We conducted this study to investigate the number and location of cDC1s in various human kidney diseases as well as their correlation with clinico-pathological features and CD8+ T cells.cDC1 is a subset of conventional DCs, whose most recognized function is cross-presentation to CD8+ DCs, and CD8+ T cells.We analyzed 135 kidney biopsies samples. Kidney diseases included: acute tubular necrosis (ATN), acute interstitial nephritis (AIN), proliferative glomerulonephritis (GN) , non-proliferative GN  and diabetic nephropathy. Indirect immunofluorescence staining was used to quantify cDC1s, CD1c+ DCs. cDC1s were mainly found in the interstitium, except in lupus nephritis, pauci-immune GN and anti-GBM disease, where they were prominent in glomeruli and peri-glomerular regions. The number of cDC1s correlated with disease severity in ATN, number of crescents in pauci-immune GN, interstitial fibrosis in IgA nephropathy and lupus nephritis, as well as prognosis in IgA nephropathy. The number of CD8+ T cells also increased significantly in these conditions and cDC1 number correlated with CD8+ T cell number in lupus nephritis and pauci-immune GN, with many of them closely co-localized.cDC1s were rarely present in normal kidneys. Their number increased significantly in ATN and proliferative GN, proportionally much more than CD1c+ T cells suggests a combined mechanism in keeping with the results in animal models.cDC1 number correlated with various clinic-pathological features and prognosis reflecting a possible role in these conditions. Their association with CD8 These cells are heterogeneous and can be divided into distinct subsets based on their phenotype and function. Dendritic cells can be broadly categorized into plasmacytoid DCs (pDC) and conventional DCs (cDC). cDC consists of two major subsets: cDC1  , 4. AfteThe study was conducted in accordance with principles of the Declaration of Helsinki and was approved by the Human Research Ethics Committee of the Western Sydney Local Health District. Informed patient consent was obtained.st June 2016 to 30th June 2017 in Westmead Hospital, Sydney, Australia. Kidney tissues were snap frozen in O.C.T. compound  and stored at -80°C. Forty-one (41) samples had poor tissue quality and were excluded from the study. Baseline patient data including age, gender, estimated glomerular filtration rate (eGFR) and degree of proteinuria were collected at the time of kidney biopsy. eGFR was calculated using the CKD-EPI formula. The diagnosis was made by a renal pathologist, based on light, immunofluorescence (IF) and electron microscopy as well as clinical history.We analyzed 176 frozen diagnostic kidney biopsy samples taken from non-pregnant adult patients (>18 years old) between 1a priori as >20% reduction in eGFR on or before 31st December 2019) in IgA nephropathy by dividing patients into 2 groups according to cDC1 number with cut-off point at upper quartile (>=15). Lupus nephritis was further classified into 2 groups according to the level of interstitial fibrosis . Pauci-immune GN was classified into 2 groups according to the percentage of glomeruli with crescents .A variety of diseases were analyzed including non-glomerular diseases , proliferative GN , non-proliferative GN  and diabetic nephropathy. For ATN, we only included non-septic cases as septic ATN has a different pathophysiology. ATN was further categorized into mild-moderate disease  and severe disease . IgA nephropathy was classified according to the Oxford MEST score . We also analyzed the correlation between cDC1 number and prognosis . Slides were stored at -80°C. Tissue sections were fixed with 100% methanol at -20°C for 10 minutes and then air-dried. Indirect immunofluorescence staining was performed using the following method: tissue sections were washed in DPBS  and blocked with 2% Bovine Serum Albumin  for 15 minutes; then they were stained with primary antibody at 4°C overnight followed by secondary antibodies for 40 minutes at room temperature. + T cells were identified by staining for marker CD8.cDC1s were identified by staining for marker Clec9A. In humans, Clec9A expression is highly restricted to cDC1s in blood and tissues , 11. To IF images were acquired with a confocal microscope . Four randomly selected pictures were taken for each sample under 20X magnification and the average number of positive cells in these 4 pictures was used in the analysis. Labeled cells were counted by an investigator twice in a blinded fashion and the mean value was used. When calculating cDC2/cDC1 ratio, we used the mean number of cDC2 and cDC1 for each sample. When cDC1 number was 0, we used 1 instead of 0 in calculating cDC1/cDC1 ratio as it would otherwise be infinite. The number of cells was expressed per high power field. In quantifying the number of cells in the intra-glomerular region, 4 randomly selected glomeruli were taken from each sample and the average number of cells inside these 4 glomeruli was calculated. Image J manual cell counting and marking tool was used to record positive cells.Statistical analysis was performed using SPSS version 26. All analyses were 2 tailed and P<0.05 was considered statistically significant. When there was multiple comparisons to the control group (5), Bonferroni adjustment was made and P<0.01 was considered statistically significant. Continuous variables were presented as median with interquartile range (IQR). The distributions between groups were compared using Mann-Whitney U-test or Kruskal Wallis tests as appropriate. The strength of association was quantified using Spearman rank correlation. Kaplan-Meier time-to-event curves with log-rank test were used for outcome analysis.The baseline characteristics of patients in control and disease cohorts are summarized in cDC1s were rarely present in normal kidneys Figure 1The number of cDC1 increased significantly in ATN and proliferative GN  . More severe disease was associated with a higher number of cDC1 (p=0.032), but not cDC2 (+ T cells was significantly higher in IgA nephropathy than control (p<0.001) (+ T cell number. Thirty-five (35) patients had follow up data on or before 31st December 2019, of whom 9 experienced > 20% reduction in eGFR. Dividing patients into 2 groups according to cDC1 number with cut-off point at upper quartile (>=15), the higher cDC1 number group was associated with worse outcome , a higher number of cDC1 was associated with a higher T score (p=0.008), but not MES scores   (P<0.001) Table 3.=0.021)    Table 3.+ T cell numbers increased significantly compared to control, with cDC1s increased proportionally much more than cDC2s , we found that cDC1 number correlated with severity of fibrosis, as well as prognosis in IgA nephropathy, while no such correlation was found in non-immune mediated fibrotic disease (diabetic nephropathy). Third, there was a strong correlation between cDC1 number and crescent formation in pauci-immune GN, and cDC1 were present in large numbers in peri-glomerular and intra-glomerular regions indicating their possible role in crescent formation. Fourth, the number of cDC1 correlated with CD8+ T cell number was also increased. ATN is usually caused by ischemia reperfusion injury (IRI), nephrotoxins or sepsis. Traditionally, IRI and toxins cause sterile inflammation, and innate immunity, where DCs and T cells are less important, was considered to play a dominant role. However, increasing evidence from animal studies has shown both cDC1 and CD8+ T cells are important players. Previous studies in animal IRI and cisplatin nephrotoxicity found the total DC and T cell numbers increased , but not in non-immune mediated fibrotic disease (diabetic nephropathy), Previous study showed increased numbers of cDC1s and cDC2s in interstitial fibrosis . We, forfibrosis . It is ar organs –23. Sinchropathy , which mephritis , specialephritis . We exteephritis . cDC1s mephritis –30 and cephritis  Second,  T cells –37 and oimmunity . In addiimmunity . There hh kidney , 33 and h kidney –36 corre+ T cells. Previous studies showed that DCs are rarely present inside the glomerulus .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Intestinal ischemia/reperfusion (I/R)-injury often results in sepsis and organ failure and is of major importance in the clinic. A potential strategy to reduce I/R-injury is the application of ischemic preconditioning (IPC) during which repeated, brief episodes of I/R are applied. The aim of this study was to evaluate physiological and cellular effects of intestinal I/R-injury and to compare the influence of in-vivo IPC (iIPC) with ex-vivo IPC (eIPC), in which blood derived factors and nerval regulations are excluded.Using an established perfused rat intestine model, effects of iIPC and eIPC on physiological as well as cellular mechanisms of I/R-injury  were investigated. iIPC was applied by three reversible occlusions of the mesenteric artery in-vivo for 5 min followed by 5 min of reperfusion before isolating the small intestine, eIPC was induced by stopping the vascular perfusion ex-vivo 3 times for 5 min followed by 5 min of reperfusion after isolation of the intestine. Study groups  were: iIPC, eIPC, I/R (iIPC group), I/R (eIPC group), iIPC+I/R, eIPC+I/R, no intervention/control (iIPC group), no intervention/control (eIPC group). Tissue morphology/damage, metabolic functions, fluid shifts and barrier permeability were evaluated. Cellular mechanisms were investigated using signaling arrays.I/R-injury decreased intestinal galactose uptake (iIPC group: p<0.001), increased vascular perfusion pressure  and attenuated venous flow (iIPC group: p<0.05) while lactate-to-pyruvate ratio , luminal flow , goblet cell ratio  and apoptosis  were all increased. Application of iIPC prior to I/R increased vascular galactose uptake (P<0.05) while eIPC had no significant impact on parameters of I/R-injury. On cellular level, I/R-injury resulted in a reduction of the phosphorylation of several MAPK signaling molecules. Application of iIPC prior to I/R increased