Search

Electron donors and acceptors in organic solar cells (OSCs) shall strike a favorable vertical phase separation that acceptors and donors have sufficient contact and gradient accumulation near the cathodes and anodes, respectively. Random mixing of donors/acceptors at surface will result in charge accumulation and severe recombination for low carrier-mobility organic materials. However, it is challenging to tune the vertical distribution in bulk-heterojunction films as they are usually made from a well-mixed donor/acceptor solution. Here, for the first time, it presents with solid evidence that the commonly used 1-chloronaphthalene (CN) additive can tune the donor/acceptor vertical distribution and establish the mechanism. Different from the previous understanding that ascribed the efficiency enhancement brought by CN to the improved molecular stacking/crystallization, it is revealed that the induced vertical distribution is the dominant factor leading to the significantly increased performance. Importantly, the vertical distribution tunability is effective in various hot nonfullerene OSC systems and creates more channels for the collection of dissociated carriers at corresponding organic/electrode interfaces, which contributes the high efficiency of 18.29%. This study of the material vertical distribution and its correlation with molecular stacking offers methods for additives selection and provides insights for the understanding and construction of high-performance OSCs. © 2022 Wiley-VCH GmbH

Many researchers have examined the desalination performance of various kinds of two-dimensional (2D) porous nanosheets prepared by top-down approaches such as forming pores on the plain based on molecular dynamics (MD) simulations. In contrast, it is rare to find MD simulations addressing the desalination performance of a 2D porous nanosheet prepared by bottom-up approaches. We investigated the desalination performance of a 2D porous nanosheet prepared by the assembly of cucurbit[6]uril (CB[6]) via MD simulation. The model 2D CB[6] nanosheet features CB[6] with the carbonyl-fringed portals of 3.9 Å and the interstitial space filled with hydrophobic linkers and dangling side chains. Our MD simulation demonstrated that the 2D porous CB[6] nanosheet possesses a 70 to 140 times higher water permeance than commercial reverse osmosis membranes while effectively preventing salt passage. The extremely high water permeance and perfect salt rejection stem from not only CB[6]’s nature (hydrophilicity, negative charge, and the right dimension for size exclusion) but also the hydrophobic and tightly filled interstitial space. We also double-checked that the extremely high water permeance was attributable to only CB[6]’s nature, not water leakage, by contrasting it with a 2D nanosheet comprising CB[6]-spermine complexes. Lastly, this paper provides a discussion on a better cucurbituril homologue to prepare a next-generation desalination membrane possessing great potential to such an extent to surpass the 2D porous CB[6] nanosheet based on quantum mechanics calculations.

Identification and classification are important application areas of surface-enhanced Raman spectroscopy (SERS). Substance is identified via the chemical finger-print function of Raman spectroscopy. Diseases can be diagnosed through biofluidic Raman spectrum analysis and classification accordingly. Since bio-fluidic, such as serumurineand tissue fluid contains various substances, Raman spectrum is too complex to be classified manually. The optimization of deep learning classification model is critical in diagnosis accuracy improvement. Here we propose, for the first, applying DARSHN algorithm in automatic diagnosis model design and optimization. DARSHN was applied to serialize the discrete search space. Optimal structural solution was generated through approximate gradient descent subsequently. This research suggested that DARSHN can be used in the optimization of classification models automatically and effectively. Its advantages in the application of serum SERS-based cancer diagnosis compared to residual network spectral classification models were shown in this paper. © 2022 IEEE.

The peptidyl transferase center (PTC) in the large subunit of the ribosome plays a critical role in protein synthesis by catalyzing the formation of peptide bonds with an astounding speed of about 15 to 20 peptide bonds per second. The ribosome coordinates the nucleophilic attack and deprotonation in the rate-limiting step at the PTC. However, the details of peptide bond formation within the ribosome, particularly the precise role of the two water molecules in the PTC, remain unclear. Here, we propose a novel stepwise "proton shuttle" mechanism which corroborates all the reported experimental measurements so far. In this mechanism, a water molecule close to A76 of peptidyl-tRNA 2′- and 3′-O stabilizes the transition state. The other one adjacent to the carbonyl oxygen of peptidyl-tRNA actively participates in the proton shuttle, playing the catalytic role of ribosome-catalyzed peptide bond formation.

