Advancing Integration of Direct C-H Arylation-Derived Star-Shaped Oligomers as Second Acceptors for Ternary Organic Solar Cells.

Organic solar cells (OSCs) could benefit from the ternary bulk heterojunction (BHJ), a method that allows for fine-tuning of light capture, cascade energy levels, and film shape, in order to increase their power conversion efficiency (PCE). In this work, the third components of PM6:Y6 and PM6:BTP-eC9 BHJs are a set of four star-shaped unfused ring electron acceptors (SSUFREAs), i.e., BD-IC, BFD-IC, BD-2FIC, and BFD-2FIC, that are facilely synthesized by direct C-H arylation. The four SSUFREAs all show complete complementary absorption with PM6, Y6, and BTP-eC9, which facilitates light harvesting and exciton collection. When BFD-2FIC is added as a third component, the PCEs of PM6:Y6 and PM6:BTP-eC9 binary BHJs are able to be improved from 15.31% to 16.85%, and from 16.23% to 17.23%, respectively, showing that BFD-2FIC is useful for most effective ternary OSCs in general, and increasing short circuit current (JSC) and better film morphology are two additional benefits. The ternary PM6:Y6:BFD-2FIC exhibits a 9.7% percentage of increase in PCE compared to the PM6:Y6 binary BHJ, which is one of the highest percentage increases among the reported ternary BHJs, showing the huge potential of BFD-2FIC for ternary BHJ OSCs.

Fine-Scale Characterization of Plant Diterpene Glycosides Using Energy-Resolved Untargeted LC-MS/MS Metabolomics Analysis.

Plant diterpene glycosides are essential for diverse physiological processes. Comprehensive structural characterization proved to be a challenge due to variations in glycosylation patterns, diverse aglycone structures, and the absence of comprehensive reference databases. In this study, a method for fine-scale characterization was proposed based on energy-resolved (ER) untargeted LC-MS/MS metabolomics analysis using steviol glycosides as a demonstration. Energy-dependent fragmentation patterns were unveiled by a series of model compounds. Distinct glycosylation sites were discerned by leveraging varying fragmentation energies for the precursor ions. The sugar moiety linkage at C19OOH (R1) exhibited facile and intact cleavage at low collision energies, while the sugar moiety at C13-OH (R2) demonstrated consecutive cleavage with increasing energy. Aglycone ions exhibited a higher relative intensity at NCE 50, with relative intensities ranging from 95% to 100%. Subsequently, aglycone candidates, R1 sugar composition, and R2 sugar sequence were deduced through ER-MS/MS analysis. The developed method was applied to Stevia rebaudiana leaves. A total of 91 diterpene glycosides were unambiguously identified, including 16 steviol glycosides with novel acetylglycosylation patterns. This method offers a rapid alternative for glycan analysis and the structural differentiation of isomers. The developed method enhances the understanding of diterpene glycosides in plants, providing a reliable tool for the in-depth characterization of complex metabolite profiles.

Leveraging Unidentified Metabolic Features for Key Pathway Discovery: Chemical Classification-driven Network Analysis in Untargeted Metabolomics.

Untargeted metabolomics using liquid chromatography-electrospray ionization-high-resolution tandem mass spectrometry (UPLC-ESI-MS/MS) provides comprehensive insights into the dynamic changes of metabolites in biological systems. However, numerous unidentified metabolic features limit its utilization. In this study, a novel approach, the Chemical Classification-driven Molecular Network (CCMN), was proposed to unveil key metabolic pathways by leveraging hidden information within unidentified metabolic features. The method was demonstrated by using the herbivore-induced metabolic response in corn silk as a case study. Untargeted metabolomics analysis using UPLC-MS/MS was performed on wild corn silk and two genetically modified lines (pre- and postinsect treatment). Global annotation initially identified 256 (ESI-) and 327 (ESI+) metabolites. MS/MS-based classifications predicted 1939 (ESI-) and 1985 (ESI+) metabolic features into the chemical classes. CCMNs were then constructed using metabolic features shared classes, which facilitated the structure- or class annotation for completely unknown metabolic features. Next, 844/713 significantly decreased and 1593/1378 increased metabolites in ESI-/ESI+ modes were defined in response to insect herbivory, respectively. Method validation on a spiked maize sample demonstrated an overall class prediction accuracy rate of 95.7%. Potential key pathways were prescreened by a hypergeometric test using both structure- and class-annotated differential metabolites. Subsequently, CCMN was used to deeply amend and uncover the pathway metabolites deeply. Finally, 8 key pathways were defined, including phenylpropanoid (C6-C3), flavonoid, octadecanoid, diterpenoid, lignan, steroid, amino acid/small peptide, and monoterpenoid. This study highlights the effectiveness of leveraging unidentified metabolic features. CCMN-based key pathway analysis reduced the bias in conventional pathway enrichment analysis. It provides valuable insights into complex biological processes.

