The catalytic conversion of dinitrogen (N2) into ammonia under ambient conditions represents one of the Holy Grails in sustainable chemistry. As a potential alternative to the Haber–Bosch process, ...the electrochemical reduction of N2 to NH3 is attractive owing to its renewability and flexibility, as well as its sustainability for producing and storing value‐added chemicals from the abundant feedstock of water and nitrogen on earth. However, owing to the kinetically complex and energetically challenging N2 reduction reaction (NRR) process, NRR electrocatalysts with high catalytic activity and high selectivity are rare. In this contribution, as a proof‐of‐concept, we demonstrate that both the NH3 yield and faradaic efficiency (FE) under ambient conditions can be improved by modification of the hematite nanostructure surface. Introducing more oxygen vacancies to the hematite surface renders an improved performance in NRR, which leads to an average NH3 production rate of 0.46 μg h−1 cm−2 and an NH3 FE of 6.04 % at −0.9 V vs. Ag/AgCl in 0.10 m KOH electrolyte. The durability of the electrochemical system was also investigated. A surprisingly high average NH3 production rate of 1.45 μg h−1 cm−2 and a NH3 FE of 8.28 % were achieved after the first 1 h chronoamperometry test. This is among the highest FEs reported so far for non‐precious‐metal catalysts that use a polymer‐electrolyte‐membrane cell and is much higher than the FE of precious‐metal catalysts (e.g., Ru/C) under comparable reaction conditions. However, the NH3 yield and the FE dropped to 0.29 μg h−1 cm−2 and 2.74 %, respectively, after 16 h of chronoamperometry tests, which indicates poor durability of the system. Our results demonstrate the important role that the surface states of transition‐metal oxides have in promoting electrocatalytic NRR under ambient conditions. This work may spur interest towards the rational design of electrocatalysts as well as electrochemical systems for NRR, with emphasis on the issue of stability.
A sustainable alternative to the Haber–Bosch process: The introduction of oxygen vacancies into hematite (α‐Fe2O3) nanorods promotes the electrocatalytic synthesis of ammonia from N2 and water at room temperature and atmospheric pressure (see picture). A higher concentration of surface oxygen vacancies leads to both improved NH3 yield and a large NH3 faradaic efficiency.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Non‐small‐cell lung cancer (NSCLC), with its aggressive biological behavior, is one of the most diagnosed cancers. Tumor‐associated inflammatory cells play important roles in the interaction between ...chronic inflammation and lung cancer, however the mechanisms involved are far from defined. In the present study, by developing an orthotopic NSCLC mouse model based on chronic inflammation, we proved that an inflammatory microenvironment accelerated the growth of orthotopic xenografts in vivo. Tumor‐associated macrophages, the most abundant population of inflammatory cells, were identified. Treatment with macrophage‐conditioned medium (MCM) promoted the growth and migration of NSCLC cells. Using bioinformatics analysis, we identified downregulated PP2Ac expression in NSCLC cells upon treatment with MCM. We further confirmed that this downregulation was executed in an NF‐κB pathway‐dependent manner. As IκB kinase (IKK) has been proved to be a substrate of PP2Ac, inhibition on PP2Ac could result in amplification of NF‐κB pathway signaling. Overexpression of PP2Ac, or the dominant‐negative forms of IKK or IκB, attenuated the acceleration of growth and metastasis by MCM. Using bioinformatics analysis, we further identified that CXCL1 and COL6A1 could be downstream of NF‐κB/PP2Ac pathway. Luciferase assay and ChIP assay further confirmed the location of response elements on the promoter regions of CXCL1 and COL6A1. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted proliferation and migration.
Tumor‐associated macrophages, the prominent type of inflammatory cells in non‐small‐cell lung cancer, can promote the growth and metastasis of cancer cells. Overexpression of PP2Ac, or the dominant‐negative forms of IKK or IκB, attenuated the acceleration on cancer cell growth and metastasis by TAMs. CXCL1 and COL6A1 could be downstream of NF‐κB/PP2Ac pathway. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted cancer cell proliferation and migration.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objectives
Periodontitis is closely associated with kidney disease and reactive oxygen species (ROS) involvement. Mitochondria are the primary source of both endogenous ROS and renal energy. We ...investigated whether resveratrol (RSV) prevents renal injury and mitochondrial dysfunction in periodontitis rats.
