搜索结果：Organic Chemistry

It has long been suggested that organic solvents disrupt the solvation shell around phosphate ions, which might facilitate calcium phosphate (CaP) nucleation. This would explain recent experimental findings where organic solvents─ethanol, isopropanol, and acetone─produce a denser CaP coating when synthesized on marble for conservation applications. In this work, computational methods are used to investigate the solvation shell of phosphate ions in mixed organic-aqueous solutions. Relative one-to-one interaction energies between the phosphates and solvents were calculated with density functional theory (DFT) and suggest that ethanol and isopropanol could displace water in the hydration sphere of PO43-, HPO42-, and H2PO4-. Classical molecular dynamics simulations with models benchmarked to these DFT interaction energies were then used to investigate solvation under bulk solvent conditions. In mixed organic-aqueous conditions, we find that the behavior in the phosphate solvation shell is dependent on the solvent and protonation state. More specifically, none of the three organic solvents consistently disrupts the hydration shell of the phosphates, which would correlate with the experimental findings. Ultimately, this suggests that the influence of the organic solvent on the solvation shell of the phosphate ions may not contribute significantly to the improved synthesis of CaP.

Metal-organic frameworks (MOFs) are promising platforms for drug delivery due to their high porosity, tunable chemistry, and controlled release capabilities. However, their clinical translation is limited by insufficient safety data, particularly regarding the toxicity of organic linkers that may leach or degrade under physiological conditions. Experimental evaluation of linker biocompatibility across the vast MOF design space is impractical, creating a critical bottleneck for biomedical applications. Here, we present an integrated machine learning framework for systematic toxicity assessment of MOF organic linkers. Using acute toxicity data from the TOXRIC database, we trained four complementary modeling architectures: a directed message-passing graph neural network (Chemprop), a transformer-based SMILES model (ChemBERTa-2), a Random Forest using Morgan fingerprints, and a Support Vector Machine based on physicochemical descriptors. Across 5-fold stratified cross-validation, all models demonstrated strong predictive performance, achieving micro F1 scores up to ∼0.87, and microaveraged ROC-AUC values between ∼0.95 and 0.96, indicating robust discrimination despite substantial class imbalance. The trained models were applied to a large hypothetical MOF linker library, and ensemble predictions were used to improve robustness and reduce model-specific bias. Applicability-domain analysis based on chemical space overlap and nearest-neighbor similarity confirmed that predictions remained within well-supported regions of chemical space. To enable mechanistic interpretability, we integrated graph-based SHAP analysis with a SHAP-weighted Morgan fingerprint representation, allowing systematic identification of molecular substructures driving high-severity toxicity predictions. The most influential motifs showed strong agreement with independently documented toxic scaffolds, including polycyclic aromatic hydrocarbons. Together, this framework provides a scalable, accurate, and interpretable approach for prioritizing safe MOF linkers and guiding experimental screening toward candidates with favorable safety profiles.

Diradicals have gained interest for their unique electronic properties and potential applications in organic electronics and semiconductors. However, precise manipulation of electronic states and achieving satisfactory device performance remain challenging. Herein, we report the synthesis and characterization of tetraphenylethylene-bridged salts and their neutral diradical counterparts obtained via two-electron reduction. With extended conjugation and electron-withdrawing N-heterocyclic carbene (NHC) backbones, enhanced open-shell character is observed. Through this systematic study, a backbone engineering strategy is established that allows precise control over spin states and diradical character in carbon-centered NHC diradicals. Leveraging this strategy, compound 2d, with moderate diradical character induced by extended conjugated structures and strong electron-withdrawing groups, was employed in a spin-coated organic field-effect transistor (OFET) device. The device achieved a record-high hole mobility of 4.53 cm2·V-1·s-1, representing exceptional performance among open-shell organic semiconductors for high-performance OFETs. This not only demonstrates the outstanding charge-transport capability of 2d but also underscores the significant potential of this approach for developing functional open-shell organic semiconductors.