Modulation of Buried Interface by 1-(3-aminopropyl)-Imidazole for Efficient Inverted Formamidinium-Cesium Perovskite Solar Cells.

Considering the direct influence of substrate surface nature on perovskite (PVK) film growth, buried interfacial engineering is crucial to obtain ideal perovskite solar cells (PSCs). Herein, 1-(3-aminopropyl)-imidazole (API) is introduced at polytriarylamine (PTAA)/PVK interface to modulate the bottom property of PVK. First, the introduction of API improves the growth of PVK grains and reduces the Pb2+ defects and residual PbI2 present at the bottom of the film, contributing to the acquisition of high-quality PVK film. Besides, the presence of API can optimize the energy structure between PVK and PTAA, which facilitates the interfacial charge transfer. Density functional theory (DFT) reveals that the electron donor unit (R-C ═ N) of the API prefers to bind with Pb2+ traps at the PVK interface, while the formation of hydrogen bonds between the R-NH2 of API and I- strengthens the above binding ability. Consequently, the optimum API-treated inverted formamidinium-cesium (FA/Cs) PSCs yields a champion power conversion efficiency (PCE) of 22.02% and exhibited favorable stability.

Doping of ZnO Electron Transport Layer with Organic Dye Molecules to Enhance Efficiency and Photo-Stability of the Non-Fullerene Organic Solar Cells.

The solution-processed zinc oxide (ZnO) electron transport layer (ETL) always exhibits ubiquitous defects, and its photocatalytic activity is detrimental for the organic solar cell (OSC) to achieve high efficiency and stability. Herein, an organic dye molecule, PDINN-S is introduced, to dope ZnO, constructing a hybrid ZnO:PDINN-S ETL. This hybrid ETL exhibits improved electron mobility and conductivity, particularly post-light exposure. The catalytic activity of ZnO is also effectively suppressed.Consequently, the efficiency and photo-stability of inverted non-fullerene OSCs are synergistically enhanced. The devices based on PM6:Y6/PM6:BTP-eC9 active layer with ZnO:PDINN-S as ETL give impressive power conversion efficiencies (PCEs) of 16.78%/17.59%, significantly higher than those with pure ZnO as ETL (PCEs = 15.31%/16.04%). Moreover, ZnO:PDINN-S-based device shows exceptional long-term stability under continuous AM 1.5G illumination (T80 = 1130 h) , overwhelming the reference device (T80 = 455 h). In addition, Incorporating PDINN-S into ZnO alleviate mechanical stress within the inorganic lattice, making ZnO:PDINN-S ETL more suitable for the fabrication of flexible devices. Overall, doping ZnO with organic dye molecules offers an innovative strategy for developing multifunctional and efficient hybrid ETL of the non-fullerene OSCs with excellent efficiency and photo-stability.

Deep Characterization of Serum Metabolome Based on the Segment-Optimized Spectral-Stitching Direct-Infusion Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Approach.

Direct-infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FTICR MS) shows great promise for metabolomic analysis due to ultrahigh mass accuracy and resolution. However, most of the DI-FTICR MS approaches focused on high-throughput metabolomics analysis at the expense of sensitivity and resolution and the potential for metabolome characterization has not been fully explored. Here, we proposed a novel deep characterization approach of serum metabolome using a segment-optimized spectral-stitching DI-FTICR MS method integrated with high-confidence and database-independent formula assignments. With varied acquisition parameters for each segment, a highly efficient acquisition was achieved for the whole mass range with sub-ppm mass accuracy. In a pooled human serum sample, thousands of features were assigned with unambiguous formulas and possible candidates based on highly accurate mass measurements. Furthermore, a reaction network was used to select confidently unique formulas from possible candidates, which was constructed by unambiguous formulas and possible candidates connected by the formula differences resulting from biochemical and MS transformation. Compared with full-range and conventional segment acquisition, 8- and 1.2-fold increases in observed features were achieved, respectively. Assignment accuracy was 93-94% for both a standard mixture containing 190 metabolites and a spiked serum sample with the root mean square mass error of 0.15-0.16 ppm. In total, 3534 unequivocal neutral molecular formulas were assigned in the pooled serum sample, 35% of which are contained in the HMDB. This method offers great enhancement in the deep characterization of serum metabolome by DI-FTICR MS.