Methods
Thirty male Wistar rats were divided into control, experimental periodontitis (Ep) and Ep‐RSV groups. To induce periodontitis, a steel ligature was placed on the cervix of the bilateral first maxillary molars. RSV (50 mg/kg/day) to the Ep‐RSV group and vehicle to the Ep and control groups were gavaged. After 8 weeks, alveolar bone loss, pocket depth, gingival blood index and tooth mobility were assessed. Oxidative stress parameters, mitochondrial structure, mitochondrial membrane potential (MMP), mitochondrial ROS, adenosine triphosphate (ATP), sirtuin 1 (SIRT1) and peroxisome proliferator‐activated receptor‐γ coactivator‐1α (PGC‐1α) were analysed in renal. Renal function and histology were also evaluated.
Results
Compared with the control group, the Ep group showed renal structural destruction, elevated oxidative stress levels, mitochondrial structure destruction, MMP loss, mitochondrial ROS accumulation, ATP reduction, and decreased SIRT1 and PGC‐1α levels. RSV prevented these destruction (p < 0.05). However, there was no significant impairment in renal function (p > 0.05).
Conclusions
Periodontitis induces mitochondrial dysfunction in renal tissues. Resveratrol exerts a preventive effect on periodontitis‐induced kidney injury by preventing mitochondrial dysfunction.
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CMK, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The contribution of extracellular polymeric substances (EPS), including loosely bound EPS (LB-EPS) and tightly bound EPS (TB-EPS), to the aggregation of both aerobic and anaerobic sludge is explored ...using the extended DLVO theory. It is observed that the aggregation abilities of both sludge samples decrease with the extraction of LB-EPS and TB-EPS, implying the crucial roles of EPS in sludge aggregation. Furthermore, through analyzing the interaction energy curves of sludge before and after the EPS extraction using the extended DLVO theory, it is found that both LB-EPS and TB-EPS have a substantial contribution to the sludge aggregation. The interaction energy of LB-EPS is always negative, suggesting that the LB-EPS always display a positive effect on the sludge aggregation. On the other hand, the interaction energy of TB-EPS is not always negative, depending on the separation distance between sludge cells. These results imply that the LB-EPS and TB-EPS have different contributions to the sludge aggregation.
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IJS, KILJ, NUK, PNG, UL, UM
Pancreatic cancer is one of the most lethal gastrointestinal tumours, the most common pathological type is pancreatic adenocarcinoma (PAAD). In recent year, immune imbalanced in tumour ...microenvironment has been shown to play an important role in the evolution of tumours progression, and the efficacy of immunotherapy has been gradually demonstrated in clinical practice. In this study, we propose to construct an immune‐related prognostic risk model based on immune‐related genes MMP14 and INHBA expression that can assess the prognosis of pancreatic cancer patients and identify potential therapeutic targets for pancreatic cancer, to provide new ideas for the treatment of pancreatic cancer. We also investigate the correlation between macrophage infiltration and MMP14 and INHBA expression. First, the gene expression data of pancreatic cancer and normal pancreatic tissue were obtained from The Cancer Genome Atlas Program (TCGA) and The Genotype‐Tissue Expression public database (GTEx). The differentially expressed immune‐related genes between pancreatic cancer samples and normal sample were screened by R software. Secondly, univariate Cox regression analysis were used to evaluate the relationship between immune‐related genes and the prognosis of pancreatic cancer patients. A polygenic risk score model was constructed by Cox regression analysis. The prognostic nomogram was constructed, and its performance was evaluated comprehensively by internal calibration curve and C‐index. Using the risk model, each patient gets a risk score, and was divided into high‐ or low‐ risk groups. The proportion of 22 types of immune cells infiltration in pancreatic cancer samples was inferred by CIBERSOFT algorithm, correlation analysis (Pearson method) was used to analyse the correlation between the immune‐related genes and immunes cells. Then, we applied macrophage conditioned medium to culture pancreatic cancer cell line PANC1, detected the expression of MMP14 