Size-Dependent Lattice Symmetry Breaking Determines the Exciton Fine Structure of Perovskite Nanocrystals.

The order of bright and dark excitonic states in lead-halide perovskite nanocrystals is debated. It has been proposed that the Rashba effect, driven by lattice-induced symmetry breaking, causes a bright excitonic ground state. Direct measurements of excitonic spectra, however, show the signatures of a dark ground state, bringing the role of the Rashba effect into question. We use an atomistic theory to model the exciton fine structure of perovskite nanocrystals, accounting for realistic lattice distortions. We calculate optical gaps and excitonic features that compare favorably with experimental works. The exciton fine structure splittings show a nonmonotonic size dependence due to a structural transition between cubic and orthorhombic phases. Additionally, the excitonic ground state is found to be dark with spin triplet character, exhibiting a small Rashba coupling. We additionally explore the effects of nanocrystal shape on the fine structure, clarifying observations on polydisperse nanocrystals.

Direct Observation of Transient Structural Dynamics of Atomically Thin Halide Perovskite Nanowires.

Halide perovskite is a unique dynamical system, whose structural and chemical processes happening across different timescales have significant impact on its physical properties and device-level performance. However, due to its intrinsic instability, real-time investigation of the structure dynamics of halide perovskite is challenging, which hinders the systematic understanding of the chemical processes in the synthesis, phase transition, and degradation of halide perovskite. Here, we show that atomically thin carbon materials can stabilize ultrathin halide perovskite nanostructures against otherwise detrimental conditions. Moreover, the protective carbon shells enable atomic-level visualization of the vibrational, rotational, and translational movement of halide perovskite unit cells. Albeit atomically thin, protected halide perovskite nanostructures can maintain their structural integrity up to an electron dose rate of 10,000 e-/Å2·s while exhibiting unusual dynamical behaviors pertaining to the lattice anharmonicity and nanoscale confinement. Our work demonstrates an effective method to protect beam-sensitive materials during in situ observation, unlocking new solutions to study new modes of structure dynamics of nanomaterials.

Renormalization of excitonic properties by polar phonons.

We employ quasiparticle path integral molecular dynamics to study how the excitonic properties of model semiconductors are altered by electron-phonon coupling. We describe ways within a path integral representation of the system to evaluate the renormalized mass, binding energy, and radiative recombination rate of excitons in the presence of a fluctuating lattice. To illustrate this approach, we consider Fröhlich-type electron-phonon interactions and employ an imaginary time influence functional to incorporate phonon-induced effects nonperturbatively. The effective mass and binding energies are compared with perturbative and variational approaches, which provide qualitatively consistent trends. We evaluate electron-hole recombination rates as mediated through both trap-assisted and bimolecular processes, developing a consistent statistical mechanical approach valid in the reaction limited regime. These calculations demonstrate how phonons screen electron-hole interactions, generically reducing exciton binding energies and increasing their radiative lifetimes.

Nonlocal Screening Dictates the Radiative Lifetimes of Excitations in Lead Halide Perovskites.

We use path integral molecular dynamics simulations and theory to elucidate the interactions between charge carriers, as mediated by a lead halide perovskite lattice. We find that the charge-lattice coupling of MAPbI3 results in a repulsive interaction between electrons and holes at intermediate distances. The effective interaction is understood using a Gaussian field theory, whereby the underlying soft, polar lattice contributes a nonlocal screening between quasiparticles. Path integral calculations of this nonlocal screening model are used to rationalize the small exciton binding energy and low radiative recombination rate observed experimentally and are compared to traditional Wannier-Mott and Fröhlich models, which fail to do so. These results clarify the origin of the high power conversion efficiencies in lead halide perovskites. Emergent repulsive electron-hole interactions provide a design principle for optimizing soft, polar semiconductors.

A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES.

Purpose: The number of patients with alcohol-related problems is steadily increasing. A large-scale survey of alcohol-related problems has been conducted. However, studies that predict hazardous drinkers and identify which factors contribute to the prediction are limited. Thus, the purpose of this study was to predict hazardous drinkers and the severity of alcohol-related problems of patients using a deep learning algorithm based on a large-scale survey data. Materials and Methods: Datasets of National Health and Nutrition Examination Survey of South Korea (K-NHANES), a nationally representative survey for the entire South Korean population, were used to train deep learning and conventional machine learning algorithms. Datasets from 69,187 and 45,672 participants were used to predict hazardous drinkers and the severity of alcohol-related problems, respectively. Based on the degree of contribution of each variable to deep learning, it was possible to determine which variable contributed significantly to the prediction of hazardous drinkers. Results: Deep learning showed the higher performance than conventional machine learning algorithms. It predicted hazardous drinkers with an AUC (Area under the receiver operating characteristic curve) of 0.870 (Logistic regression: 0.858, Linear SVM: 0.849, Random forest classifier: 0.810, K-nearest neighbors: 0.740). Among 325 variables for predicting hazardous drinkers, energy intake was a factor showing the greatest contribution to the prediction, followed by carbohydrate intake. Participants were classified into Zone I, Zone II, Zone III, and Zone IV based on the degree of alcohol-related problems, showing AUCs of 0.881, 0.774, 0.853, and 0.879, respectively. Conclusion: Hazardous drinking groups could be effectively predicted and individuals could be classified according to the degree of alcohol-related problems using a deep learning algorithm. This algorithm could be used to screen people who need treatment for alcohol-related problems among the general population or hospital visitors.

Vibrational relaxation dynamics in layered perovskite quantum wells.

