated the De of its isovalent HfCX (X = S, Se, Te, Po) series and observed that they increase linearly from the lighter HfCO to the heavier HfCPo with the dipole moment of the CX ligand. The same linear relationship was observed for TiCX and ZrCX. We utilized the CCSD(T) benchmark values of De, excitation energy, and ionization energy (IE) values to evaluate density functional theory (DFT) errors with 23 exchange–correlation functionals spanning GGA, meta-GGA, global GGA hybrid, meta-GGA hybrid, range-separated hybrid, and double-hybrid functional families. The global GGA hybrid B3LYP and range-separated hybrid ωB97X performed well at representing the ground state properties of HfCO (De and IE). Finally, we extended our DFT analysis to the interaction of a CO molecule with a Hf surface and observed that the surface chemisorption energy and the gas-phase molecular dissociation energy are very similar for some DFAs but not others, suggesting moderate transferability of the benchmarks on these molecules to the solid-state