and INHBA by qRT‐PCR and Western blot methods. Knock‐down MMP14 and INHBA in PANC1 cells by transfected with shRNA lentiviruses. Detection of migration ability of pancreatic cells was done by trans‐well cell migration assay. A subcutaneous xenograft tumour model of human pancreatic cancer in nude mice was constructed. In conclusion, an immune‐related gene prognostic model was constructed, patients with high‐risk scores have poorer survival status, M2‐phenotype tumour‐associated macrophages (TAMs) up‐regulate two immune‐related genes, MMP14 and INHBA, which were used to establish the prognostic model. Knock‐down of MMP14 and INHBA inhibited invasion of pancreatic cancer.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The selection of electron donors and nonfullerene acceptors (NFAs) in organic solar cells (OSCs) is crucial for improving photovoltaic performance. Machine learning (ML) has brought a breakthrough ...solution. Herein, 292 donor‐NFA pairs with experimental OSC parameters from the reported articles are collected. The ML descriptors include device processing parameters, molecular properties, and molecular structure. The five ML regression models, random forest (RF), extra tree regression, gradient boosting regression tree, adaptive boosting, and artificial neural network (ANN) are trained. GridSearchCV is used for hyperparameter optimization of ML regression models. The SHapley Additive exPlanation approach is employed to analyze descriptor importance. Among the trained five ML models, the RF model shows superior performance, achieving Pearson's correlation coefficient (r) of 0.81 on the test set. Based on the donors and NFAs in constructed dataset, the 9779 donor–NFA pairs for OSCs are generated by randomly combining donor and acceptor molecules. The trained RF model is utilized to predict the power conversion efficiency (PCE) of new donor–acceptor pairs for OSCs. The results indicate that the OSC composed of PBDB‐TF as donor and L8‐BO as acceptor can achieve the remarkable PCE of 17.9%.
Innovative machine learning methods expedite selection of electron donors and nonfullerene acceptors for organic solar cells. The Pearson's correlation coefficient of the trained random forest model is 0.81, enabling rapid identification of high‐performance donor–acceptor pairs like PBDB‐TF and L8‐BO, achieving 17.9% power conversion efficiency.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Developing non-fullerene acceptors (NFAs) by modifying the backbone, side chains and end groups is the most important strategy to improve the power conversion efficiency of organic solar cells ...(OSCs). Among numerous developed NFAs, Y6 and its derivatives are famous NFAs in the OSC field due to their good performance. Herein, in order to understand the mechanism of tuning the photovoltaic performance by modifying the Y6's center backbone, -spacer and side-chains, we selected the PM6:Y6 OSC as a reference and systematically studied PM6:AQx-2, PM6:Y6-T, PM6:Y6-2T, PM6:Y6-O, PM6:Y6-1O and PM6:Y6-2O OSC systems based on extensive quantum chemistry calculations. The results indicate that introducing quinoxaline to substitute thiadiazole in the backbone induces a blue-shift of absorption spectra, reduces the charge transfer (CT) distance (
d
) and average electrostatic potential (ESP), and increases the singlettriplet energy gap (
E
ST
), CT excitation energy and the number of CT states in low-lying excitations. Inserting thienyl and dithiophenyl as spacers generates a red-shift of absorption spectra, enlarges
d
and average ESP, and reduces
E
ST
and the number of CT states. Introducing furo3,2-
b
furan for substituting one thieno3,2-
b
thiophene unit in the Y6's backbone causes a red-shift of absorption spectra and increases
E
ST
,
d
and average ESP as well as CT excitation energy. Introducing alkoxyl as a side chain results in a blue-shift of absorption spectra, and increases
E
ST
,
d
, average ESP, CT excitation energy and the number of CT states. The rate constants calculated using Marcus theory suggest that all the molecular modifications of Y6 reduce the exciton dissociation and charge recombination rates at the heterojunction interface, while introducing furo3,2-
b
furan and alkoxyl enlarges CT rates.
PM6:Y6, PM6:AQx-2, PM6:Y6-T, PM6:Y6-2T, PM6:Y6-O, PM6:Y6-1O and PM6:Y6-2O OSCs were studied in order to understand how to adjust photovoltaic performance by modifying the Y6's center backbone, -spacer and side-chains.