Restrictions on antibiotic growth promoters in poultry production have driven the search for safe, natural alternatives. Organic acids, herbal additives and spirulina are promising options due to their antimicrobial, antioxidant and growth-enhancing effects. The purpose of this experiment was to evaluate the effects of formic acid (FAc), herbal mixture (HMX) and spirulina powder (SPI) as potential antibiotic alternatives in broiler diets, specifically examining their impact on growth, carcass characteristics, blood biochemistry and intestinal microbial count. Six replicates of ten unsexed chicks per group comprised the eight experimental groups to which 480 one-day-old Ross 308 broiler chicks were randomly assigned. The treatments were as follows: T1 (control); T2 (0.5 g Colistin antibiotic/kg diet); T3 (2 cm3 FAc/kg diet); T4 (4 cm3 FAc/kg diet); T5 (2 g HMX/kg diet); T6 (3 g HMX/kg diet); T7 (0.5 g SPI/kg diet); and T8 (1 g SPI/kg diet). Significant differences were detected in daily body weight gain (DBWG) and live body weight (LBW), with the spirulina-treated groups (T7 and T8) showing the highest values. Also, significant influences on feed intake (FI), feed conversion ratio (FCR) and performance index (PI), with the HMX groups showing the most favourable FCR and the highest PI. Blood biochemistry and antioxidant markers were influenced by the HMX and SPI treatments. The SPI groups showed reduced liver enzyme levels, while the HMX groups demonstrated improved protein profiles and enhanced antioxidant enzyme activity. Microbial analysis revealed that FAc and HMX treatments led to a reduction in pathogenic bacteria, with T3, T4 and T5 showing the lowest levels of Escherichia coli and Salmonella. These results suggest that FAc, HMX and SPI are promising dietary supplements for enhancing both the broiler chickens' growth rates and general health.

Thin films of organic semiconductors obtained by vapor deposition under certain conditions are known to have unique thermodynamic and structural properties, for which they have been named ultrastable. The use of all-atom molecular dynamics simulations for their study is gaining interest due to the possibility of simplifying the process of their deposition and examining their properties at the molecular level. This work provides a systematic and thorough investigation of the key parameters of thin films that characterize their stability and morphology: energy, density, fictive temperature, and orientational order parameter. The results of studying these properties using molecular dynamics for vapor-deposited thin films of three organic semiconductors (TNB, TPB, and TPD) led to a number of valuable insights. First, it was shown that the dependencies of thermodynamic properties on deposition temperature (Tdep) obtained from simulations are consistent with those observed experimentally but shifted toward higher temperatures. Moreover, it was demonstrated for the first time that all glass stability indicators for each of the compounds studied show a maximum at a single deposition temperature. These observations highlight the close relationship between Tdep and the characteristics of the resulting thin films, which can be used to develop a methodology for producing ultrastable glasses with tunable characteristics. The results of this work show that further application of the molecular dynamics method to study vapor-deposited thin films of organic semiconductors may reveal intriguing aspects of their formation and structure.

Soil organic carbon (SOC) is a key indicator for assessing soil quality. Rapid and accurate acquisition of the spatial distribution of SOC content can guide production management in reclaimed farmland in mining areas. This study takes the Xinglongzhuang Coal Mine in Yanzhou District, Jining City, as the study area, with reclaimed farmland SOC as the research subject. Based on unmanned aerial vehicle (UAV) multispectral remote sensing images and ground sampling point data, three sets of feature variables were constructed: a full variable set, a variance inflation factor (VIF) screened variable set, and a genetic algorithm (GA) screened variable set. Four deep learning algorithms, namely convolutional neural network (CNN), graph neural network (GNN), recurrent neural network (RNN), and transformer, are employed to construct a total of 12 SOC content estimation models. Based on the optimal estimation model CNN-GA, the model was optimized and improved by generating pseudo-reflectance samples through Kernel-SMOTE algorithm oversampling. The results indicate that (1) following variable selection through the use of GA, the accuracy of the majority of estimation models saw a significant improvement. (2) Among the four deep learning algorithms, the model constructed using the CNN algorithm achieved the highest accuracy. (3) CNN-GA-SMOTE was identified as the optimal estimation model, achieving an R2 of 0.864 and RMSE of 0.827 g kg-1 for the modeling set, with R2 of 0.857 and RMSE of 0.796 g kg-1 for the validation set. The SOC content of reclaimed farmland was estimated using this model, with an overall range of 7.53~13.40 g kg-1. This study provides technical support for soil quality assessment in reclaimed mining areas.