A Structure-Guided Molecular Network Strategy for Global Untargeted Metabolomics Data Annotation.

Large-scale metabolite annotation is a bottleneck in untargeted metabolomics. Here, we present a structure-guided molecular network strategy (SGMNS) for deep annotation of untargeted ultra-performance liquid chromatography-high resolution mass spectrometry (MS) metabolomics data. Different from the current network-based metabolite annotation method, SGMNS is based on a global connectivity molecular network (GCMN), which was constructed by molecular fingerprint similarity of chemical structures in metabolome databases. Neighbor metabolites with similar structures in GCMN are expected to produce similar spectra. Network annotation propagation of SGMNS is performed using known metabolites as seeds. The experimental MS/MS spectra of seeds are assigned to corresponding neighbor metabolites in GCMN as their "pseudo" spectra; the propagation is done by searching predicted retention times, MS1, and "pseudo" spectra against metabolite features in untargeted metabolomics data. Then, the annotated metabolite features were used as new seeds for annotation propagation again. Performance evaluation of SGMNS showed its unique advantages for metabolome annotation. The developed method was applied to annotate six typical biological samples; a total of 701, 1557, 1147, 1095, 1237, and 2041 metabolites were annotated from the cell, feces, plasma (NIST SRM 1950), tissue, urine, and their pooled sample, respectively, and the annotation accuracy was >83% with RSD <2%. The results show that SGMNS fully exploits the chemical space of the existing metabolomes for metabolite deep annotation and overcomes the shortcoming of insufficient reference MS/MS spectra.

Defect passivation via a multifunctional organic additive toward efficient and stable inverted perovskite solar cells.

A multifunctional group molecule, namely MATC, was first introduced into a Cs/FA-based perovskite used as an additive. An impressive PCE of 21.51% was achieved for the inverted PSCs with reduced defect states and improved perovskite film quality. Moreover, MATC passivation considerably enhanced the stability of the PSC devices.

Surface termination passivation of imidazole-based diiodide enabling efficient inverted perovskite solar cells.

N-(3-aminopropyl)-imidazole diiodide (APDI) was introduced on the upper surface of the perovskite for the first time to modulate the terminal groups. The defect traps were suppressed by binding N cations from the APDI with Pb2+. Consequently, the optimum APDI-treated device achieved a PCE of 21.41% and exhibited excellent stability.

Cation and anion optimization of ammonium halide for interfacial passivation of inverted perovskite solar cells.

Perovskite solar cell (PSC) commercialization faces intrinsic stability and efficiency challenges. N1-phenylethane-1,2-diamine hydrohalides (PNEAX) based on a new design strategy featuring cation and anion optimization have been developed for efficient interfacial passivation. Among them, PNEACl-treated devices achieved a champion efficiency of 21.01% with good stability.

High Conductivity, Semiconducting, and Metallic PEDOT:PSS Electrode for All-Plastic Solar Cells.

Plastic electrodes are desirable for the rapid development of flexible organic electronics. In this article, a plastic electrode has been prepared by employing traditional conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) and plastic substrate polyethersulfone (PES). The completed electrode (Denote as HC-PEDOT:PSS) treated by 80% concentrated sulfuric acid (H2SO4) possesses a high electrical conductivity of over 2673 S/cm and a high transmittance of over 90% at 550 nm. The high conductivity is attributed to the regular arrangement of PEDOT molecules, which has been proved by the X-ray diffraction characterization. Temperature-dependent conductivity measurement reveals that the HC-PEDOT:PSS possesses both semiconducting and metallic properties. The binding force and effects between the PEDOT and PEI are investigated in detail. All plastic solar cells with a classical device structure of PES/HC-PEDOT:PSS/PEI/P3HT:ICBA/EG-PEDOT:PSS show a PCE of 4.05%. The ITO-free device with a structure of Glass/HC-PEDOT:PSS/Al4083/PM6:Y6/PDINO/Ag delivers an open-circuit voltage (VOC) of 0.81 V, short-circuit current (JSC ) of 23.5 mA/cm2, fill factor (FF) of 0.67 and a moderate power conversion efficiency (PCE) of 12.8%. The above results demonstrate the HC-PEDOT:PSS electrode is a promising candidate for all-plastic solar cells and ITO-free organic solar cells.