Molecular descriptors are critical for determining the accuracy of machine learning (ML) study on organic photovoltaics (OPV). To unravel the complex relationship between molecular properties and ...device performance, on the basis of 510 donor‐acceptor pairs in OPV active layer, the open‐circuit voltage loss (VOC‐loss), dielectric constants of donor and acceptor (ε‐D and ε‐A) were firstly implemented into property descriptor set that includes 41 quantities totally. Then, the five ML algorithms were applied to compare the property descriptor sets with and without VOC‐loss, ε‐D and ε‐A (coded as new and old sets) in the prediction of photovoltaic parameters. The ML results of Pearson's correlation coefficient and the slope of regression lines indicate the performances of new molecular descriptor set are prevailing to that of old set. Furthermore, the Gini important analysis indicates that the ε‐D, ε‐A and VOC‐loss are very important parameters for determining device performance. Higher dielectric constants and lower VOC‐loss will be more beneficial to the performance of OPV devices.
The open‐circuit voltage loss (VOC‐loss), dielectric constants of donor and acceptor materials (ε‐D and ε‐A, respectively) were firstly implemented into molecular property descriptor set (MPDS). The machine‐learning algorithms random forest, extra trees regressor, gradient boosting regression tree, adaptive boosting and extreme gradient boosting were applied to compare the MPDS with and without VOC‐loss, ε‐D and ε‐A in photovoltaic parameters prediction.
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BFBNIB, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Molecular stacking modes that determine morphology of bulk‐heterojunctions are important because of their effects on photovoltaic performance of organic solar cells (OSCs). Here, in order to ...investigate how molecular stacking pattern in OSCs heterojunction impact on electronic structures and properties, and then influence photovoltaic performance, this work selected D18:Y6 OSC as a representative system. On the basis of semi‐empirical quantum chemistry and density functional theory calculations, we studied the geometries, electronic structures and excitation properties, as well as electron and hole couplings of D18 and Y6 molecules, Y6 dimers, D18/Y6 and D18/Y6‐dimer complexes which are heterojunction interface models. The results indicate that the molecular stacking effects on open‐circuit voltage (VOC) can be attributed to the influences on charge transfer (CT) excitation energies because molecular stacking modes at donor/acceptor heterojunction interface can significantly change excitation energies. Furthermore, the molecular stacking modes can cause drastically different electron and hole couplings, and then affect charge transfer/transport rates. Hence, the molecular stacking effects on short‐circuit current density (JSC) can be understood from the effects on electron and hole couplings. The molecular stacking modes that are favorable to improving VOC and JSC of D18:Y6 OSC were also discussed.
This work selected D18:Y6 organic solar cells as represent system. On the basis of semi‐empirical quantum chemistry and density functional theory calculations, studied the geometries, electronic structures and excitation properties, as well as electron and hole couplings of D18 and Y6 molecules, Y6 dimers, D18/Y6 and D18/Y6 dimer complexes which are heterojunction interface models. Further, the effect of molecular stacking modes on open‐circuit voltage and short‐circuit current density were investigated.
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BFBNIB, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Upconversion luminescence (UCL) in organometallic complexes has attracted great interest in photovoltaics and biological applications due to their fascinating energy transfer mechanism from ...low‐energy photon to high‐energy photon. However, photon‐upconversion operating in a single discrete entity remains a challenge caused by low‐absorption cross section of the luminescent lanthanide element. Here, a novel upconversion system is reported combining Yb (Ytterbium) sensitizers and Er (Erbium) activators in the film by electropolymerization, which leads to excited‐state absorption (ESA) and energy transfer upconversion (ETU) processes. For the first time, the UCL has been achieved in the thin films upon near‐infrared laser irradiation, and the upconversion intensity exhibits up to 30‐fold enhancement with the variation of Yb/Er ratio.
Co‐polymers containing the Yb3+ sensitizer and Er3+ activator are formed by chemical polymerization or electropolymerization from Ln complexes with styrene group. The construction of a novel upconversion Yb/Er system is first realized with bright visible/near‐infrared emissions in organic thin film.
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