phosphorylation of JNK2 and p38δ while eIPC enhanced CREB and GSK-3α/β phosphorylation.Intestinal I/R-injury is associated with major physiological and cellular changes. However, the overall influence of the two different IPC strategies on the acute phase of intestinal I/R-injury is rather limited. Ischemia/reperfusion (I/R)-injury commonly results in organ failure and is associated with high mortality. An immediate and early recovery of blood flow (reperfusion) in affected areas is important to prevent irreversible organ damage. Paradoxically reperfusion in ischemic organs like heart, brain kidney and intestine increases the initial tissue damage leading to so called I/R-injury ,2. EspecIn case of the heart, brain, kidney and recently intestine, the application of ischemic preconditioning (IPC) and RIPC has the potential to reduce I/R mediated cell damage, morbidity and mortality in patients and animal models. Up to now, numerous animal studies and small clinical “proof-of-concept” trials have shown the benefits of different IPC strategies –10. DuriIn this study we employed an isolated perfused rat small intestine model for a detailed analysis of the early physiological and cellular processes induced by intestinal I/R-injury. In addition, potential protective effects of IPC were evaluated using two different experimental approaches: (i) a physiological in-vivo IPC (iIPC) setup was used for protecting the intestine from I/R-injury. (ii) blood derived factors and nerval regulations were excluded by performing ex-vivo IPC (eIPC). We hypothesize that iIPC and eIPC differentially affect physiological as well as cellular events triggered by intestinal I/R-injury.Our results show that although I/R-injury leads to major changes in intestinal physiology, effects of both strategies of IPC in the acute phase of intestinal I/R-injury are rather limited.https://arriveguidelines.org) were employed to improve the reporting of the study results. Organ isolation was performed under inhalation anaesthetics  and intraperitoneal injection of Ketamine up to a maximum dose of 40 mg/kg. The rats remained narcotised until intestine extraction was performed. Euthanasia was elicited by cervical dislocation.Female Wistar rats  were used for all experiments. Animals were housed with standard diet and water ad libitum for at least 24 hours before surgery. The experiments were approved by the local authority . All methods were conducted in accordance with the relevant guidelines and regulations. The recommendations of the ARRIVE guidelines  was treated with iIPC followed by an equilibration phase and I/R. All perfusions were continuously applied for 150 min without intermittent stops  received a vascular perfusion without intervention for 150 min. The second group  received after the equilibration phase of 60 min a hypoxic perfusion for 60 min followed by 30 min normoxic reperfusion (reoxygenation). In the third group  iIPC was applied by three reversible occlusions of the mesenteric artery for 5 min followed by 5 min of reperfusion nt stops .after isolation of the small intestine. The following eIPC groups were investigated: E: control group, N = 8. F: I/R group, N = 8. G: eIPC group, N = 8. H: eIPC+I/R group, N = 8  were matched . eIPC wap, N = 8 .Details about the respective methods have been published recently ,17. BrieActivities of the effector Caspases-3 and -7, which play a central role in apoptotic events were evaluated in luminal effluent samples before and after perfusion using rhodamine based fluorometric assays . Treatment of the samples and evaluation of Caspase-3/7 activity were done based on the manufacturer’s protocol using a fluorescence ELISA reader  in combination with the Magellan software v1.1. Protein extraction was performed with RIPA buffer containing 150 mM sodium chloride, 1% NP-40, 1% sodium deoxycholate, 0.1% sodium dodecyl sulfate (SDS) and 50 mM Tris-HCl . Protein concentrations were determined with Roti®-Quant assays  . To visuFor the evaluation of relative levels of phosphorylation of mitogen-activated protein kinases and other serine/threonine kinases phospho-MAPK arrays  were used. Samples of each respective group were pooled and analyzed based on the protocol provided by the manufacturer. Therefore, depending on the group, equal volumes of 8 or 9 samples were pooled (i.e. 50μl of each sample) and applied to the respective array membrane. Images were taken and the intensities of the signals were densitometrically analyzed with the software ImageJ . Signals on the membrane were compared with the corresponding reference spots and signals below 20% of the mean intensities of the reference spots were excluded from further analyses. Proteins on the array membranes are represented by duplicate spots and signal intensities shown in the results section represent the mean of the signal intensities of these two spots.All statistical analyses were performed using GraphPad Prism 5 for Windows . Data are presented as mean values with standard deviations (SD). Normal distribution was assessed by the Kolmogorov-Smirnov normality test. Statistical comparisons were performed using repeated measures two-way ANOVA with Bonferroni post-tests  as well as one-way ANOVA (parametric data) with Bonferroni post-tests or Kruskal-Wallis tests (non-parametric data) with Dunns post-tests . Differences were considered to be statistically significant if p was less than 0.05. The number of animals used per experimental group was determined on the basis of experience and data from previous studies with the perfused intestine model, as well as a power analysis using the Graph Pad StatMate 2.00 program .A summary of the main results of the study is shown in t90, p<0.05; I/Rt105, I/Rt120, I/Rt135, I/Rt150 all p<0.001 vs. respective control). iIPC increased intestinal galactose uptake prior induction of I/R , suggesting an enhanced intestinal functional performance at early but not at later time points, while eIPC had no effect at any of the time points investigated  as indicator for metabolic function showed a time dependent decrease in all groups which was possibly related to effects of the ex-vivo perfusion procedure on intestinal metabolism. I/R resulted in an additional decrease of galactose uptake which was most evident at later time points . Interestingly, performing iIPC alone also significantly increased goblet cell ratio . However, no influence of iIPC or eIPC on Caspase-3/7 activity was observed .t120-130 p<0.001 vs. respective control; eIPC: I/Rt150-160 p<0.001 vs. respective control). Interestingly, eIPC alone also resulted in an increase in vascular perfusion pressure , while iIPC and eIPC had no impact  which served as surrogate for in-vivo I/R in our model of the perfused intestine. The lactate-to-pyruvate ratio increased rapidly during hypoxic perfusion and reached normal levels directly after reoxygenation. This was expected and has also been shown by other authors ,27. In cThe two different IPC strategies (iIPC and eIPC) employed in our ex-vivo perfused rat small intestine model revealed only minor effects on I/R induced alterations in the rat intestine. iIPC significantly increased galactose uptake before I/R but showed no beneficial effects during or after I/R. While other animal studies employed reperfusion periods between 1h and 6h ,39, our Despite the rather discouraging effects of iIPC and eIPC on I/R associated physiological parameters, MAPK arrays revealed an increased phosphorylation of JNK2 and p38δ when iIPC was applied prior to I/R. Both molecules are part of the MAPK family and several studies showed JNK and p38 activation by environmental stressors like cytokines and I/R –38. Mura2 partial pressure, while ischemia in-vivo is mostly represented by a low flow or no flow condition. (v) Due to methodological constraints, the length of time the intestine remained in the perfusion chamber differed between the two groups , and we cannot exclude that this had an influence on the parameters analyzed in the study. (vi) Anesthesia was performed by using Sevoflurane, which exhibits vasodilatory effects. Accordingly, it cannot be excluded that, especially at the beginning of the anesthesia, hypoperfusion may have occurred in some organs/tissues.Based on its ex-vivo character, our study has some model related limitations which need to be considered: (i) We cannot exclude the possibility that ligation of the smaller vessels of the intestine before removal of the organ may have caused short ischemic phases in the organ which in turn might mask or interfere with potential iIPC or eIPC effects in our model. (ii) Another limitation of the study is the use of Sevoflurane for anesthetic management. Sevoflurane is considered to have organ-protective properties which could have an influence on the results of the present study. However, it should be noted that other volatile anesthetics as well as propofol have also been ascribed organ-protective properties and to the best of our knowledge, there are no anesthetics available for small animal anesthesia that do not exert organ-protective effects. (iii) We have employed a single pass ex-vivo model lacking recirculating humoral factors, systemic immune cells and accumulation of metabolites. Moreover, our system only allows the observation of short-term effects of I/R-injury and IPC since ex-vivo organ viability is limited. (iv) To ensure a continuous measurement of all parameters, the model is based on a hypoxic perfusion with constant flow rate and low OTaken together our results show that although I/R leads to major changes in intestinal physiology, effects of IPC in the acute phase of intestinal I/R-injury are rather limited. It cannot be ruled out that the IPC triggered cellular mechanisms may reveal their protective effects in medium or long-term observations. Therefore, additional animal and clinical studies are needed to assess the significance of IPC for intestinal protection from I/R-injury.S1 Fig(TIF)Click here for additional data file.