Nontargeted air analysis using methods based on gas chromatography (GC) and mass spectrometry (MS) is very important for the discovery of new potentially dangerous volatile organic compounds (VOCs). Solid-phase microextraction (SPME) is one of the simplest and cost-efficient sampling techniques for screening VOCs in air, but the extraction effectiveness of detected compounds can substantially vary depending on their properties and affinity to the fiber coating. This study was aimed at the development of a novel method for semi-quantitative determination of VOCs identified in air samples using SPME and GC-MS. Extraction effectiveness was estimated from fiber coating-air distribution constants predicted using linear solvation energy relationship and numerical modeling with COMSOL Multiphysics. MS detector response factors were estimated using multiple regression obtained from experimental responses of 111 VOCs and SVOCs, their molecular weights, octanol-water partitioning coefficients, polar surface areas, and fractional ion abundances of base ions. Numerical modeling using COMSOL Multiphysics improved the accuracy for less volatile analytes with greater molecular weight, particularly at lower extraction times. For 12 of 14 tested analytes, recoveries from spiked nitrogen samples were in the range between 39% and 275%. The developed method was successfully applied for determining approximate concentrations of VOCs identified in samples of air, and for determination of approximate time-weighted average concentrations of VOCs. It can be recommended for the quick estimation of approximate concentrations of VOCs detected during nontargeted analysis when calibration standards are not available or when high accuracy is not needed.

Chemical mechanisms are one of the major sources of bias in chemical transport model simulations, making their improvement a critical step towards enhancing model performance and supporting air quality management and research. In this study, a newly developed chemical mechanism, the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM), integrated into the Community Multiscale Air Quality (CMAQ) modeling system, was evaluated through comparison with two traditional chemical mechanisms, Carbon Bond 6 version r3 with aero7 treatment of SOA (CB6r3_ae7) and State Air Pollution Research Center version 07tc with extended isoprene chemistry and aero7i treatment of SOA (Saprc07tic_ae7i), for China. Sensitivity simulations related to precursor reactive organic carbon (ROC) emissions were conducted to investigate the key driving factors of PM2.5 formation. The results indicate that, when using the traditional primary organic aerosol (POA) inventory, the differences among the three chemical mechanisms are within 0-0.14 for the R, 0-10 μg m-3 for the MB, and within 10 % for the NMB values. However, when the full-volatility emission inventory is applied in January, CRACMM exhibits improved performance in the Pearl River Delta (PRD) region. The MB is reduced by 3.0-7.8 μg m-3. In addition, the NMB decreases by 17 %-23 %, and the root mean square error (RMSE) is reduced by 1-6 μg m-3 compared with simulations using the traditional POA inventory across the four months. CRACMM predicts higher PM2.5 concentrations during spring, summer and autumn, mainly due to enhanced secondary organic aerosol (SOA) formation driven by increased precursor emissions. Benzene-toluene-xylene (BTX) species and semi-volatile organic compound (SVOC) emissions significantly contributed to PM2.5 formation in CRACMM. The SOA from BTX emissions accounts for nearly 50 % of the PM2.5 changes, while intermediate-volatility organic compounds (IVOC) and SVOC emissions mainly affect PM2.5 concentrations through SOA formation. These results indicate that CRACMM, when using the full-volatility inventory, can effectively compensate for the underestimation of PM2.5 mass that may occur with traditional POA treatment, particularly in regions with high photochemical activity and abundant S/IVOC precursors.

Conducting multi-mode detection of multiple targets simultaneously on a single platform can significantly enhance the accuracy and flexibility of the detection process. Herein, a fluorescence-colorimetric dual-mode sensing platform was constructed by in-situ coating polydopamine (PDA) on Cu/Ce multivalent metal-organic frameworks (Cu/Ce-MOFs). The obtained Cu/Ce-MOFs@PDA exhibits excellent fluorescent properties and multienzyme-like nanozymes activity (including mimics oxidase, peroxidase, phosphatase, and laccase), facilitating dual-mode detection of pesticides, phenolic pollutants, and biomolecules. Particularly, the excellent detection performance is attributed to the synergistic Ce4+/Ce3+-Cu2+/Cu+ redox cycling and the interfacial electron modulation of polydopamine. In addition, the sensing platform demonstrates excellent signal reproducibility, remarkable anti-interference capabilities and strong applicability to real samples, with a recovery ranging from 84.3% to 118.8%. This work demonstrates a generalizable approach for constructing multifunctional bimetallic MOFs-based nanozymes, enabling the development of integrated analytical platforms with multi-mode signal outputs for environmental and biosensing applications.