With the development of state-of-the-art techniques in biological systems, many previous inaccessible data now has become massive. To understanding this unprecedented data is the key to discover new principles underlying the biological behaviour. The application of statistical methods, which contains mathematical formulation and physical thinking, could extract the hidden information from research data and shed light to the major research direction. The evolution is essentially variation, namely mutation, in its genetic material, which leads to the variation in the product, protein. Most of mutations at amino acid level come from non-synonymous single nucleotide polymorphism (nsSNP). The functions of protein could thus be altered. As a result, propagation of mutations and competitions between different sub-types together, is regarded as evolution. In this dissertation, two chapters are included under the title statistical methods for protein function and evolution analysis. In the first chapter, a statistical method, deLemus, is constructed for the time-resolved track of mutation trajectories, and the robustness of deLemus is verified by mapping the SOI with sites with structural and functional significance.In the second chapter, the mechanisms of CRISPR Cas9 were firstly introduced. Then a model with consideration of confrontational changes is proposed to link the mutation and off-target effects. During the ongoing CoVID-19 epidemic, the continuous genomic evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been generating new variants with enhanced transmissibility and immune escape. Being one key target of antibodies, mutations of the spike glycoprotein play a vital role in the trajectory of virus evasion. Here, we present a time-resolved statistical method, dynamic expedition of leading mutations (deLemus), to analyze the evolution dynamics of the spike protein. Together with analysis on single amino-acid polymorphism (SAP), we proposed

Low-dimensional copper halides having nontoxic elements are attracting increasing attention for their peculiar emission properties. Self-trapped excitons (STEs) account for their high photoluminescence quantum yields (PLQYs) with emission that can stretch across the entire visible spectrum. However, intrinsic factors that influence the formation or loss of the emissive species in low-dimensional copper halides remain elusive. Here, a comprehensive study on the STE formation dynamics of one-dimensional CsCu2I3 and zero-dimensional Cs3Cu2I5 is presented. It is found from STE kinetic analysis that a slower STE formation demonstrated by the 1D structure is not hindered by a potential barrier, but instead related to the number of phonons released in the self-trapping process. It is further revealed that in 1D CsCu2I3, the non-radiative recombination of STEs mainly occurs via the intersection between the STE state and the ground state in the configuration coordinate diagram, placing an intrinsic limit on the PLQY at room temperature. These findings show that the STE formation is affected by both the self-trapping depth and the phonon energy as opposed to a potential barrier in low-dimensional copper halides. The better understanding of STE formation and recombination processes provide basis for improving design and performance for broadband light emitting devices.

The electrochemical reduction (ECR) of CO2 is a powerful strategy to reduce the world's carbon footprint by converting CO2 to useful products such as CH3OH and CO. Recent techno-economic analysis has found that for the electro-conversion of CO2 to be adapted for practical use, the main products formed from this reaction need to be low-order, such as CO. This review summarizes recent progress in the ECR of CO2 to CO on nano-electrocatalysts (noble, non-noble metals and carbon nanomaterials) and provides the limitations and challenges that each electrocatalyst faces. It discusses the mechanism behind the performance of the electrocatalysts and offers the potential future prospects of the ECR process.

Layered phosphorus materials hold great potential in a wide range of applications. Although tremendous efforts have been made to investigate energetics of monolayer phosphorus structures, the insight into better understanding their stability from a structure and bonding perspective remains elusive. In this work, the gauche conformation is identified to play an important role in the energetics of reported monolayer phosphorus allotropes via a proposed potential energy function. This study sheds light on the importance of delicate lone pairs' interactions manifested by gauche effect in understanding the stability of phosphorene allotropes. © 2022 American Chemical Society. All rights reserved.

We study halide perovskites materials, which have lately emerged as potential materials for low-cost, high-efficiency solar cells due to their ease of synthesis and relatively abundant constituent elements, as well as their intriguing photo-physical features. Increasing evidences has showed that the drivers of their remarkable properties is related to a temperature-activated symmetry-lowering distortion effect, which was originally named emphanisis in the context of compounds like rock-salt group IV chalcogenides. Here we study a class of ABX3 compounds [A+ = Cs or CH3NH3 (MA) or CH(NH2)2 (FA); B2+ = Sn or Pb; X- = Br or I] to understand the driving forces behind emphanisis or dynamical off-centering instability. We show that electron-phonon interaction is the driving force with the covalency of BX3 framework and the dipole fluctuations of the A-site cation plays an essential role in determining the off-center temperature. We propose a general formula that capture the observed off-centering temperature dependence on aforementioned factors. Our theory suggests that A-site driven polaron-like model might be beneficial to understand the off-centering phenomenon in halide perovskites.