Mn) in 1–10 kDa) can overcome these problems. Herein, a new mesopolymer, MePBDFClH as donor material is designed and synthesized, and firstly applied in OSCs. As a comparison, other lower molecular weight mesopolymer of MePBDFClL and higher molecular weight polymer of PBDFCl with same structure are also prepared and investigated. Because of its appropriate phase separation and miscibility in the blend film, the MePBDFClH exhibits the highest power conversion efficiency (PCE) of 15.06% among the three materials. Meanwhile, the champion PCE is a new record for benzodifuran‐based photovoltaic materials. Importantly, comparing to the pronounced PCE decrease of polymer PBDFCl by about 12%, a slightly PCE difference for mespolymer MePBDFClL is only less than 5%, reducing the batch‐to‐batch variation. This work not only suggests that the benzodifuran unit is a promising electron‐donating core but also shows that the mesopolymers have great potentials to produce the low‐differentiated and high‐performance organic photovoltaic materials.The high‐performance organic solar cells (OSCs) tend to choose the polymers with high molecular weight as donors, which easily produce good crystallinity to facilitate intermolecular charge transfer. However, these polymers usually accompanied by the low solubility and synthetic difficulty, increasing batch‐to‐batch variations. The proposal of conjugated mesopolymers (molar mass ( H/Y6 shows a power conversion efficiency (PCE) of 15.06%, which is attributed to the efficient intermolecular charge transfer. Meanwhile, the champion PCE is a new record for benzodifuran‐based organic solar cells. More importantly, the batch‐to‐batch variation is effectively reduced by adopting mesopolymer.Conjugated mesopolymer is first applied in non‐fullerene solar cells. The champion device based on MePBDFCl In particular, the emergence of non‐fullerene acceptors has realized high power conversion efficiency (PCE) over 18%, attaining the preliminary level of commercialization.Solution‐processed bulk heterojunction organic solar cells (OSCs) have made considerable development due to their unique merits of low‐cost, lightweight, flexible, and simple device processing in recent decades.4, 5 Despite these factors, strong crystalline polymer donor featuring high molecular weight also is one indispensable factor, since high molecular weight commonly accompanies by good crystallinity which facilitates intermolecular charge transfer. However, this high molecular weight requirement in polymer not only lead to the low solubility but also cause difficulty in synthesis, especially, controlling the appropriate high molecular weight region. Although the adoption of the modified polymerization conditions such as mixed solvents of toluene and N,N‐dimethylformamide (DMF), or combined catalyst could realize high molecular weight, an inevitable negative effect appears in obvious batch‐to‐batch variations. Taking two best‐known polymer donors as examples, benzodithiophene]{3‐fluoro‐2[(2‐ethylhexyl)carbonyl]thienothiophenediyl}))‐Th,‐4‐fluorothiophen‐2‐yl)‐benzodithiophene))‐alt‐benzodithiophene‐4,8‐dione)]) (PM6)[32] and polydithiophene))‐alt‐(2‐butyloctyl) thiophen‐2‐yl)‐8‐(4‐(2‐butyloctyl)‐5‐methylthiophen‐2‐yl)dithienobenzothiadiazole)]) (D18). Some reports have showed that PM6 with high molecular weight can produce high PCE of over 17%. But the efficient PM6 batch must react in a mixed solvents of toluene and DMF system, which is difficult to control in molecular weight consistency. As far as D18, only in a narrow number‐averaged molecular weight (Mn) range about 70 kDa can exhibit relatively high efficiency for corresponding PSC device. Under these circumstances, the incapable volume‐produce of high‐efficiency polymer donors with high molecular weight becomes one of archcriminal for impeding the commercialization of OSCs. Recently, the proposal of conjugated mesopolymers (molar mass (Mn) between 1 and 10 kDa) have been proved to be an effective strategy for overcoming the low solubility and batch‐to‐batch variations. The mesopolymers possess facile synthesis, high molecular regularity, and good solution processability. Meanwhile, the appropriate molecular weights for mesopolymers can be easily obtained by controlling the reaction time or adopting the different polymerization process. However, the mesopolymers as donor materials are infrequent in organic photovoltaic field ‐indanone))‐5,5,11,11‐tetrakis(4‐hexylphenyl)‐dithieno‐s‐indacenodithiophene (ITIC) and ‐‐3,9‐diundecyl‐12,13‐dihydro‐thiadiazolo thienothienopyrrolothieno thienoindole‐2,10‐diyl)bis(methanylylidene)) bis) dimalononitrile) (Y6), et al., a reasonable match in absorption region, energy levels, and ideal morphology between acceptor and donor is necessary.18 Des To precisely evaluate the difference between mesopolymer and polymer on the photovoltaic performance, two contrasts, a mesopolymer MePBDFClL with lower molecular weight and a polymer PBDFCl with higher molecular weights were also synthesized. In the meantime, the non‐fullerene Y6 was used as acceptor in the PSCs, to match the absorption and energy levels of polymer. As the Mn increases, three materials exhibited different molecular packing and photovoltaic properties. To elucidate the origin of the differences in the solar cell performance, the molecular weight dependence of the charge carrier mobility, crystallization behavior and molecular packing, film morphology, and the miscibility in the blends were investigated. As a result, the medium molecular weight of MePBDFClH achieved the highest PCE value of 15.06%, which is the best PCE for BDF‐based polymers and the highest efficiency record for furan based photovoltaic materials. Meanwhile, this work is the first time to report mesopolymer application in organic photovoltaics. It was worth noting that the different PCEs between MePBDFClL and MePBDFClH was less than 5% under the optimized photovoltaic device conditions. In contrast, the polymer PBDFCl with high molecular weight exhibited a pronounced drop in PCE by 12%, which indicated that the proposed mesopolymer was an effective strategy to reduce the batch‐to‐batch variation. This successful case not only proves that the BDF unit is a promising electron‐donating core for OSCs, but also indicates that the mesopolymer possessed more potentials for the application in the organic photovoltaics.Herein, in this contribution, we reported a new mesopolymer donor, named ‐benzodifuran))‐alt‐(2‐butyloctyl)thiophen‐2‐yl)‐8‐(4‐(2‐butyloctyl)‐5‐methylthiophen‐2 yl)dithienobenzothiadiazole)]) (MePBDFCl). This mesopolymer adopted benzodifuran (BDF) as electron‐donating core since the oxygen atomic radius (1.52 Å) of furan is smaller than the sulfur atomic radius (1.80 Å), which easily formed intermolecular stacking. Meanwhile, the furan‐based photovoltaic materials hold some unique fascinations in comparison with thiophene‐based materials, such as, good solubility, strong fluorescence, abundant product from renewable resources, high mobility, and so on.50 To 22.1FigureL and MePBDFClH) and a polymer PBDFCl. All of them possess adequately good solubility in chloroform (CHCl3) and chlorobenzene at room temperature. The molecular weights (Mn) of MePBDFClL, MePBDFClH, and PBDFCl are 8.0, 9.9, and 17.1 kDa with appropriate polydispersity index (PDI) of 1.51, 1.41, and 1.60, respectively. The results show that MePBDFClL and MePBDFClH belong to mesopolymers due to their low molecular weights between 1 and 10 kDa. Meanwhile, all these donor materials have good thermostability with a similar decomposition temperature beyond 370 °C under nitrogen atmosphere.  (eV). The measured HOMO/LUMO levels were −5.51 eV/−3.53 eV for PBDFCl, and these levels of the mesopolymers were almost comparable with PBDFCl. The energy level diagrams of donor and acceptor display a clear comparison in Figure The UV–vis spectroscopy was used to investigate the optical properties for these mesopolymers and the polymer in dilute chloroform solution and films. As shown in Figure Figureπ‐π stacking diffraction peaks in the OOP direction. The location of lamellar (100) peak and π–π stacking peak (010) changed with the increasement of molecular weights. On the one hand, the lamellar (100) peaks were observed at q ≈ 0.317, 0.310, and 0.308 Å–1 for MePBDFClL, MePBDFClH, and PBDFCl, respectively, corresponding to a packing distance of 19.81, 20.26, and 20.39 Å. On the other hand, the MePBDFClL, MePBDFClH, and PBDFCl showed the π–π stacking peak located at q ≈ 1.702, 1.713, and 1.734 Å–1 in the OOP direction, corresponding to the π–π stacking distance of 3.69, 3.67, and 3.62 Å, respectively. The results suggested that the crystallinity could increase as the improvement of molecular weights. Meanwhile, due to the smaller atom radius of oxygen in furan than sulfur atom in thiophene unit, both the mesopolymers of MePBDFClL and MePBDFClH are easy to form efficient molecular π‐π stacking whether the low or high molecular weight. That is to say, the adoption of BDF as monomer to finely construct reasonable low molecular weight mesopolymeric region (8 KDa< Mn <10 KDa), the slightly decreased π–π stacking degree has not affect its basic strong crystalline properties, which could facilitate efficient charge transportation.To investigate the effect of different molecular weights of mesopolymer and polymer on the molecular packing and crystalline features in the thin film, the grazing incidence wide angle X‐ray scattering (GIWAXS) measurement was adopted. The 2D GIWAXS profiles and corresponding line‐cuts of in‐plane (IP) and out‐of‐plane (OOP) direction are exhibited in 2.2L needed 0.5% chloronaphthalene (CN) as additive to obtain an optimal condition, inversely, MePBDFClH and PBDFCl‐based devices only needed thermal annealing without additive. The current density–voltage (J–V) curves of the optimized devices based on MePBDFClL:Y6, MePBDFClH:Y6, and PBDFCl:Y6 are displayed in FigureTableH‐based OSCs exhibited the highest PCE of 15.06%, with Voc of 0.883 V, Jsc of 24.96 mA cm−2, and FF of 68.32%. For the other polymers, the optimal OSCs showed PCEs of 14.36% and 13.28% for MePBDFClL‐ and PBDFCl‐based devices, respectively. It is worth noting that the variations of the optimized PCEs are less than 5% between the mescopolymers of MePBDFClL and MePBDFClH, which is far less than that of the polymer of PBDFCl (≈12% discount). The result indicates that the proposal of mesopolymers is an effective strategy to reduce the batch‐to‐batch variation. Additionally, in spite of little difference of energy levels among the three materials, the diversity of molecular aggregation and phase separation with the varied molecular weights can caused their different Voc values. On the one hand, the Voc is related with energy levels of materials; on the other hand, the microstructure of blend film plays an important role in affecting the cell voltages. The difference of miscibility among the three donor materials with the acceptor could form diverse microstructures, influencing the carrier lifetimes and recombination losses, thus achieving the discrepant Voc. Figure L and PBDFCl, the MePBDFClH‐based OSC exhibited largest photoresponse area, thereby generating the highest Jsc value due to the more efficient photon‐harvesting. On the contrary, the OSC based MePBDFClL:Y6 had the least photoresponse area, thus yielding the lowest