The development of smart circularly polarized luminescence (CPL) materials faces significant challenges, primarily centered on achieving high luminescence dissymmetry factors (glum) alongside broadly tunable responses. Here, we report a chiral scaffold based on covalent organic frameworks (COFs) for high-performance and adaptive photocontrollable time-evolving CPL, enabling identifiable and encrypted chiroptical outputs. Cyclodextrin modified on the COF generates multicolor CPL emission through noncovalent interaction with fluorophores. Blending the modified COF and fluorophores with polyethylene glycol (PEG) yields transparent mixed-matrix films exhibiting a high glum of -0.027 and absolute quantum yield (39%). Subsequently, sulfonato-merocyanine, a photochromic switch, is introduced to modulate the system's emission, endowing the reversible CPL signals with light-fueled tunability and time-dependent dynamic evolution. Notably, we fabricate mixed-matrix films to amplify the light-controllable CPL signals, where the glum varies between -0.009 and -0.044 upon 420 nm irradiation and thermal relaxation. A dynamic modulation range of glum ≈0.035 is achieved, which is a remarkable value reported among dynamic COF-based CPL materials. Furthermore, films featuring photocontrollable, self-erasable vector luminescent signals are achieved for dual-mode anticounterfeiting. This work provides insight into the design of intelligent luminescent materials.

Current strategies for microRNAs (miRNAs) detection in live-cell imaging are hindered by several methodological limitations, including poor delivery efficiency, inadequate signal amplification, insufficient target specificity, and overly complex reaction architectures. To address these issues, we present a streamlined cascade logic system mediated by multilayered metal-organic framework nanomaterials (PCZF-8), which integrates catalytic hairpin assembly (CHA) and DNAzyme sequences for the fluorescent detection of endogenous intracellular miRNAs (miR-21 and miR-155) and enables precise cancer cell identification. Central to this approach is a bifunctional double-loop hairpin probe (H1) that incorporates both miRNA recognition sequences and a DNAzyme motif, endowing it with dual capabilities for target binding and catalytic signal generation. Upon recognition of miR-21 and miR-155, the CHA-DNAzyme cascade amplification reaction is effectively triggered, enabling rapid cleavage of a fluorogenic substrate probe (H3) and a robust fluorescent output. Remarkably, the entire dual miRNAs recognition, CHA-DNAzyme cascade amplification, and logic-gated response are achieved with only three hairpin components (H1, H2, and H3), underscoring the system's molecular economy and design elegance. The assay achieves femtomolar (fM) detection limits for both miR-21 and miR-155 and operates as an AND-gated logic circuit, selectively identifying breast cancer cells based on their characteristic coexpression profile of these miRNAs. Furthermore, the intrinsic pH-responsive fluorescence property of PCZF-8 enhances cellular discrimination by distinguishing the acidic tumor microenvironment of cancer cells from that of normal cells. By synergistically combining nanomaterial engineering with molecular logic and cascade amplification, this platform establishes a novel paradigm for intelligent, highly specific cancer diagnostics in live-cell settings.

Soil C:N:P relationships are widely used indicators of nutrient balance, organic matter quality, and biogeochemical functioning in forest ecosystems. However, their organization across structural phases and soil horizons in undisturbed temperate forests remains insufficiently documented. This study examined vertical and structural-phase variation in soil C:N:P stoichiometry within an old-growth Fagus orientalis forest the Hyrcanian region. We quantified C:N, C:P, and N:P ratios in paired organic and mineral soil samples, with stoichiometric relationships interpreted based on total C and N and Olsen-extractable (plant-available) P, across the initial, optimal, and decay structural phases of this contiguous old-growth stand. Within this forest, C:N and C:P ratios showed phase-associated differences in the organic horizon, generally declining from the initial to the decay phase, whereas N:P remained comparatively stable. In the mineral horizon, phase-associated differences were also observed for C:N and C:P; however, the magnitude of variation was smaller, and patterns were less consistent than in the organic layer. Strong vertical contrasts were observed, with consistently higher C:N and C:P ratios in the organic layer and comparatively conservative N:P patterns across horizons. Overall, vertical differentiation between soil horizons represented a stronger axis of variation than structural-phase differentiation within this old-growth system. These findings provide a high-resolution stoichiometric characterization of a long-protected Hyrcanian beech forest and may serve as a baseline for future comparisons in similare temperate beech forest ecosystems under low-disturbance conditions.

Colorectal cancer (CRC) is one of the most common malignancies worldwide and is the second leading cause of cancer-related deaths. Currently, the main therapies for CRC include surgery, chemotherapy and radiotherapy. However, all of them have certain limitations, such as the tendency to trigger cancer recurrence and metastasis, and excessive damage to patients' bodies. To overcome some of these limitations, scholars have developed many nanoparticle-based therapies. This review discusses recent advances in the application of nanoparticles in CRC therapy, presenting the progress of inorganic, organic, inorganic-organic hybrid, and bioactive nanoparticles in the diagnosis and treatment of CRC. Finally, we also present our perspectives on the development of nanoparticles in CRC therapy.