Bay-Functionalized Perylene Diimide Derivative Cathode Interfacial Layer for High-Performance Organic Solar Cells.

The field of organic solar cells (OSCs) has acquired rapid progress with the development of nonfullerene acceptors. Interfacial engineering is also significant for the enhancement of the power conversion efficiency (PCE) in OSCs. Among the cathode interfacial materials (CIMs), perylene diimide (PDI) small molecules are promising owing to the excellent electron affinity and electron mobility. Although the well-known PDINN molecule has excellent properties, it has a high planarity formed by an extensive rigid π-conjugated backbone. Because the PDI molecular backbone has a strong tendency to aggregate, it causes the problem of excessive molecular aggregation and stacking, which directly leads to excessive crystallinity. Proper accumulation is beneficial for charge transport, but oversized crystals formed by overaggregation will hinder charge transport, ultimately affecting the film morphology and charge transport efficiency. Modifying the bay position of PDINN is an effective strategy to reduce the planarity, modulate the molecular aggregation, optimize the morphology, and enhance the charge-collecting efficiency. Therefore, PDINN-S was synthesized from PDINN by substituting the hydrogen with thiophene. The optimal PCE in the PM6:Y6 active layer was 16.18% and remained at 80% of the initial value after 720 h in a glovebox. This provides some guidance for exploring CIMs and preparing large-scale OSCs in the future.

Highly Stable Supercapacitors Enabled by a New Conducting Polymer Complex PEDOT:CF3 SO2(x) PSS(1-x).

Herein, a novel conducting polymer complex PEDOT:CF3 SO2(x) PSS(1-x) [denoted as S-PEDOT:CF3 SO2(x) PSS(1-x) , where PEDOT is poly(3,4-ethylenedioxythiophene) and PSS is poly(styrene sulfonate)], is fabricated with the assistance of zinc di[bis(trifluoromenthylsulfonyl) imide][Zn(TFSI)2 ] (CFE). The introduction of CF3 SO2 - group is expected to bring better stability of PEDOT:CF3 SO2 than PEDOT:PSS due to its strong Coulomb force. Electrochemical measurement shows that a high specific capacitance of 194 F cm-3 was achieved from the novel complex S-PEDOT:CF3 SO2(x) PSS(1-x) , the highest value reported so far. An all-solid-state supercapacitor assembly with a structure of S-PEDOT:CF3 SO2(x) PSS(1-x) /H2 SO4 :polyvinyl alcohol (PVA)/S-PEDOT:CF3 SO2(x) PSS(1-x) shows a record specific capacitance of 70.9 F cm-3 and a maximum energy density of 6.02 mWh cm-3 at a power density of 397 mW cm-3 . This supercapacitor device demonstrates excellent electrochemical stability with a capacitance retention rate of 98 % after 10 000 cycles and extreme air stability of 96 % capacitance retention rate after 10 000 cycles, even if the device is exposed to air over 2880 h, much better than that of PEDOT:PSS based supercapacitors. Excellent capacitance can be achieved from PEDOT:CF3 SO2(x) PSS(1-x) electrode under electrolyte-free conditions. This work provides a novel method for high performance stable supercapacitors and may pave the way for the commercialization of PEDOT based supercapacitors.

Novel Method for Comprehensive Annotation of Plant Glycosides Based on Untargeted LC-HRMS/MS Metabolomics.