Jsc value. It's worth mentioning that the mesopolymer is first used in organic photovoltaics and the champion PCE of 15.05% is a new record for BDF‐based PSCs :poly(styrenesulfonate)/polymers:Y6 /PDINO/Ag. Figure  The detas Figure . The corμh) values were 3.49 × 10−4, 4.78 × 10−4, and 4.46 × 10−4 cm2 V−1 s−1 for MePBDFClL, MePBDFClH, and PBDFCl neat films, respectively. The MePBDFClH with a middle molecular‐weight has slightly improved charge mobility than PBDFCl with high molecular‐weight, which signifies the middle molecular‐weight has been enough to generate continuous ordered domains, serving as pathways and therefore benefit efficient charge transportation. On the other hand, Previous research has demonstrated that polydispersity of polymer is important for achieving high carrier mobilities. Even doping of small amounts of low molecular weight material can also limit interchain hopping, reducing the charge carrier mobility. The material purity of MePBDFClH is higher than that of PBDFCl according to the PDI data, therefore, the deficiency of length of the material is counteracted by crystalline purity for MePBDFClH. For the blend films, the MePBDFClL, MePBDFClH, and PBDFCl exhibited the hole mobility (μh)/electron mobility (µe) of 3.17 × 10−4/3.56 × 10−4 cm2 V−1 s−1, 4.57 × 10−4/4.84 × 10−4 cm2 V−1 s−1, as well as, 3.73 × 10−4/4.45 × 10−4 cm2 V−1 s−1, respectively. The ratios of hole and electron mobility in binary blend film were obtained: 0.89 for MePBDFClL, 0.94 for MePBDFClH, and 0.84 for PBDFCl, respectively. It is well known that the more balanced hole/electron mobilities ratio can boost the FF. Consequently, the most balanced μh/µe ratio coincided with the highest FF for OSCs based on MePBDFClH:Y6 among these devices. On the other hand, although the μh/µe ratio of MePBDFClL:Y6 was higher than that of PBDFCl blends, the lower charge mobility resulted in lower Jsc for MePBDFClL‐based device.In addition, the charge carrier mobilities of the neat and blend films for three materials were also estimated by the space‐charge‐limited current method, and corresponding parameters are summarized in Figure Jph) versus the effective voltage (Veff), as well as, the relationship between Jsc/Voc and light intensity (Plight) were measured. Generally, Jph equals to JL–JD, where JL and JD represent the current density under illumination and dark, respectively. Veff equals V0–V, where V0 and V are the voltage when Jph = 0 and the applied voltage, respectively. When Veff ≥ 2 V, the Jph reaches saturation (Jsat), consequently, the probability of charge dissociation and collection of photocurrent carriers P  can be estimated by the ratio of Jph/Jsat. As shown in Figure P  for the OSCs based on MePBDFClL:Y6, MePBDFClH:Y6, and PBDFCl:Y6 are 95.4%, 97.8%, and 96.3%, respectively. The result signified that the MePBDFClH based devices possessed more efficient exciton dissociation and charge extraction than those of MePBDFClL and PBDFCl based devices. In addition, the charge‐recombination mechanism was investigated by studying the relationship Jsc and Plight according to the equation Jsc∝PlightS. The value of S closer to 1 means less charge‐recombination. Figure S values for the MePBDFClL, MePBDFClH, and PBDFCl‐based devices, which were 96.3%, 98.9%, and 97.2%, respectively, indicating the less charge‐recombination in the MePBDFClH‐based devices. Furthermore, the dependency between Voc and Plight can contribute to confirming the mode of charge‐recombination. When the slope of fitted data equals kBT/q, the charge‐recombination is bimolecular recombination as dominance, where kB is Boltzmann's constant, T is temperature, and q is the elementary charge. While the slope is closer to 2 kBT/q, the charge‐recombination is monomolecular (trap‐assisted) recombination dominates. Thereinto, bimolecular recombination is mainly the recombination of free charges of holes and electrons in the D/A interface, and monomolecular recombination is mostly happened in the defects or trap state for the holes and electrons. As shown in Figure kBT/q for MePBDFClL‐, MePBDFClH‐, and PBDFCl‐based devices. The result shows that the mesopolymer based devices have fewer trap‐assisted recombination compared to the polymer based devices.To further gain a better understanding of the mesopolymers and the polymer on the exciton dissociation and charge recombination, the dependency of photocurrent density Jph versusFigure–1 (d‐spacing: 3.610 Å)  peak of Y6 was undiscovered in these blend films, indicating better miscibility between these donors and Y6. Significantly, MePBDFClL and MePBDFClH exhibited similar stacking condition with polymer PBDFCl in the blend films, which demonstrated that the mesopolymer had enough potential to form appropriate molecular packing via proper optimization.To meticulously explore the effect of the mesopolymers and polymer on the photovoltaic performance, the details of molecular morphology and orientation features were investigated by GIWAXS for these materials blend films. The images of GIWAXS measurements and the corresponding line cuts of these blend films are exhibited in ) Figure . AccordiL, MePBDFClH, and PBDFCl blend films exhibited gradually enhancive root‐mean‐square (RMS) roughness values of 0.928, 1.09, and 1.27 nm, respectively , which was easy to cause exciton recombination, resulting in reduced charge transfer. Under the optimized device fabrication conditions, MePBDFClL blend (adding 0.5% CN as additive) displayed the increased phase separation (RMS = 1.67 nm), however, the blend films RMS of MePBDFClH and PBDFCl precipitously increased to 5.41 and 5.58 nm, respectively , which guarantee enough exciton dissociations and efficient charge transfer.Considering that the morphology of the active layer plays an important role for photovoltaic performance, so atomic force microscope (AFM) was performed to investigate the phase separation morphologies of all blend films. As determined by AFM, with the increase of molecular weight, MePBDFCly Figure. The bley Figure . The excγ) between the donor and acceptor can be calculated by Wu model. As shown in Figure L, MePBDFClH, and PBDFCl, respectively, and similar trend for glycerol contact angles. The corresponding γ values could be calculated, and data is summarized in Table χ based on the equation of χ ∝ (γA−γB)2 can evaluate the blend miscibility. The calculated χ values were 0.0051, 0.0076, and 0.84 for MePBDFClL:Y6, MePBDFClH:Y6, and PBDFCl:Y6, respectively, which indicated that the MePBDFClL and MePBDFClH had better miscibility than polymer PBDFCl. The pronounced low miscibility representing large phase separation in the PBDFCl blend films, causing the difficulty in charge extraction  of two different solvents (water and glycerol) on the donor neat films and Y6 films were measured. The interfacial tensions Wu model.61 As 61 As γ3H was designed and synthesized, other two contrastive counterparts of MePBDFClL and PBDFCl varying molecular weights were also synthesized for a comprehensive comparison. With the change of molecular weights, these materials exhibited different molecular packing and crystallization behaviors. When blending with acceptor Y6, the MePBDFClL with low molecular weight and PBDFCl with high molecular weight showed little or large phase separated morphology, respectively. As a result, the mesopolymer MePBDFClH with medium molecular weight exhibited highest PCE of 15.06%, with Voc of 0.883 V, Jsc of 24.96 mA cm−2, and FF of 68.32% among the three materials, which was ascribed to the appropriate phase separation and miscibility in the blend film, achieving the efficient intermolecular charge transfer. It is worth mentioning that the mesopolymer is first used in organic photovoltaic and 15.06% is the highest PCE reported for BDF‐based single‐junction OSCs. Additionally, the difference of PCE was less than 5% between MePBDFClL and MePBDFClH, which indicated that the proposal of mesopolymers was an effective strategy to reduce the batch‐to‐batch variation. This work proves that the BDF unit is a promising electron‐donating core for OSCs. Meanwhile, it also provides an evidence that mesopolymers possess advantages in batch‐to‐batch consistence, good solution‐processability, and high‐performance over OSCs.In conclusion, high‐performance photovoltaic polymers featuring high molecular weight still have faced some typical challenges such as strong crystallinity leading to low solubility and synthetic difficulty, increasing batch‐to‐batch variations. In this work, the emerging conjugated mesopolymer as donor materials were first constructed to solve these issues. When the new mesopolymer of MePBDFClThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


IBRD1–IBRD6 have been designed by structural modification of the terminal moieties from experimentally synthesized A2-A1-D-A1-A2 architecture IBR for better integration in organic solar cells (OSCs). To exploit the electronic, photophysical and photovoltaic behavior, density functional theory/time dependent-density functional theory (DFT/TD-DFT) computations were performed at M06/6-311G functional. The geometry, electrical and optical properties of the designed acceptor molecules were compared with reported IBR architecture. Interestingly, a reduction in bandgap (2.528–2.126 eV), with a broader absorption spectrum, was studied in IBR derivatives (2.734 eV). Additionally, frontier molecular orbital findings revealed an excellent transfer of charge from donor to terminal acceptors and the central indenoindene-core was considered responsible for the charge transfer. Among all the chromophores, IBRD3 manifested the lowest energy gap (2.126 eV) with higher λmax at 734 and 745 nm in gaseous phase and solvent (chloroform), respectively due to the strong electron-withdrawing effect of five end-capped cyano groups present on the terminal acceptor. The transition density matrix map revealed an excellent charge transfer from donor to terminal acceptors. Further, to investigate the charge transfer and open-circuit voltage (Voc), PBDBT donor polymer was blended with acceptor chromophores, and a significant Voc (0.696–1.854 V) was observed. Intriguingly, all compounds exhibited lower reorganization and binding energy with a higher exciton dissociation in an excited state. This investigation indicates that these designed chromophores can serve as excellent electron acceptor molecules in organic solar cells (OSCs) that make them attractive candidates for the development of scalable and inexpensive optoelectronic devices.Considering the increased demand and potential of photovoltaic devices in clean, renewable electrical and hi-tech applications, non-fullerene acceptor (NFA) chromophores have gained significant attention. Herein, six novel NFA molecules  Until now Silicon-based solar cells (SCs) have been used frequently due to their low toxicity, thermal stability, and comparatively impressive power conversion efficiency (PCE); but suffer from certain drawbacks, including the high cost of production, heavy weight (20–30 kg m−2), rigidity, as well as defined and unalterable HOMO–LUMO levels3. To overcome these drawbacks, significant research effort has been put into more flexible, lightweight (0.5 kg m−2) organic solar cells (OSCs)4. These show great promise but traditionally suffered from low efficiencies. OSCs are generally bulk heterojunction (BHJ) units where absorption