It has long been recognised that, in the long term, hazardous acetonitrile (ACN) as a mobile-phase component and the environmentally critical trifluoroacetic acid (TFA) as an ion-pairing reagent should be replaced in high-performance liquid chromatography (HPLC). Nevertheless, methods relying on precisely these reagents are still widely used. Herein, we show that alternative approaches for the analysis of small molecule drugs are readily applicable, using examples from pharmaceutical quality control and medicinal chemistry. First, the principles of green analytical chemistry were implemented in an alternative HPLC method for the theophylline monohydrate monograph of the European Pharmacopoeia, without altering the core methodology. Among the various conditions tested, the use of 2% dimethyl carbonate (DMC) provided equivalent separation and an even slightly improved resolution compared with the original ACN-based pharmacopoeial method. In a second approach, we present a highly sustainable gradient HPLC method for routine purity analysis of synthesis products by replacing TFA with safe, biodegradable, and environmentally benign methanesulfonic acid (MSA). Furthermore, in the case of this gradient method, ACN could be replaced by the biodegradable and environmentally friendly DMC. An eluent composition consisting of 42 parts DMC, 23 parts EtOH, 35 parts H2O and 0.1 parts MSA was found to be equivalent to ACN containing 0.1% TFA. By employing a reproducible protocol using EtOH as a co-solvent, we were able to overcome current challenges associated with the use of organic carbonates in HPLC, which primarily arise from their limited miscibility with water. Given the continued widespread use of gradient HPLC methods employing ACN as an eluent and TFA as an acidic modifier, the methods presented herein offer significant potential to advance the implementation of sustainability in pharmaceutical quality control and medicinal chemistry.

The kelp Laminaria digitata uses iodide as a unique inorganic antioxidant to protect its surface and apoplastic space, with implications for atmospheric and marine chemistry as well as regional climatic processes. However, until now, significant open questions have remained regarding the cellular localization and processes involved. Here, using cutting-edge, synchrotron-based micro-X-ray fluorescence (µXRF) nanoprobe tomography with strontium (II) as a biomarker for algal cell walls, complemented by micro-X-ray absorption near-edge structure (μXANES) and scanning imaging, we unambiguously show that iodide is stored in intracellular vesicles of cortical cells. In contrast, bromide is mostly accumulated in the vacuoles of meristoderm cells. Upon oxidative stress, it is mobilized by a hitherto-uncharacterized anion transporter different from the well-known eukaryotic chloride channels. This study offers the first evidence of tissue localization for the formation of I2 or an organic iodine compound as a minor component in the cortical cell layer, as demonstrated using µXANES.

Dissolved sulfur dioxide (SO2), nitrogen oxides (NOx), and organic acids in precipitation can lower rainwater pH and affect ecosystems and infrastructure. Although precipitation acidity and acid rain frequency have declined in Shanghai in recent years, the factors driving this change remain insufficiently understood, especially in rapidly urbanizing coastal areas. In this study, precipitation samples were collected throughout 2024 in the Lingang New Area of Shanghai to investigate rainwater chemistry and the processes associated with reduced acidity. Major ions, dissolved organic carbon (DOC), and stable hydrogen and oxygen isotopes were analyzed, and enrichment factor (EF) analysis, together with positive matrix factorization (PMF), was applied to identify major sources and influencing processes. The volume-weighted mean pH was 5.65 (n = 52), and the acid rain frequency was 21.8%. Sulfate (SO₄2⁻) remained the dominant acidic ion, with a higher equivalent concentration than nitrate (NO3-). PMF results showed different dominant source associations for sulfate and nitrate: nitrate was mainly associated with secondary aerosols linked to anthropogenic NOₓ emissions, whereas sulfate was more strongly associated with a processed marine aerosol factor, especially during humid periods. At the same time, neutralization by Ca2+-rich dust and NH3-related inputs helped alleviate precipitation acidity. By combining source apportionment with isotope-based information on precipitation processes, this study provides new evidence that the reduction in precipitation acidity in the Lingang New Area during 2024 was jointly influenced by changes in anthropogenic emissions, coastal meteorological conditions, and neutralizing inputs.