The need to understand chemistry through data-driven analysis from a comprehensive collection of reaction data has long been recognized, and the development of chemical reaction databases has been conducted for decades, including commercial databases such as Reaxys, Scifinder, or Web of Science and open-source database like the Open Reaction Database. As a result, exploiting information in this large-scale database could accelerate the process of addressing challenging chemistry problems. Recent developments in big data and machine learning have revolutionized approaches for analyzing chemical data, and successful applications of these techniques have significantly advanced the research in chemical reactions, including reaction classification, product prediction, yield estimation, and synthesis planning. In recent years, homogeneous nickel catalysis has been extensively studied in academia and industry. Remarkable advances have been made for many valuable reactions by using nickel as an effective catalyst, owing to its unique reactivity and cost efficiency. It would be beneficial to prepare a dataset to analyze this field from a fundamental point of view and provide more insight into the nickel-catalyzed reactions. We collected and analyzed a comprehensive dataset containing important papers in the field of C-O bond activation cross-coupling reactions and developed data mining tools to accelerate similar studies in the future.

Motivated by the controversial bright exciton splittings in inorganic cesium lead halide perovskite nanocrystals, we studied excitation state of perovskite CsPbBr3 by four-band model Hamiltonian. With spin-orbit coupling, the calculated band structure shows that the double degeneracy of each band around (0, 0, 0) point is removed because of broken spatial inversion symmetry (SIS). With broken SIS, ring-shaped valence band maximum is formed in the band structure of ground state, and SU(2) vector potential in momentum is created with the excitation of one electron from valence band to conduction band by photon absorption. In the case of low density carrier, our theory also predicts that the energy splitting between the four binding electron-hole states by the vector potential is proportional to the power of laser light which certainly stimulates further experimental work in this intriguing topic. © 2021 World Scientific Publishing Company.

Introducing ionic liquid (ILs) into ultra-high molecular polyethylene (UHMWPE) to form composites is a promising approach in enhancing the processability of UHMWPE and thus broaden its applications in industries. In order to have a comprehensive understanding of the effect of ILs, we conducted a systematic study on the UHMWPE/ILs composites with various ILs content under different applied tensile strains (0.28, 0.47 and 0.94 %) and room temperature. Constant strain-rate tests are also performed at five constant strain rates over the range of 2 × 10−3 s−1 to 1.7 × 10−1 s−1. The generalized Maxwell model was employed to model the time-dependent relaxation modulus, and the modelling results agree well with the experimental measurements. Moreover, experimental yield stress were modelled by the cooperative model based on Eyring’s activation theory and collective motion of chain segments under a fixed temperature. Analysis of the modelling results suggests that both the activation volume and the energy barrier are reduced by the addition of ILs, resulting in enhanced mobilities of chain segments and processibility of the UHMWPE.

Background and aims: genetic predisposition to autoimmune hepatitis (AIH) in adults is associated with possession of human leukocyte antigen (HLA) class I (A*01, B*08) and class II (DRB1*03, -04, -07, or -13) alleles, depending on geographic region. Juvenile autoimmune liver disease (AILD) comprises AIH-1, AIH-2, and autoimmune sclerosing cholangitis (ASC), which are phenotypically different from their adult counterparts. We aimed to define the relationship between HLA profile and disease course, severity, and outcome in juvenile AILD. Approach and results: we studied 236 children of European ancestry (152 female [64%], median age 11.15 years, range 0.8-17), including 100 with AIH-1, 59 with AIH-2, and 77 with ASC. The follow-up period was from 1977 to June 2019 (median 14.5 years). Class I and II HLA genotyping was performed using PCR/sequence-specific primers. HLA B*08, -DRB1*03, and the A1-B8-DR3 haplotype impart predisposition to all three forms of AILD. Homozygosity for DRB1*03 represented the strongest risk factor (8.8). HLA DRB1*04, which independently confers susceptibility to AIH in adults, was infrequent in AIH-1 and ASC, suggesting protection; and DRB1*15 (DR15) was protective against all forms of AILD. Distinct HLA class II alleles predispose to the different subgroups of juvenile AILD: DRB1*03 to AIH-1, DRB1*13 to ASC, and DRB1*07 to AIH-2. Possession of homozygous DRB1*03 or of DRB1*13 is associated with fibrosis at disease onset, and possession of these two genes in addition to DRB1*07 is associated with a more severe disease in all three subgroups. Conclusions: unique HLA profiles are seen in each subgroup of juvenile AILD. HLA genotype might be useful in predicting responsiveness to immunosuppressive treatment and course.

High electron mobility is pivotal in engineering oxide interfaces for electronic devices. Here, interfacial structure and physical behaviors of gamma-A1(2)O(3)/SrTiO3 spinel/perovskite heterostructure are explored to understand the microscopic origin of its extremely high electron mobility (1.4 x 10(5) cm(2) V(-1 )s(-1) at 2 K). Lattice mismatch at interface and intrinsic Al cation vacancies result in unexpected interfacial reconstruction and anisotropic electronic behavior. The spontaneous polarization in the gamma-A1(2)O(3) part leads to an insulator-metal transition observed experimentally, even if the thickness of gamma-A1(2)O(3) is only one unit cell, and a strong internal electric field can be as large as 142 mV/angstrom roughly 1.8 times the experimentally observed value of 80.1 mV/angstrom in LaA1O(3)/SrTiO3. As a result, unlike only in-plane slightly occupied Ti-d(xy) subbands in the conventional SrTiO3-based perovskite/perovskite heterostructure, all three t(2g) orbitals have charge exchange with the surfacial O-2p orbitals in gamma-A1(2)O(3)/SrTiO3; especially, the preferential orbital occupation is out-of-plane Ti-d(xz)/Ti-d(yz) at the interface. Nontrivial orbital occupation and complicated interfacial reconstruction result in large group velocity and a high density of states at the Fermi level and therefore serve as the origins of extremely high electron mobility and high carrier concentration. The physical mechanism revealed in our work offers insight into the creation of high-mobility nanoscale electronic devices.

The mainstream approach to antiviral drugs against COVID-19 is to focus on key stages of the SARS-CoV-2 life cycle. The vast majority of candidates under investigation are repurposed from agents of other indications. Understanding protein-inhibitor interactions at the molecular scale will provide crucial insights for drug discovery to stop this pandemic. In this article, we summarize and analyze the most recent structural data on several viral targets in the presence of promising inhibitors for COVID-19 in the context of the perspective of modes of action (MOA) to unravel insightful mechanistic features with atomistic resolution. The targets include spike glycoprotein and various host proteases mediating the entry of the virus into the cells, viral chymotrypsin- and papain-like proteases, and RNA-dependent RNA polymerase. The main purpose of this review is to present detailed MOA analysis to inspire fresh ideas for both de novo drug design and optimization of known scaffolds to combat COVID-19.

Herein, we report a smart coating with autonomous self-healing and self-reporting functions by simple integration of one-component microcapsules into the matrix without external intervention. The microcapsules containing hexamethylene diisocyanate (HDI) solution of aggregation-induced emission luminogens (AIEgens) were synthesized, and their properties, such as their composition, thermal stability, morphology, and damage-indicating ability, were investigated systematically. The AIEgen/HDI microcapsule-embedded coatings display adaptive self-repair of scratches and simultaneous high-contrast indication of the healed damage. Two commercialized AIEgens, tetraphenylethylene (TPE) and its derivative with dimethoxyl and benzylidene-methyloxazolone moieties (DM-TPE-BMO), were utilized as examples to demonstrate the feasibility of this concept in diverse polymer matrixes (including blue autofluorescent matrixes). It was found that the content of AIEgens can even be lowered to 0.05 wt %. This facile, economical, and feasible strategy toward the dual functions of self-repairing and self-sensing provides a new route for enhancing the longevity and reliability of polymer coatings, which is appealing and of great importance in practical applications. Copyright © 2019 American Chemical Society.

Adsorption of globular proteins at liquid-liquid interface results in compromised structures and functionalities to maintain a thermodynamically favorable state. However, the structural behavior of highly symmetrical supramolecular protein assemblies, adsorbed at the liquid-liquid interface, is not well understood. In this study, a model supramolecular protein assembly, E2 protein nanocage, a dodecahedral cage-structured protein, is studied upon adsorption at the oil-water interface by both theoretical and experimental analyses. Molecular dynamics simulations and force estimation reveal that noncovalent interactions between E2 subunits dominate over the tangential force experienced by E2 at the interface allowing it to retain its structural integrity. Experimental analyses confirm the adsorption of E2 on the liquid-liquid interface with negligible penetration depth. Molecular structural analyses further suggest the structural integrity of the caged structure of E2 at the oil-water interface with minimal change in the tertiary and secondary structures. In conclusion, this study brings new insights into the behavior of highly symmetrical supramolecular protein assemblies at liquid-liquid interface which is important in preserving their functionalities.

Recent experimental data reveal the complexity of diffusion dynamics beyond the scope of classical Brownian dynamics. The particles exhibit diverse diffusive motions from the anomalous toward classical diffusion over a wide range of temporal scales. Here a dressed diffusion model is developed to account for non-Brownian phenomena. By coupling the particle dynamics with a local field, the dressed diffusion model generalizes the Langevin equation through coupled damping kernels and generates the salient feature of time-dependent diffusion dynamics reported in the experimental measurements of biomolecules. The dressed diffusion model provides one quantitative aspect for future endeavors in this rapid-growing field. Copyright © 2019 American Chemical Society.