layers blend donor and acceptor molecules. Over the last 2 decades, cell efficiencies have improved from 2 to 18% and it has been possible due to use of fullerenes as electron-accepting moieties5. PCE of OSCs containing fullerene and their derivatives like PC61BM or PC71BM is found to be 11–12%, which is comparatively good electron conduction owing to their deep-lying LUMO levels. But fullerene acceptors suffer from the inability to harvest light as their absorption spectrum is poorly matched to the solar spectrum. This is further complicated by low photostability, diffusion into other layers, and lack of tunability11. This has given a way to research into non-fullerene acceptors (NFAs), particularly small molecules offering electron affinity tuneability and better-suited absorption spectra to capture sunlight15. Non-fullerene (NF) solar cells also termed as ‘all polymer’ or fullerene-free solar cells16 are considered as next generation OSCs17. Fused ring electron acceptors (FREAs) is an emergent class that absorbs visible to near-infrared (NIR) very well24 and possess better PCE values25, high thermic constancy26, and good stability in comparison to other NFAs27. In the last decade, there has been a move to design better photovoltaic materials and fine-tune their optoelectronic characteristics utilizing various FREAs, such as star molecule28, linear geometric molecules29 and X-shaped donor molecule30 etc. FREAs are usually A-D-A type chromophores where donor forms the central core, while electron acceptors act as pendants where they play the role of side end-capped groups which can be modified to tune the optoelectronic properties of investigated compounds34. This arrangement has been shown to be effective to build up highly desirable optoelectronic materials and the prediction of their electronic characteristics prior to synthesis. The properties of NFAs in OSCs inspired us to use recently synthesized A2-A1-D-A1-A2 type efficient NFA as reference chromophore, shortened as IBR synthesized by Zulfiqar et al. with an indenoindene core35 and 3-ethylrodanine end-capped acceptor. The indenoindene core in IBR enhanced the electron transportation due to extended π-electron conjugation. One sp3 carbon bridge and conjugated 14π-electrons in indenoindene allows it for tuning crystallinity, energy levels, absorption and solubility. This core has proven very effective in developing photovoltaic materials36. Li et al. showed that weak electron-withdrawing units play a vital role in tuning charge transport properties and energy level tuning. Thus, we planned to replace 3-ethylrodanine of IBR with different compounds with varying strength of electron removal in combination with indenoindene core to design novel photovoltaic molecules. Further, in the designed compounds, 2-butyloctyl is replaced by a methoxy group taking into account the computational cost. To the best of our information, the photovoltaic investigation of designed compounds (IBRD1–IBRD6) is unreported. Therefore, for the first time, we reported maximum absorption (λmax), frontier molecular orbital (FMOs), density of states (DOS) analysis, open-circuit voltage (Voc), reorganization energies and transition density matrix (TDM) heat maps of IBRD1–IBRD6 chromophores. Above mentioned properties of designed compounds have been compared with IBR to evaluate the performance of end-capped acceptor units. This theoretical insight should offer better design of photovoltaic materials to be used in the OSC applications.Solar energy is the most poised amongst the renewable sources to avert the climate crisis37, and calculations were examined through GaussView version 538. First of all, for optimization of geometrical parameters of IBR, theoretical calculations were performed at various functionals such as B3LYP39, CAM-B3LYP40, M0634, Hartree Fock method (HF)41 and M062X42 with a 6-311G basis set. Furthermore, UV–visible investigations for IBR was performed at the aforementioned functionals and basis set in chloroform. At the M06 Level, UV–visible findings exhibited an excellent agreement with experimental values  were investigated at M06/6-311g level. Moreover, the charge transfer phenomena for the complexes (PBDBT:IBRD3 and PBDBT:IBR-IBRD6) was investigated at M06 and 43. Subsequently, the charge transformation is significantly observed from donor to acceptor in PBDBT:IBRD3 and PBDBT:IBRD6 at 44, PyMOlyze version 2.045, Avogadro version 1.2.0n46, Gaussview version 5.038 and Chemcraft build 595b47 were used for data analysis.All the computations for the present work were implemented using Gaussian version 09 softwareIBR, used as a reference molecule, consists on an indenoindene-core that behaves as a donor (D) unit and flanked by A1  and A2 (3-ethyl-5-methylene-2-thioxothiazolidin-4-one). We substituted the terminal acceptor species (A2) of the IBR with various reported acceptors to design IBRD1–IBRD6 species  and lowest unoccupied molecular orbital (LUMO) distribution pattern, the charge transfer in photovoltaic OSCs varies significantly. According to valence band theory, the LUMO and HOMO are considered as conduction and valence bands, respectively. The difference of energy between HOMO/LUMO has been explained as the bandgap (Eg)53. The proficiency of OSCs power conversion is fairly reliant on the energy bandgap as there would be a high photovoltaic response of a material with a low Eg and vice versa. Herein, molecular orbital energies and their Eg for entitled compounds are calculated as shown in Table FMO investigation is considered a crucial factor for detecting the photo-electronic properties of OSCsIBR, 2.734 eV band gap is studied with − 5.981 and − 3.247 eV energies of HOMO and LUMO, respectively, in a closed relationship with experimental value (2.23 eV)35. Interestingly, a reduction in Eg has been examined in designed chromophores. The energies for HOMO are found to be − 6.030, − 6.427, − 6.531, − 6.155, − 6.154, and − 6.141 eV, respectively, for IBRD1–IBRD6, while for LUMO are − 3.502, − 4.161, − 4.405, − 3.714, − 3.739 and − 3.664 eV, respectively  group stabilized the chromophore by lowering its bandgap. Furthermore, a decrease in Eg is examined for IBRD2–IBRD3 when the number of electron-withdrawing groups (–CN) increased 54. The bandgap starts diminishing in IBRD5 than IBRD4 as the number of the electron-withdrawing groups (–Cl) increased  group. This might be due to the resonance effect that may compete with the inductive effect as F and Cl groups are electron donating due to the resonance effect (Cl > F)55. Overall, the reduction in the bandgap with terminal electron-withdrawing groups was found as F > Cl > CN. Among all the chromophores, it is inferred that IBRD3 has a narrow energy gap as it has three cyano groups that powerfully attract the electronic cloud toward themselves and lower the band gap between orbitals. However, the decreasing Eg order of IBR and IBRD1–IBRD6 is IBR > IBRD1 > IBRD6 > IBRD4 > IBRD5 > IBRD2 > IBRD3. Additionally, the dispersion pattern of electron density in LUMO and HOMO on the surface of both IBR and their fabricated molecules are shown in Fig. IBR the charge density is located all over the chromophore but significantly concentrated over the central indenoindene-core (donor) in HOMO while end-capped acceptor units in LUMO. Similarly, in all designed molecules charge density for HOMO exists over donor (indenoindene) unit and A1 while in LUMO on the terminal acceptors moieties. A relatively lower Eg between orbitals and effective CT from D to terminal A is examined in derivatives than that of reference which indicates them to be efficient materials for solar cells.In Eg can also be determined56. Thus, DOS helps in the manifestation of evidence discussed in FMOs and percentage influences about HOMO and LUMO charge densities. Herein, to investigate DOS, IBR and IBRD1–IBRD6 are divided into three fragments, i.e., A1, donor, and A2. In DOS spectra, the scattering pattern of the donor is manifested by a blue line, whereas the green and red lines exhibit the scattering pattern of acceptor-1 and acceptor-2, respectively  is the number of different states that electrons will occupy at a given energy level. For energy levels, a high DOS value indicates that numerous states are vacant. The DOS zero value exhibits that there are no states available for occupation at any energy level. DOS computations allow the broad distribution of states as a function of energy to be measured and ely Fig. . The posIBR, the Acceptor-1 contributes 20.8% to HOMO and 57.3% to LUMO, whereas, Acceptor-2 contributes to HOMO 14.2% and 30.4% to LUMO. Similarly, Donor contributes to HOMO, 65.0%, and LUMO, 12.3% in IBR. The Acceptor-1 contributes 19.4%, 17.7%, 17.6%, 18.8%, 18.5%, and 18.7% to HOMO and 31.5%, 22.1%, 18.9%, 27.8%, 25.4% and 28.4% to LUMO in IBRD1–IBRD6, respectively. Similarly, acceptor-2 contributes 6.7%, 7.4%, 7.5%, 6.7%, 6.2% and 6.3% to HOMO, while 61.4%, 73.0%, 76.7%, 66.1%, 69.4% and 65.5% to LUMO for IBRD1–IBRD6, respectively. In the same way, donor contributes 74.0%, 74.9%, 74.9%, 74.5%, 75.2% and 75.0% to HOMO whereas 7.1%, 4.9%, 4.4%, 6.1, 5.2, and 6.2% to LUMO for IBRD1–IBRD6, accordingly. DOS speculates that various electron-withdrawing acceptor groups are accountable for different scattering patterns of electron densities. Further, these electronic transitions are also responsible for intramolecular charge transfer. Figure For d,p) level in chloroform and gaseous phase to elucidate the optical properties of IBR and IBRD1–IBRD6  is connected with the inner climate of particles and outside reorganizational energy (λext.) should be identified with the outside environment of an atom. As outside climate effect is less relevant in this context so we are excluding outer RE for this manuscript. Charge transfer and reorganization energy have an inverse relation, so if the reorganization energy is low, the system initiates a significant amount of charge transfer65. Therefore, reorganization energies Measuring the reorganization energy (RE) of the compounds is one of the simplest ways to test CT (charge transfer) propertiesHere, λe for IBR is calculated to be 0.00882 eV and all derivatives have the higher value of λe except IBRD2 and IBRD3 as shown in Table λe exhibited lower rate of charge transfer66. Therefore, the results from Table IBRD2 and IBRD3 among all the studied compounds as they have the lower value of λe. While IBRD1, IBRD5 and IBRD6 have the higher value of electron reorganization energies than reference so expressed lower electron mobility rate than the parent molecule. IBRD4 and reference compound have almost equal electron charge transfer rate as they have comparable values of λe 0.009976 and 0.00882 eV, respectively. Overall decreasing order of λe is IBRD3 > IBRD2 > IBR. > IBRD4 > IBRD5 > IBRD1 > IBRD6. Similarly, λh calculated for reference is lower than all its derivatives which indicates that among all the designed compounds higher rate for hole transportation is present than parent chromophore  and Acceptors  units.The tool for measuring and evaluating the transmission of the charge of electrons in an excited state is known as transition density matrix (TDM). In an excited state, it supports to explain donor–acceptor unit interactions, electronic excitation, hole-electron localization and delocalizationEb) is another favorable factor that assists in