Arsenic accumulation and biotransformation in fungi remain poorly understood, particularly in mushrooms. This study investigated arsenic distribution, speciation, and detoxification mechanisms in three mushroom species of the genus Hebeloma: H. bulbiferum, H. sinapizans, and H. mesophaeum. Wild collected fruit bodies and laboratory mycelial cultures were analysed using size-exclusion chromatography (SEC) and ion-pair reversed-phase ICP-MS to determine total arsenic concentrations and speciation patterns. H. bulbiferum exhibited the highest arsenic accumulation in fruit bodies (up to 563 mg kg⁻¹ dry mass), predominantly as dimethylarsenate, whereas H. sinapizans accumulated less total As (up to 41.2 mg kg⁻¹ dry mass), comprising mainly arsenobetaine and dimethylarsenate, and H. mesophaeum (up to 4.2 mg kg⁻¹ dry mass) was dominated by inorganic arsenic and arsenocholine. SEC revealed that arsenic was present as low-molecular-weight fractions, although a minor protein-associated peak was observed in H. sinapizans, suggesting a possible presence of an arsenic-binding protein. Mycelial cultures demonstrated species-specific tolerance to arsenate and the ability to transform inorganic arsenic into organic arsenicals, with varying degrees of arsenate reduction, arsenite efflux, and methylation. In particular, H. sinapizans and H. mesophaeum exhibited a higher degree of As(III) efflux than H. bulbiferum, indicating a more efficient As reduction and export. Notably, some organoarsenicals, dimethylarsenate and trimethylarsine oxide, were actively excreted into the growth medium, indicating a role for mushroom mycelia in environmental arsenic cycling. These findings highlight distinct arsenic detoxification strategies in Hebeloma species, reveal fungal de novo arsenobetaine synthesis, and provide insights into arsenic transformation and sequestration in ectomycorrhizal mushrooms.

Hydrogen peroxide (H2O2) is an essential chemical and potent energy carrier. Its production through solar energy and metal-free photocatalysts is desirable. Organic semiconductors, as a new generation of semiconductors, can form suitable transition state intermediates showing great ability in enhancing the efficiency and selectivity of photocatalytic H2O2 generation, offering a metal-free, green, and more economical solution. However, the smaller Frenkel exciton radius and larger exciton Coulomb binding energy lead to a constrained capacity for exciton dissociation, blocking the way of photocatalysts based on organic semiconductors. Here, we overcome the bottleneck by cocrystal engineering. A kind of cocrystal photocatalysts with X-packing are designed and synthesized, which permit all excited states to be optically allowed due to reduced energy splitting, enhancing the exciton participation in photosynthesis of H2O2 giving much more efficient singlet exciton dissociation and exciton utilization. Indeed, the X-packed cocrystals show photosynthesis of H2O2 from O2 and H2O at a rate of 2.65 mmol h-1 g-1 and a solar-chemical energy conversion efficiency of 0.42%, which can be further improved to 13.3 mmol h-1 g-1 with a hole sacrificial agent. This work seems to open a new door for high solar exciton utilization with organic semiconductors by cocrystal engineering.

The photocatalytic coupling of molecular oxygen with organic substrates, such as indoline represents a sustainable solar-to-chemical strategy. However, designing highly-efficient organic photocatalysts still remains a significant challenge. Herein, three Zn-Salen covalent organic frameworks (COFs, Zn-Salen-EN, -PD, and -HATP) with tunable donor-acceptor (D-A) nanodomains were synthesized through combining the same Zn-Salen acceptor units with different electron-donating linkers including ethylenediamine (EN), 1,2-phenylenediamine (PD), and 2,3,6,7,10,11-hexaaminotriphenylene (HATP). Among them, Zn-Salen-PD exhibits best activity for the two-electron photoreduction of O2 (2e- ORR) to produce hydrogen peroxide (H2O2) with a rate of 26 700 µmol gcat -1 h-1, while simultaneously enabling efficient photocatalytic indoline dehydrogenation to generate indole (2e- IND-DR). The enhanced performance of Zn-Salen-PD stems from its optimal D-A spatial alignment and a tailored band structure, which achieve a balanced synergy among exciton dissociation, charge carrier lifetime, and electron reduction capability. Moreover, mechanistic insights from in situ spectroscopy and theoretical calculations revealed that ZnN2O2 motifs served as efficient Griffith-type 2e- ORR active centers, while photoinduced holes accumulated on the donor units to drive 2e- IND-DR. This work demonstrates that the nanoscale engineering of D-A structures within metal-COFs offers a powerful strategy for enabling coupled photoredox transformations.