Glycosides are a large family of secondary metabolites in plants, which play a critical role in plant growth and development. Due to the complexity and diversity in structures and the limited availability of authentic standards, comprehensive annotation of the glycosides remains a great challenge. In this study, using maize as an example, a deep annotation method of glycosides was proposed based on untargeted liquid chromatography-high-resolution tandem mass spectrometry metabolomics analysis. First, knowledge-based in silico aglycone and glycosyl/acyl-glycosyl libraries were built. A total of 1240 known and potential aglycones from databases and literature were recorded. Next, the MS parameters beneficial to aglycone ion-rich MS/MS were explored using 1782 high-resolution MS/MS spectra of glycosides from the MassBank of North America (MoNA) and confirmed by 52 authentic glycoside standards. Then, screening rules for aglycon ions in MS/MS were recommended. Glycoside candidates were further filtered by MS/MS-based chemical classification and MS/MS similarity of aglycon-glycoside pairs. Finally, the glycosylation sites of flavonoid mono-O-glycosides were recommended by characteristic fragmentation patterns. The developed method was validated using glycosides and nonglycosides from the MoNA library. The annotation accuracy rates were 96.8, 94.9, and 98.0% in negative ion mode (ESI-), positive ion mode (ESI+), and the combined ESI- & ESI+, respectively. The annotation specificity was 99.6% (ESI-), 99.6% (ESI+), and 99.2% (ESI- & ESI+). A total of 274 glycosides (including 34 acyl-glycosides) were tentatively annotated in maize by the developed method. The method enables effective and reliable annotation for plant glycosides.

[A novel method for efficient screening and annotation of important pathway-associated metabolites based on the modified metabolome and probe molecules].

Plants produce a wide variety of secondary metabolites in the process of evolution. Secondary metabolites have highly diverse structures due to the modification of the basic skeletons of metabolites. They are required for interaction with the environment and are produced in response to abiotic/biotic stress. Characterization of secondary metabolic pathways is significant to plant molecular breeding and natural product biosynthesis. The liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) is one of the major techniques for untargeted metabolomics study. The LC-HRMS/MS method could detect tens of thousands of metabolic features and provide abundant structural information. It has been widely used in the discovery and characterization of the secondary metabolome. However, due to the largely diverse structure and limited records in the mass spectral library, the annotation of the secondary metabolome is very difficult. To address the analytical challenges associated with the vast structural diversity and the large numbers of secondary metabolites, particularly those previously unknown structural metabolites, a novel method for the efficient characterization of pathway-associated metabolites was developed. Modification reactions and MS/MS spectral information were collected using the metabolic pathways database and mass spectral library. Screening and annotation of metabolites involved in phenylpropanoid metabolism in maize leaves were used as an example. First, a database of modified groups was established via pathway-associated modifications from open access metabolic pathway database and literature. Here, pathway databases included the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Plant Metabolic Pathways (PlantCyc). A total of 61 modification types were enrolled, including 10 generic and 51 pathway-specific modifications. Modified metabolomes were filtered from untargeted LC-HRMS/MS metabolomics data. Next, MS/MS spectra of the pathway-associated compounds (probe molecules) were collected in the Global Natural Products Social Molecular Networking (GNPS) MS/MS spectral library. The MS/MS of compounds assigned to chemical classes of phenylpropanoids were kept. An MS/MS spectral database of the probe molecules was constructed. It included 2677 spectra of 1542 phenylpropanoid compounds in the positive mode and 814 spectra of 661 phenylpropanoid compounds in the negative mode. Then, an MS/MS molecular network was generated by modified metabolome and probe molecules. The clusters comprising both probe molecules and modified metabolites were kept. To explore more previously unknown structural metabolites, the clusters with one more pathway-specific modified metabolite were retained even though they didn't contain any probe molecule. A total of 392 and 417 phenylpropanoid pathway-related metabolic metabolites were obtained in positive and negative ion modes, respectively. The pathway-associated metabolites were annotated based on the propagation of the molecular network. For the metabolites within the co-cluster, annotations were performed using the probe molecules as the initial seed. The modification group's substructure information was used for network propagation annotation. For the clusters containing only pathway-specific modified metabolites, the annotation is similar to the above process if identified nodes were present within the cluster. Otherwise, de novo annotation was manually executed based on substructure information. Finally, 129 unique metabolites were annotated after integration and removal of redundancy. Ten annotated metabolites were validated using commercially available or synthesized reference compounds. The other annotation results were validated using predicted chemical classes, in silico MS/MS, and predicted retention time. They are mainly involved in the downstream branch of phenylpropanoid pathways, including the flavonoid pathway (8 flavonoids, 19 flavonoid O-glycosides, 32 flavonoid C-glycosides), the hydroxycinnamic acid pathway (31 hydroxycinnamic acids and derivatives), and the lignan pathway (22 neo-lignans/lignan/lignan glycosides). All the annotated structures were searched against the PubChem and SciFinder databases. Among them, 26 metabolites were previously unreported in both the databases. In this study, the pathway-associated metabolites could be quickly discovered and annotated by the integration of probe molecules and modified metabolome. It provides a method for the in-depth study of the phenylpropanoid pathway.

Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes.

Aims/Hypothesis: Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites. Methods: Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA1c, and fasting insulin. Results: Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA1c, insulin, or a combination of FPG and HbA1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA1c. In comparison, the AUCs of FPG, HbA1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide). Conclusions/Interpretation: Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.

A two-dimensional conductive polymer/V2O5 composite with rapid zinc-ion storage kinetics for high-power aqueous zinc-ion batteries.

Vanadium oxides represent a promising cathode material for aqueous zinc ion batteries (ZIBs) owing to their abundant valences and versatile cation-storage capacities. However, the sluggish Zn2+ diffusion kinetics in the V2O5 framework and poor intrinsic conductivity result in inferior rate capability and unsatisfactory cycling performance of the V2O5 cathode, and thus limits its commercial-scale deployment. Herein, a unique conducting polymer intercalation strategy is developed to optimize the ion/electron transport simultaneously based on the rational design of the composite structure and morphology. The poly(3,4-ethylenedioxythiophene) (PEDOT) intercalated V2O5 not only remarkably enlarges the interlayer distance for facile Zn2+ diffusion, but also diminishes the electron transport resistance by the π-conjugated structure of PEDOT. Additionally, the two-dimensional (2D) morphology enables shorter ion diffusion paths as well as a larger number of exposed sites for Zn2+ insertion. As a result, the PEDOT-intercalated V2O5 (PEDOT/V2O5) exhibits a good high-rate performance (154 mA h g-1 at an ultrahigh current density of 50 A g-1) and a long-term cycling life (maintains 170 mA h g-1 even after 2500 cycles at 30 A g-1). This universal strategy provides a design principle for constructing efficient Zn2+ and electron transport pathways within cathode materials, holding great potential for the development of high-performance and durable ZIB cathodes.

Highly efficient and stable ZnO-based perovskite solar cells enabled by a self-assembled monolayer as the interface linker.

2-TA and 3-TA were introduced for the first time on the surface of ZnO, and used as SAMs for interfacial modification. A highest PCE of 20.6% was achieved for 2-TA PSCs with improved energy alignment and perovskite film quality, and reduced defect density. The modified ZnO exhibited better thermostability of the perovskite and resultant device stability.

Does Schizophrenia Itself Cause Obesity?

Background: Schizophrenia (SC) is considered the most serious of all mental disorders. Some antipsychotics are associated with weight gain and metabolic abnormalities. Whether SC itself causes obesity remains uncertain. Methods: We collected 185 first-episode drug-naive SC and 59 healthy controls (HCs) from the Third People's Hospital of Foshan, Guangdong, China, and distinguished their course of disease in order to understand the body mass index (BMI) and body fat metabolism of SC. Results: We found that excluding the drug factors, the longer the course of SC, the more obvious the increase of BMI and the higher the proportion of obesity. BMI was positively correlated with age, course of disease, fasting blood glucose (FBG), low-density lipoprotein (LDL), triglyceride (TG), and total cholesterol (TC), and negatively correlated with high-density lipoprotein (HDL). The results of regression analysis were further proof that age (B = 0.094, p < 0.001), duration (B = 0.081, p = 0.002), FBG (B = 0.987, p = 0.004), and TG (B = 0.918, p = 0.002) were the risk factors for the increase of BMI. HDL (B = -2.875, p < 0.001) was the protective factor. Conclusion: SC itself can increase BMI and easily lead to obesity. We should pay more attention to the monitoring of blood metabolism indicators, so as to reduce the risk of obesity and improve the quality of life of patients.

Novel dopant-free hole transport materials enabling 20.9% efficiency in perovskite solar cells.

Two novel donor-acceptor-donor (D-A-D) type dopant-free hole transport materials (HTMs), named BDD-T and BTT-T, were developed and applied in perovskite solar cells. An impressive power conversion efficiency (PCE) of 20.9% was acquired, which is one of the highest PCEs for D-A-D type dopant-free HTMs.