determining the capacity for exciton dissociation, photo-electronic properties, and efficiency of OSCs. The PCE of OSCs and the parting rate of charges depend on the binding energies (Eb). Further, Eb is also linked to energy driving force (∆E). ∆E is the difference of LUMOs of acceptor and donor and it should be greater than 0.3 eV, for effective exciton split and charge transfer at DA interface70. The band gap difference of the optical and electrical energies gives the exciton binding energies. By using Eq.  units and then these excitations diagonally extend via A1 and A2 as though electron–hole pair started to build along diagonally without trapping in all investigated molecules. Binding energy  and h (hole). There is a direct relationship between Eb and coulombic hole-electron interaction, which has an inverse relation with exciton dissociation in the excited state72. A molecule with low Eb indicates low columbic contact between h and e that triggers high dissociation of arousal in an excited state. The IBR has a higher value of exciton Eb while IBRD3 expressed the lowest value of exciton Eb 0.437 eV along with smaller λe, compared to the reference and other designed compounds indicating the presence of the greater amount of charges, leading to a higher degree of charge separation in the S1 state observed in Table Eb order is obtained to be IBR > IBRD1 > IBRD6 > IBRD4 > IBRD5 > IBRD2 > IBRD3  of donor/acceptor complexes is found to be 2.154, 1.899, 1.24, 0.996, 1.687, 1.662, and 1.95PBDBT polymer. For this purpose, we blend the IBRD3 molecule with PBDBT polymer because of its lowest transition energy, highest λmax, good electron and hole mobility values among IBRD1–IBRD6. Additionally, IBRD6 is also utilized to make a complex with PBDBT polymer as it exhibited a higher value of Voc among all derivatives  PBDBT:IBRD6 is implemented at M06 and PBDBT polymer while LUMO is located over the IBRD3, which indicates that an excellent transfer of electronic cloud from donor PBDBT polymer towards IBRD3 chromophore. The same phenomena are observed for PBDBT:IBRD6  was designed from organic chromophore IBR. These IBRD1–IBRD6 chromophores were obtained by the structural modification of terminal acceptor units. The effect of various A units was examined on photovoltaic properties and a comparable relation is found between parent chromophore and their derivatives. Interestingly, all the derivatives showed a broader spectrum with a smaller bandgap than the parent molecule. FMO, DOS and TDM findings reveals that an effective charge is transfer from donor moiety to acceptor units. Further lower value of λe, indicated higher rate of electron mobility in all designed chromophores.The Voc calculated with respect to PBDBT for IBRD1–IBRD6 was 1.854, 1.599, 0.94, 0.696, 1.387, 1.362, and 1.437 V, respectively. In all newly designed molecules, IBRD3 exhibits the highest optical absorption wavelength (754 nm) with the lowest energy band gap (2.126 eV). All molecules with lower binding energies make the higher exciton dissociation in an excited state, which eventually causes a high transfer rate of charge. These photovoltaic properties suggest that all the newly designed molecules were excellent acceptor candidates for obtaining high PCE in organic solar cells.A series of indenoindene based A2-A1-D-A1-A2 architecture of novel NF-SMAs (Supplementary Information.


Topic recognition technology has been commonly applied to identify different categories of news topics from the vast amount of web information, which has a wide application prospect in the field of online public opinion monitoring, news recommendation, and so on. However, it is very challenging to effectively utilize key feature information such as syntax and semantics in the text to improve topic recognition accuracy. Some researchers proposed to combine the topic model with the word embedding model, whose results had shown that this approach could enrich text representation and benefit natural language processing downstream tasks. However, for the topic recognition problem of news texts, there is currently no standard way of combining topic model and word embedding model. Besides, some existing similar approaches were more complex and did not consider the fusion between topic distribution of different granularity and word embedding information. Therefore, this paper proposes a novel text representation method based on word embedding enhancement and further forms a full-process topic recognition framework for news text. In contrast to traditional topic recognition methods, this framework is designed to use the probabilistic topic model LDA, the word embedding models Word2vec and Glove to fully extract and integrate the topic distribution, semantic knowledge, and syntactic relationship of the text, and then use popular classifiers to automatically recognize the topic categories of news based on the obtained text representation vectors. As a result, the proposed framework can take advantage of the relationship between document and topic and the context information, which improves the expressive ability and reduces the dimensionality. Based on the two benchmark datasets of 20NewsGroup and BBC News, the experimental results verify the effectiveness and superiority of the proposed method based on word embedding enhancement for the news topic recognition problem. With the rapid development of information technology, people have been accustomed to obtaining various information from the Internet. These platforms, such as news websites and social media, enable us to know what is happening around the world whenever and wherever possible. However, under the current wave of information explosion, people are generally faced with the problem of having to spend much time and energy to find target information. Therefore, there is an urgent need to introduce topic recognition technology to identify news topics from texts, especially to identify different categories of news topics with different granularity to help enterprises or individuals quickly identify, extract, and analyze key information from the vast array of texts.In recent years, topic recognition technology has become a research hotspot in the field of natural language processing (NLP). And, we notice that it has been widely used in online public opinion monitoring, news recommendation, search engine optimization, and other fields. During the classic topic recognition process, the text representation layer is responsible for converting texts into feature vectors that computers can understand and it is expected to minimize information loss, which is actually the foundation of the whole task . As a maFrom the 1970s to the present, text representation methods have undergone an evolution from shallow semantic to deep semantic. The traditional text representation model can be traced back to the Boolean Model method, which can efficiently process large-scale data while having the disadvantage of lacking semantic information. The emergence of the Vector Space Model (VSM) alleviates the problem of lacking semantic information to a certain extent, but high-dimensional sparsity and computational complexity are the major drawbacks. To explore the potential features of the text, researchers introduced probabilistic topic models, Latent Dirichlet Allocation (LDA)  and Bitedistributional hypothesis of linguistics [In terms of the design principles, the topic model such as LDA uses statistical inference methods to automatically discover the hidden patterns in a large-scale corpus. Based on this type of model, the text can be mapped to a low dimensional latent semantic space from the document-word matrix. The whole process has nothing to do with the language category and belongs to an unsupervised way. At the same time, the result is better interpretable . Howeverguistics  can mineguistics . From thBased on the above analysis, this paper proposes a conjecture that the effective combination of topic model and word embedding model can enrich the text representation and benefit NLP downstream tasks. In recent years, some work has been carried out around this idea. Wang et al.  proposedHowever, due to the differences in target tasks, the updating of text representation models, and other factors, we can see that there is no standard framework for combining topic information and word embedding representation at present. For the topic recognition of news text, existing methods have been explored to improve the accuracy of recognition based on the above conjecture, but there are still some shortcomings. On the one hand, the model complexity is increased at the expense of time. On the other hand, the topic distribution of word or document reflects topic information in different granularities , so the A text representation method based on word embedding enhancement is proposed. Considering the lack of semantics in the LDA topic model, and the word embedding models Word2vec and Glove have a good ability to capture semantic information, we tried to fuse the two types of models. Based on the topic distribution at document level and word level, two vector concatenation strategies were designed to incorporate more semantic information into the text representation.A topic recognition framework for news text is proposed. The framework mainly includes three modules: preprocessing layer, feature extraction layer, and topic recognition layer. The preprocessing layer is responsible for performing necessary data cleaning, and the feature extraction layer is the concrete implementation of the proposed text representation method with different vector concatenation strategies. And, the topic recognition layer uses two popular classifiers: Support Vector Machine (SVM) and Logistic Regression (LR). The entire framework involves technologies such as BOW, LDA, word embedding, machine learning, and so on.In this paper, several similar methods were selected as the baselines. Based on the two benchmark datasets of 20NewsGroup and BBC News, we conducted a comprehensive evaluation. The experimental results show that the performance of the proposed method is better than the baselines for news topic recognition.In response to the above limitations, we propose a novel text representation method and form a full-process topic recognition framework for news text. In practice, this paper proposes to add word embedding vector as auxiliary information on the basis of LDA, and construct two kinds of text representations combined with topic information of different granularities: document-level topic distribution and document embedding (DTE) and word-level topic distribution and document embedding (WTE). Furthermore, we apply the two representations into the feature extraction layer in the proposed framework. The results show that this framework can make better use of the relationship between the document and the topic and the context information, which improves the expression ability and topic recognition accuracy. More specifically, our contributions are summarized as follows:The rest of the paper is organized as follows: TDT is a kind of information processing technology oriented to text mining, which aims to monitor the information flow to realize the automatic recognition and classification of massive text data. At the same time, it can also detect hot events in specific fields, and merge the new text into a topic cluster