Organic-inorganic layered perovskites, or Ruddlesden-Popper perovskites, are two-dimensional quantum wells with layers of lead-halide octahedra stacked between organic ligand barriers. The combination of their dielectric confinement and ionic sublattice results in excitonic excitations with substantial binding energies that are strongly coupled to the surrounding soft, polar lattice. However, the ligand environment in layered perovskites can significantly alter their optical properties due to the complex dynamic disorder of the soft perovskite lattice. Here, we infer dynamic disorder through phonon dephasing lifetimes initiated by resonant impulsive stimulated Raman photoexcitation followed by transient absorption probing for a variety of ligand substitutions. We demonstrate that vibrational relaxation in layered perovskite formed from flexible alkyl-amines as organic barriers is fast and relatively independent of the lattice temperature. Relaxation in layered perovskites spaced by aromatic amines is slower, although still fast relative to bulk inorganic lead bromide lattices, with a rate that is temperature dependent. Using molecular dynamics simulations, we explain the fast rates of relaxation by quantifying the large anharmonic coupling of the optical modes with the ligand layers and rationalize the temperature independence due to their amorphous packing. This work provides a molecular and time-domain depiction of the relaxation of nascent optical excitations and opens opportunities to understand how they couple to the complex layered perovskite lattice, elucidating design principles for optoelectronic devices.

Cloud-BS: A MapReduce-based bisulfite sequencing aligner on cloud.

In recent years, there have been many studies utilizing DNA methylome data to answer fundamental biological questions. Bisulfite sequencing (BS-seq) has enabled measurement of a genome-wide absolute level of DNA methylation at single-nucleotide resolution. However, due to the ambiguity introduced by bisulfite-treatment, the aligning process especially in large-scale epigenetic research is still considered a huge burden. We present Cloud-BS, an efficient BS-seq aligner designed for parallel execution on a distributed environment. Utilizing Apache Hadoop framework, Cloud-BS splits sequencing reads into multiple blocks and transfers them to distributed nodes. By designing each aligning procedure into separate map and reducing tasks while an internal key-value structure is optimized based on the MapReduce programming model, the algorithm significantly improves alignment performance without sacrificing mapping accuracy. In addition, Cloud-BS minimizes the innate burden of configuring a distributed environment by providing a pre-configured cloud image. Cloud-BS shows significantly improved bisulfite alignment performance compared to other existing BS-seq aligners. We believe our algorithm facilitates large-scale methylome data analysis. The algorithm is freely available at https://paryoja.github.io/Cloud-BS/ .

BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing data.

BACKGROUND: Bisulfite sequencing is one of the major high-resolution DNA methylation measurement method. Due to the selective nucleotide conversion on unmethylated cytosines after treatment with sodium bisulfite, processing bisulfite-treated sequencing reads requires additional steps which need high computational demands. However, a dearth of efficient aligner that is designed for bisulfite-treated sequencing becomes a bottleneck of large-scale DNA methylome analyses. RESULTS: In this study, we present a highly scalable, efficient, and load-balanced bisulfite aligner, BiSpark, which is designed for processing large volumes of bisulfite sequencing data. We implemented the BiSpark algorithm over the Apache Spark, a memory optimized distributed data processing framework, to achieve the maximum data parallel efficiency. The BiSpark algorithm is designed to support redistribution of imbalanced data to minimize delays on large-scale distributed environment. CONCLUSIONS: Experimental results on methylome datasets show that BiSpark significantly outperforms other state-of-the-art bisulfite sequencing aligners in terms of alignment speed and scalability with respect to dataset size and a number of computing nodes while providing highly consistent and comparable mapping results. AVAILABILITY: The implementation of BiSpark software package and source code is available at https://github.com/bhi-kimlab/BiSpark/ .

Translation-rotation decoupling of tracers of locally favorable structures in glass-forming liquids.

Particles in glass-forming liquids may form domains of locally favorable structures (LFSs) upon supercooling. Whether and how the LFS domains would relate to the slow relaxation of the glass-forming liquids have been issues of interest. In this study, we employ tracers of which structures resemble the LFS domains in Wahnström and Kob-Andersen (KA) glass-forming liquids and investigate the translation-rotation decoupling of the tracers. We find that the tracer structure affects how the translation and the rotation of tracers decouple and that information on the local mobility around the LFS domains may be gleaned from the tracer dynamics. According to the Stokes-Einstein relation and the Debye-Stokes-Einstein relation, the ratio of the translational (DT) and rotational (DR) diffusion coefficients is expected to be a constant over a range of T/η, where η and T denote the medium viscosity and temperature, respectively. In supercooled liquids and glasses, however, DT and DR decouple due to dynamic heterogeneity, thus DT/DR not being constant any more. In Wahnström glass-forming liquids, icosahedron LFS domains are the most long-lived ones and the mobility of neighbor particles around the icosahedron LFS domain is suppressed. We find from our simulations that the icosahedron tracers, similar in size and shape to the icosahedron LFS domains, experience drastic translation-rotation decoupling upon cooling. The local mobility of liquid particles around the icosahedron tracers is also suppressed significantly. On the other hand, tracers of FCC and HCP structures do not show translation-rotation decoupling in the Wahnström liquid. In KA glass-forming liquids, bicapped square antiprism LFS domains are the most long-lived LFS domains but are not correlated significantly with the local mobility. We find from our simulations that DT and DR of bicapped square antiprism tracers, also similar in size and shape to the bicapped square antiprism LFS domains, do not decouple significantly similarly to tracers of other structures, thus reflecting that the local mobility would not be associated strongly with LFS domains in the KA liquid.