by topic clustering, which can be used to track the progress of hot topics in large dynamic data.Traditional TDT model mostly uses representation methods such as BOW and the topic model. Then, it uses text classification or clustering methods to perform topic recognition based on the obtained text vector representation. Obviously, the quality of the text representation largely lays the foundation of the topic recognition results, and the text classification or clustering models are also closely related to the accuracy and efficiency of the results. A lot of work has been carried out on these two aspects: Yan et al.  tried toAs an important research direction, the text representation plays a fundamental role in the NLP field. And, how to better represent text semantics to solve the practical applications is a problem under constant exploration. The classical methods can be traced back to the one-hot encoding, which belongs to the BOW model in essence. Then, the research focus has experienced the evolution from the topic model to the word embedding model . EspeciaAs the most basic text representation method, the BOW  separateTo further improve the quality of text representation, researchers try to explore the potential features. The Latent Semantic Indexing model (LSA)  uses theIn recent years, the rapid development of deep learning has opened up a new direction for the development of text representation . In 2013N, the complexity of Glove and BERT is O(N) and O(N2H), respectively, where H represents the maximum number of neurons in the hidden layer. Besides, BERT also limits the input length of the text sequence, and news text is usually long text data, which may lead to the loss of global information related to the task. Considering the complexity and recognition quality, this paper attempts to integrate the word embedding models, Word2vec, Glove, and topic model LDA to improve the quality of text representation. By integrating the advantages of each model, the new text representation includes not only the relationship between the document and topic but also the contextual relationship. Based on the new representation method, we design corresponding comparative experiments to verify the effectiveness of the proposed topic recognition framework.However, it is also noteworthy that some more excellent models have been proposed, such as Embedding from Language Models (ELMo) , GeneratAs shown in Word.Tin means that the element is the nth word in the ith document.A word is the smallest unit in a document, where Document.Di is essentially sequences of words and can be described as Di=.In this paper, a news document Corpus.C is essentially a collection of news documents, which can be denoted as C=.In this paper, a corpus Topic distribution based on the LDA model.ℵ hidden topics in m documents, and all words V in the documents will also have a corresponding probability value for each topic, where Z= and V=. As shown in Compared with traditional feature engineering, LDA has more advantages in text representation . Assume Based on the conjecture that “the effective combination of topic model and word embedding model can enrich the text representation” refer to , this paC, the topic model TM can be obtained by training the LDA model. In addition, EM can also be obtained by training the word embedding model. For topic model, each document represents a probability distribution formed by some topics. Therefore, input the tokens contained in document Di into TM, and the topic distribution of the document DTDi can be obtained:i ∈ Rτ, |Di|=n, which shows that there are n words in document Di, and the document-level topic distribution DTDi is a τ-dimensional vector. For document Di, the static representation of the included tokens can be easily obtained, and the word embedding of Di is represented asWEi ∈ Rφ. Similar to the method in literature [DTEi is obtained by combining document-level topic representation and document embedding representation:Based on the corpus terature , the finℵ × n probability distribution matrix, where ℵ denotes the number of hidden topics and n denotes the number of words. After transposing, we can get the topic distribution of each word. For any token Tij in Di, the word-level topic distribution WTDi is calculated as follows:i, TM(Tij) ∈ Rτ, which denotes that the topic distribution dimension of Tij is τ, and the word-level topic distribution WTDi is also a τ-dimensional vector. Similarly, the final representation vector WTEi for document is obtained by concatenating the word-level topic representation and the document embedding representation:For topic model, the topic-word distribution information can be obtained when training TM, which can be regarded as As shown in Data processing is an important concept in many domains of scientific research ,35. In tWithin the whole framework, the feature extraction layer plays a pivotal role in transforming texts into vector representations with semantic information. And, the output of this layer largely determines the quality of the subsequent NLP tasks. Considering the complexity of the representation method and the recognition quality refer to , the feaTo further utilize the obtained text representation to complete the topic recognition task, this framework will use two excellent classifiers: LR and SVM.hθ(xi)=θTxi+b. The part after “+” is a regularization term, which helps to alleviate the model's overfitting.LR is a classic classification model. From a mathematical point of view, the model can be considered as adding a sigmoid function mapping on the basis of linear regression, which can improve the nonlinear capability. In more detail, the final goal of LR is to find the best plane to make the data linearly separable, while the nonlinear mapping reduces the weight of the points far away from the classification plane, and relatively increases the weight of the most relevant data points. Relatively speaking, LR is simple, easy to parallelize, and can be explained strongly, so it is often used to solve the binary classification problem in reality. The common solving methods of LR include stochastic gradient descent, Newton's method, etc. The cost function is a logarithmic loss function, which is generally expressed as follows:SVM is a generalized linear classifier that uses supervised learning to perform binary classification on data, whose final goal is to find the best classification hyperplane and ensure the maximum geometric interval. In the process of finding the decision boundary, SVM only considers the support vector, which is the local point near the classification surface. And, the ordinary samples other than the support vector will not participate in the final hyperplane decision. Therefore, the dependence on the number of training samples is greatly reduced, and the training efficiency is improved. In addition, for samples that are linearly inseparable in a finite-dimensional vector space, the appearance of kernel functions such as Gaussian, Laplace RBF, and Sigmoid realize the nonlinear separability of SVM. Generally speaking, the cost function of the SVM can be expressed as follows:The content within the whole bracket with “+” index is the hinge loss function, which has the following meaning:Python 3.7.7.In this section, all experiments are performed on a PowerEdge T640 tower server with Intel Xeon Gold 6238 processor, 128 GB DDR4 RDIMM memory, NVIDIA GeForce RTX 2080Ti. And, the software environment is CentOS 7.6, https://scikit-learn.org/0.19/datasets/twenty_newsgroups.html) and BBC News (https://mlg.ucd.ie/datasets/bbc.html) are selected in this paper. These text data are all from the real world and marked with topic category tags.According to the task requirements, two commonly used News text datasets 20NewsGroup . Thus, it adds a certain degree of difficulty to topic recognition. Python, we firstly filter out the common stop words, punctuations, numbers, and words with a total frequency of less than 3 in the document from the original text, then build and encode dictionaries based on the words.20NewsGroup and BBC News are both English text datasets, so we do not need to consider word segmentation for them. Besides, we will make use of some existing methods for preprocessing ,38. WithLdaMulticore training method in the GenSim library is called during LDA training. The parameters are set as chunkSize = 200, passes = 50, workers = 31, and the rest are the default values. When training Word2vec , the training was carried out based on the CBOW model, with iter = 8 and sg = 0. When training Glove (https://github.com/stanfordnlp/GloVe), the parameters are set as verbose = 2. memory = 4.0, vocab_min_count = 5, max_iter = 15, window_size = 15, binary = 2, num_threads = 24, and x_max = 10. In addition, it is necessary to point out that the target output vector dimension is a scalar, and the specific value can be changed as needed. When calculating the vector representation of the target word, the word embedding model may encounter the OOV (out of vocabulary) problem. In this case, we will generate a vector of values between  in a specific dimension as the embedding representation of the word.After preprocessing, we input the text corpus into the topic recognition framework for model training. In order to make full use of the computing power of the server, the newton-cg, sag, lbfgs, liblinear, and saga. After a lot of experiments, we chose to use lbfgs to solve the problem, with max_iter set to 100 and C set to 1.0. Regarding SVM, the kernel functions that can be used include linear, poly, rbf, sigmoid, and precomputed. After testing, we finally choose linear, with C set to 1 and gamma set to 1. For the purpose of enhancing the credibility of the experimental results, the parameters of the classifier are kept unchanged when compared with other models. Besides, the 5-fold cross validation method is adopted during the experiments.In this paper, we use LR and SVM to evaluate the effect of topic recognition. Both of these classifiers have detailed implementations in sklearn. To our best knowledge, the common methods for solving LR's loss function include Macroscopically speaking, the topic model is a statistical model used to discover abstract topics in a series of documents. In the proposed topic recognition framework, the quality of the LDA model is closely related to the final topic recognition effect. Here, we will give relevant evaluation indicators.Z, the formula for calculating the confusion degree of the trained topic model on the test set is as follows:Artificial topic quality judgment methods require a lot of manpower and material resources, and the emergence of those simulated artificial evaluation methods has brought new ideas to researchers. Among them, perplexity is a common topic model evaluation method . In shorp(T) in the numerator represents the probability of each word in the test set, and the specific calculation formula of p(T) is as follows:Here, the denominator in formula  represenp(Z|D) represents the probability of each topic in a document, and p(T|Z) represents the probability of each word in a certain topic. In the following experiments, the Perplexity indicator is abbreviated as PERP.Here, distribution hypothesis of linguistics, and many calculation methods such as CU Mass, CUCI, and Cv have been proposed based on this hypothesis [Cv performs better. Therefore, this paper will adopt PERP and Cv to comprehensively evaluate the quality of topic model from an indirect and direct perspective.To some extent, the evaluation of topic models by perplexity is essentially achieved by evaluating the performance of the model in downstream tasks, so this is an indirect method. Actually, there are some direct evaluation methods that are mainly based on the internal characteristics of the language. “Topic coherence” is another type of evaluation method used in this paper. This type of method is mainly used to automatically reveal the coherence of topic, where the larger the coherence value, the better the topic model. Its basic idea is rooted in the pothesis . In litepothesis , Röder eTopic recognition for news text can be considered as a classification problem for the long text. Considering that this module pays more attention to the quality of classification, this paper will use the common confusion matrix. For the news dataset in this paper, there are many categories. Correspondingly, for the single label multi-classification problem, Micro-F1 score is used to evaluate the proposed model:In the following experiments, we will first verify the effectiveness of the idea of fusion of the word embedding model and topic model for news topic recognition, and then explore the best way of fusion. Furthermore, we have reproduced some related research work in recent years, and finally verify the superiority of the proposed text topic recognition framework based on word embedding enhancement.SGL. Performing a vector summation operation on the text representations obtained by the Glove and LDA methodsCGL. Concatenating the representation vectors obtained by Glove and LDA methodsSWL. Performing a vector summation operation on the text representations obtained by the Word2vec and LDA methodsCWL. Concatenating the representation vectors obtained by Word2vec and LDA methodsBased on the theoretical analysis of different text representation methods refer to , this paThe detailed experimental results are shown in In general, the highest Micro-F1 value on the 20NewsGroup dataset does not exceed 0.83, which is related to factors such as the variety of topics in the dataset and the high similarity of some topics. From the perspective of the classifier, the results show that the effect of SVM is better than that of LR, which is consistent with the theoretical analysis results. From the perspective of the dimension of the text representation vector, it can be found that Micro-F1 is increasing with the increase of the dimension, but the growth rate gradually decreases. Especially for SWL and Word2vec models, when the dimension of vector is greater than 400, Micro-F1 basically remains unchanged or even decreases. In summary, the combination effect of the topic model and the word embedding model is obviously better than any single model, which shows the correctness of the conjecture that “the effective combination of the topic model and the word embedding model can enrich the text representation and then improve the NLP downstream task effect” to a certain extent. Among the above models, the CGL model performs the best, which denotes that the concatenation of representation vectors obtained by Glove and LDA can indeed enrich text representation information and improve the topic recognition quality.Moreover, we analyze the quality of the text representation vector from a semantic perspective. In the semantic space, each document is represented as a dense vector. Assuming all documents are mapped into a 2-dimensional space, the densely distributed area indicates that the potential topics of these documents are relatively similar. Considering that the text representation vector has high-dimensional sparse characteristics, we use Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP)  and K-meFP2, FPC models with different fusion strategies.FPW. Zhou et al.  proposedDRIWL. Wang et al.  proposedTDE. Hui et al.  proposedIn this section, comparative experiments will be carried out to verify the superiority of the proposed framework for the problem of news topic recognition. The relevant information of baselines is described as follows. Note that differing from the existing methods, this framework also considers the impact of the optimal number of topics on the final results. In order to make the experimental results more convincing, the word vector dimension and the LDA topic representation vector dimension in baselines are both set to 300:From the perspective of model construction, all models in baselines improve the quality of text representation by making comprehensive use of the advantages of TF-IDF, LDA, Word2vec, and Glove. In this regard, we have conducted some analysis on all models involved in the experiment. The overview of different fusion models is revealed in τ, which means the number of topics when training the LDA model. Moreover, the parameter τ will affect the quality of the topic model, and then indirectly affect the quality of the whole framework. Therefore, it is necessary to explore the optimal number of topics before evaluating the proposed two representation methods.For the two text representation models proposed in this paper, it can be seen that the essential difference lies in the presentation granularity of the topic distribution, and the topic distribution dimension is related to Cv. The specific experimental results are shown in For the 20NewsGroup dataset, some previous work pointed out that the optimal number of topics is around 20 . For thiτ is set to 20, the results under the PERP and Cv indicators are better, which indicates that the topic quality and topic coherence generated by LDA are both relatively good. Finally, we choose τ=20 as the optimal topic number. Comprehensive analysis shows that when τ is set to 20, the quality of the LDA model obtained is better.For the above experimental values, we mark the best three results under different evaluation indicators. It can be found that when ∗, FPC∗, FP2∗, and TDE∗ on the test dataset is worse than that of FPW, FPC, FP2, and TDE. However, the recognition equality of DRIWL∗ is better than DRIWL. The primary reason is that the fusion effect of TF-IDF and Word2vec is better than the fusion effect of TF-IDF and Glove. Finally, to evaluate the above models from the perspective of the classifier, it can be found that SVM often has a better result than LR for topic recognition on this dataset.Similarly, for the BBC News dataset, we set the number of topics between 5 and 55 to train the LDA model, and the detailed results are shown in Cv when τ=20. Based on above analysis, we finally choose 20 as the optimal topic number. Then, we conducted corresponding comparative experiments, the results of which shown in For BBC News dataset, it is relatively small, so the training time of the LDA model has been significantly reduced. According to the results in On the whole, SVM and LR classifiers both have achieved relatively high Micro-F1 results, which may due to the fact that the BBC News dataset has a small scale and few topic categories. Compared with other methods, the text representation obtained by the DTE method has a small dimension but performs the best, reaching 0.969 based on both SVM and LR classifiers. In contrast, the WTE text representation model has an average performance on this dataset, but the difference between results is no more than 0.1.Based on the idea that adding word embedding information on the basis of the topic model can enrich the semantic information of the document, we propose two granularity text representation models, which are named DTE and WTE. Both models perform unsupervised learning on corpus to obtain the final representation vectors, which is simple to implement and can improve the quality of text representation. After testing on different datasets with other models, we found the two models that have achieved better topic recognition results; especially, the DTE method achieves the highest Micro-F1 score by using different classifiers on different datasets. According to the above theoretical analysis and the subsequent experimental results, we have reason to believe that the effective combination of the topic model and the word embedding model can make up for the defects of a single model to a certain extent. At the same time, it also shows the effectiveness and superiority of the proposed method based on word embedding enhancement for the problem of news topic recognition.For the above experiments, we can also draw some other conclusions. First of all, for the document-level topic distribution in the DTE method, it does not need to be large. For example, when the dimension of the representation vector is 600 with the CGL method on 20NewsGroup, it obtains the Micro-F1 scores of 0.812 and 0.796 based on SVM and LR, respectively. In With the evolution of the big data era, we are facing more and more serious information load problems in real life. This paper aims to realize the accurate and automatic sorting of Internet news text data. Considering that the single topic model and the word embedding model have certain defects, and the fusion of the two can enrich the representation information of the text, we proposed a novel text representation method and conducted preliminary exploration based on the classic TF-IDF, LDA, Word2VEC, and Glove models. Finally, we proposed two granularity fusion strategies for the topic model and the word embedding model, named DTE and WTE. Besides, we also formed a topic recognition framework based on word embedding enhancement. The core of the framework is to achieve a better integration of topic distribution representation and word embedding information. And, its essence lies in the realization of a more informative text representation method, which not only considers the relationship between document and topic but also integrates the context information of words. Through a large number of experiments on the 20Newsgroup and BBC News datasets, we first verified that the combination of the topic model and the word embedding model can effectively take advantage of the topic distribution, semantic knowledge, and syntactic relationship to achieve better text representation. In addition, we also compare DTE and WTE with the methods in related literature, and the results further prove the effectiveness and superiority of the proposed method for the problem of news topic recognition.The word embedding enhancement concept proposed in this paper is implemented in a simple and efficient way with good results, but the deeper integration ideas have not been considered. Therefore, we can start from the mathematical principles of the model and try to design a better fusion model to solve more NLP downstream tasks.It is noteworthy that the amount of data used in the above experiments is limited. When processing the real massive news texts, the single machine environment is not enough to support subsequent storage, management, and analysis tasks. In response to this practical problem, we consider extending the proposed method to the Spark platform.Compared with classical SVM, our team found that the Relevance Vector Machine (RVM) not only had a better classification performance on large document datasets  but alsoFor the work of this paper, we believe that there are still the following directions that are worthy of further study: