UiO-66/PIM-1 Mixed-Matrix Membrane for Hexane Isomer Separation.

The separation of high-octane dibranched alkanes from naphtha is critical in the refining of gasoline. To date, research on the membrane-based separation of alkane isomers has been limited, with a particular paucity of investigations into mixed-matrix membranes. Herein, the continuous and dense UiO-66/PIM-1 mixed-matrix membrane, which was prepared through precise control of the interfacial structure, was first applied to the differentiation of C6 alkane isomers. Due to the synergistic combination of UiO-66 with differential adsorption capabilities for alkanes and PIM-1 that possesses a cross-linkable structure, the resulting UiO-66/PIM-1-(20) membrane demonstrated remarkable separation performance and high stability. Pervaporation measurements showed that the mass fraction of 2,2-dimethylbutane in the feed side was increased from 50.0 to 75.8 wt % while an excellent flux of 1700 g m-2 h-1 was maintained over a continuous 40 h period. The UiO-66/PIM-1-(20) membrane, characterized by its facile replication and processing, shows potential for large-scale fabrication. This study offers a new approach to the membrane separation of alkane isomers.

Construction of Highly Accurate Machine Learning Potential Energy Surfaces for Excited-State Dynamics Simulations Based on Low-Level Data Sets.

Machine learning is capable of effectively predicting the potential energies of molecules in the presence of high-quality data sets. Its application in the construction of ground- and excited-state potential energy surfaces is attractive to accelerate nonadiabatic molecular dynamics simulations of photochemical reactions. Because of the huge computational cost of excited-state electronic structure calculations, the construction of a high-quality data set becomes a bottleneck. In the present work, we first built two data sets. One was obtained from surface hopping dynamics simulations at the semiempirical OM2/MRCI level. Another was extracted from the dynamics trajectories at the CASSCF level, which was reported previously. The ground- and excited-state potential energy surfaces of ethylene-bridged azobenzene at the CASSCF computational level were constructed based on the former low-level data set. Although non-neural network machine learning methods can achieve good or modest performance during the training process, only neural network models provide reliable predictions on the latter external test data set. The BPNN and SchNet combined with the Δ-ML scheme and the force term in the loss functions are recommended for dynamics simulations. Then, we performed excited-state dynamics simulations of the photoisomerization of ethylene-bridged azobenzene on machine learning potential energy surfaces. Compared with the lifetimes of the first excited state (S1) estimated at different computational levels, our results on the E isomer are in good agreement with the high-level estimation. However, the overestimation of the Z isomer is unimproved. It suggests that smaller errors during the training process do not necessarily translate to more accurate predictions on high-level potential energies or better performance on nonadiabatic dynamics simulations, at least in the present case.

Conversion of Propargylic Amines with CO2 Catalyzed by a Highly Stable Copper(I) Iodide Thorium-Based Heterometal-Organic Framework.

The conversion of CO2 to generate high-value-added chemicals has become one of the hot research topics in green synthesis. Thereinto, the cyclization reaction of propargylic amines with CO2 is highly attractive because the resultant oxazolidinones are widely found in pharmaceutical chemistry. Cu(I)-based metal-organic frameworks (MOFs) as catalysts exhibit promising application prospects for CO2 conversion. However, their practical application was greatly limited due to Cu(I) being liable to disproportionation or oxidization. Herein, the solid copper(I) iodide thorium-based porous framework {[Cu5I6Th6(µ3-O)4(µ3-OH)4(H2O)10(L)10]·OH·4DMF·H2O}n (1) (HL = 2-methylpyridine-4-carboxylic acid) constructed by [Th6] clusters and [CuxIy] subunits was successfully prepared and structurally characterized. To our knowledge, this is the first copper(I) iodide-based actinide organic framework. Catalytic investigations indicate that 1 can effectively catalyze the cyclization of propargylic amines with CO2 under ambient conditions, which can be reused at least five times without a remarkable decline of catalytic activity. Importantly, 1 exhibits excellent chemical stability and the oxidation state of Cu(I) in it can remain stable under various conditions. This work can provide a valuable strategy for the synthesis of stable Cu(I)-MOF materials.

Quantitative Assessment of Acute Intracranial Clot and Collaterals on High Resolution Magnetic Resonance Imaging.

INTRODUCTION: There has been an increasing demand for imaging methods that provide a comprehensive evaluation of intracranial clot and collateral circulation, which are helpful for clinical decision-making and predicting functional outcomes. We aimed to quantitatively evaluate acute intracranial clot burden and collaterals on high-resolution magnetic resonance imaging (HR-MRI). METHODS: We analyzed acute ischemic stroke patients with internal carotid artery or middle cerebral artery occlusion in a prospective multicenter study. The clot burden was scored on a scale of 0-10 based on the clot location on HR-MRI. The collateral score was assigned on a scale of 0-3 using the minimum intensity projection from HR-MRI. Uni- and multivariable logistic regression analyses were performed to assess their correlation with clinical outcome (modified Rankin Scale >2 at 90 days). Thresholds were defined to dichotomize into low and high score groups and predictive performances were assessed for clinical and radiologic outcomes. RESULTS: Ninety-nine patients (mean age of 60.77 ± 11.54 years) were included in the analysis. The interobserver correlation was 0.89 (95% CI: 0.77-0.95) for the clot burden score and 0.78 (95% CI: 0.53-0.90) for the collateral score. Multivariable logistic regression analysis demonstrated that the collateral score (odds ratio: 0.41, 95% CI: 0.19-0.90) was significantly associated with clinical outcomes. A better functional outcome was observed in the group with clot burden scores greater than 7 (p=0.011). A smaller final infarct size and a higher diffusion-weighted imaging-Alberta Stroke Program Early Computed Tomography Score were observed in the group with collateral scores greater than 1 (all p<0.05). CONCLUSIONS: HR-MRI offers a new tool for quantitative assessment of clot burden and collaterals simultaneously in future clinical practices and research endeavors.

Quantum Computation of Conical Intersections on a Programmable Superconducting Quantum Processor.

Conical intersections (CIs) are pivotal in many photochemical processes. Traditional quantum chemistry methods, such as the state-average multiconfigurational methods, face computational hurdles in solving the electronic Schrödinger equation within the active space on classical computers. While quantum computing offers a potential solution, its feasibility in studying CIs, particularly on real quantum hardware, remains largely unexplored. Here, we present the first successful realization of a hybrid quantum-classical state-average complete active space self-consistent field method based on the variational quantum eigensolver (VQE-SA-CASSCF) on a superconducting quantum processor. This approach is applied to investigate CIs in two prototypical systems─ethylene (C2H4) and triatomic hydrogen (H3). We illustrate that VQE-SA-CASSCF, coupled with ongoing hardware and algorithmic enhancements, can lead to a correct description of CIs on existing quantum devices. These results lay the groundwork for exploring the potential of quantum computing to study CIs in more complex systems in the future.

Nonadiabatic Molecular Dynamics in Momentum Space Beyond Harmonic Approximation: Hot Electron Relaxation in Photoexcited Black Phosphorus.

We simulated hot-electron relaxation in black phosphorus using the nonadiabatic molecular dynamics (NA-MD) approach with a non-Condon effect in momentum space beyond the harmonic approximation. By comparing simulations at the Γ point in a large supercell with those using a few k-points in a smaller supercell─while maintaining the same number of electronic states within the same energy range, we demonstrate that both setups yield remarkably consistent energy relaxation times, regardless of the initial state energy. This consistency arises from the complementary effects of supercell size in real space and the number of k-points in the reciprocal space. This finding confirms that simulations at a single k-point in large size supercells are an effective approximation for NA-MD with a non-Condon effect. This approach offers significant advantages for complex photophysics, such as intervalley scattering and indirect bandgap charge recombination, and is particularly suitable for large systems without the need for a harmonic approximation.

Elucidating Facet-Dependent Photocatalytic Activities of Metastable CdS and Au@CdS Core-Shell Nanocrystals.

Controlling the crystal facets of semiconductor nanocrystals (NCs) has been proven as an effective approach to tune their physicochemical properties. However, the study on facet-engineering of metastable zinc blende CdS (zb-CdS) and its heterostructures is still not fully explored. In this study, the zb-CdS and Au@zb-CdS core-shell NCs with tunable terminating facets are controllably synthesized, and their photocatalytic performance for water splitting are evaluated. It is found that the {111} facets of the zb-CdS NCs display higher intrinsic activity than the {100} counterparts, which originates from these surfaces being much more efficient, facilitating electron transition to enhance the adsorption ability and the dissociation of the adsorbed water, as revealed by theoretical calculations. Moreover, the Au@zb-CdS core-shell NCs exhibit better photocatalytic performance than the zb-CdS NCs terminated with the same facets under visible light irradiation (≥400 nm), which is mainly ascribed to the accelerated electron separation at the interface, as demonstrated by femtosecond transient absorption (fs-TA) spectroscopy. Importantly, the quantum yield of plasmon-induced hot electron transfer quantified by fs-TA in the Au@zb-CdS core-shell octahedrons can be reached as high as 1.2% under 615 nm excitation, which is higher than that of the Au@zb-CdS core-shell cubes. This work unravels the face-dependent photocatalytic performance of the metastable semiconductor NCs via a combination of experiments and theoretical calculations, providing the understanding of the underlying mechanism of these photocatalysts.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Rapid solar-driven atmospheric water-harvesting with MAF-4-derived nitrogen-doped nanoporous carbon.

Sorption-based atmospheric water-harvesting (AWH) could help to solve global freshwater scarcity. The search for adsorbents with high water-uptake capacity at low relative humidity, rapid adsorption-desorption kinetics and high thermal conductivity is a critical challenge in AWH. Herein, we report a MAF-4 (aka ZIF-8)-derived nanoporous carbon (NPCMAF-4-800) with multiple N-doped sites, considerable micropore characteristics and inherent photothermal properties, for efficient water production in a relatively arid climate. NPCMAF-4-800 exhibited optimal water-sorption performance of 306 mg g-1 at 40% relative humidity (RH). An excellent sunlight-absorption rate was realized (97%) attributed to its high degree of graphitization. A proof-of-concept device was designed and investigated for the practical harvesting of water from the atmosphere using natural sunlight. NPCMAF-4-800 achieved an unprecedentedly high water production rate of 380 mg g-1 h-1 at 40% RH, and could produce 1.77 L kg-1 freshwater during daylight hours in an outdoor low-humidity climate of ∼25 °C and 40% RH. These findings may shed light on the potential of MOF-derived porous carbons in the AWH field, and inspire the future development of solar-driven water-generation systems.

Unlocking the potential of phenolated kraft lignin as a versatile feed additive.

Lignin, a renewable natural antioxidant and bacteriostat, holds promise as a versatile, cost-effective feed additive. However, traditional industrial lignin faces limitations, including low reactivity, poor uniformity, and unstable properties, necessitating chemical modification. Complex modification methods pose economic and toxicity challenges, so this study adopted a relatively simple alkali-catalyzed phenolization approach, using phenol, catechol, and pyrogallol to modify kraft lignin, and characterized the resulting products using various techniques. Subsequently, their antioxidant, antibacterial, adsorption properties for heavy metal ions and mycotoxins, growth-promoting properties, and antiviral abilities were assessed. The phenolation process led to lignin depolymerization and a notable increase in phenolic hydroxyl content, particularly in pyrogallol-phenolated lignin (Py-L), rising from 3.08 to 4.68 mmol/g. These modified lignins exhibited enhanced antioxidant activity, with over 99 % inhibition against E. coli and S. aureus, and remarkable adsorption capacities for heavy metal ions and mycotoxins. Importantly, Py-L improved the growth performance of mice and reduced influenza mortality. Furthermore, density functional theory calculations elucidated the mechanism behind the enhanced antioxidant properties. This study presents a promising avenue for developing versatile feed additives to address challenges related to animal feed antioxidant supplementation, bacterial control, and growth promotion.

Multi-fidelity machine learning for predicting bandgaps of nonlinear optical crystals.

Nonlinear optical (NLO) materials are of great importance in modern optics and industry because of their intrinsic capability of wavelength conversion. Bandgap is a key property of NLO crystals. In recent years, machine learning (ML) has become a powerful tool to predict the bandgaps of compounds before synthesis. However, the shortage of available experimental data of NLO crystals poses a significant challenge for the exploration of new NLO materials using ML. In this work, we proposed a new multi-fidelity ML approach based on the multilevel descriptors developed by us (Z.-Y. Zhang, X. Liu, L. Shen, L. Chen and W.-H. Fang, J. Phys. Chem. C, 2021, 125, 25175-25188) and the gradient boosting regression tree algorithm. The calculated and experimental bandgaps of NLO crystals were collected as the low- and high-fidelity labels, respectively. The experimental values were predicted based on chemical compositions of crystals without prior knowledge about crystal structures. The multi-fidelity ML model overcame the performance of single-fidelity predictor. Furthermore, it was observed that less accurate predictions on the low-fidelity label may result in more accurate prediction on the high-fidelity label, at least in the present case. Using the multi-fidelity ML model with the best performance in this work, the mean absolute error on the test set of experimental bandgaps was 0.293 eV, which is smaller than that using the single-fidelity model (0.355 eV). It is far from perfect but accurate enough as an effective computational tool in the first step to discover novel NLO materials.

Compression of Organic Molecules Coupled with Hydrogen Bonding Extends the Charge Carrier Lifetime in BA2SnI4.

Two-dimensional (2D) metal halide perovskites, such as BA2SnI4 (BA═CH3(CH2)3NH3), exhibit an enhanced charge carrier lifetime in experiments under strain. Experiments suggest that significant compression of the BA molecule, rather than of the inorganic lattice, contributes to this enhancement. To elucidate the underlying physical mechanism, we apply a moderate compressive strain to the entire system and subsequently introduce significant compression to the BA molecules. We then perform ab initio nonadiabatic molecular dynamics simulations of nonradiative electron-hole recombination. We observe that the overall lattice compression reduces atomic motions and decreases nonadiabatic coupling, thereby delaying electron-hole recombination. Additionally, compression of the BA molecules enhances hydrogen bonding between the BA molecules and iodine atoms, which lengthens the Sn-I bonds, distorts the [SnI6]4- octahedra, and suppresses atomic motions further, thus reducing nonadiabatic coupling. Also, the elongated Sn-I bonds and weakened antibonding interactions increase the band gap. Altogether, the compression delays the nonradiative electron-hole recombination by more than a factor of 3. Our simulations provide new and valuable physical insights into how compressive strain, accommodated primarily by the organic ligands, positively influences the optoelectronic properties of 2D layered halide perovskites, offering a promising pathway for further performance improvements.

HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos.

We conducted a large-scale study of human perceptual quality judgments of High Dynamic Range (HDR) and Standard Dynamic Range (SDR) videos subjected to scaling and compression levels and viewed on three different display devices. While conventional expectations are that HDR quality is better than SDR quality, we have found subject preference of HDR versus SDR depends heavily on the display device, as well as on resolution scaling and bitrate. To study this question, we collected more than 23,000 quality ratings from 67 volunteers who watched 356 videos on OLED, QLED, and LCD televisions, and among many other findings, observed that HDR videos were often rated as lower quality than SDR videos at lower bitrates, particularly when viewed on LCD and QLED displays. Since it is of interest to be able to measure the quality of videos under these scenarios, e.g. to inform decisions regarding scaling, compression, and SDR vs HDR, we tested several well-known full-reference and no-reference video quality models on the new database. Towards advancing progress on this problem, we also developed a novel no-reference model called HDRPatchMAX, that uses a contrast-based analysis of classical and bit-depth features to predict quality more accurately than existing metrics.

Phenotypic and Genomic Characterization of Pseudomonas wuhanensis sp. nov., a Novel Species with Promising Features as a Potential Plant Growth-Promoting and Biocontrol Agent.

Plant growth-promoting rhizobacterial strain FP607T was isolated from the rhizosphere of beets in Wuhan, China. Strain FP607T exhibited significant antagonism toward several phytopathogenic bacteria, indicating that FP607T may produce antimicrobial metabolites and has a stronger biocontrol efficacy against plant pathogens. Growth-promoting tests showed that FP607T produced indole-3-acetic acid (IAA), NH3, and ferritin. The genome sequence of strain FP607T was 6,590,972 bp long with 59.0% G + C content. The optimum temperature range was 25-30 °C, and the optimum pH was 7. The cells of strain FP607T were Gram-negative, short, and rod-shaped, with polar flagella. The colonies on the King's B (KB) agar plates were light yellow, smooth, and circular, with regular edges. A phylogenetic analysis of the 16S rRNA sequence and a multilocus sequence analysis (MLSA) showed that strain FP607T was most closely related to the type of strain Pseudomonas farris SWRI79T. Based on a polyphasic taxonomic approach, strain FP607T was identified as a novel species within the genus Pseudomonas, for which the name Pseudomonas wuhanensis sp. nov. was proposed. The type of strain used was FP607T (JCM 35688, CGMCC 27743, and ACCC 62446).

MicroRNAs as Key Regulators in RA and SLE: Insights into Biological Functions.

MicroRNAs (miRNAs) are non-coding RNA molecules that bind to mRNAs to regulate gene expression. Since changes in miRNA expression levels have been found in a variety of autoimmune illnesses, miRNAs are important in autoimmune diseases. MiRNAs serve not only as pathogenic factors and biomarkers for autoimmune diseases but also as important targets for disease therapeutics. Although miRNA-based treatments are still in the research stage, in-depth investigations into the biological functions of miRNAs have significantly enhanced our understanding of their mechanisms in autoimmune diseases. The purpose of this review is to summarize the biological functions of miRNAs, their roles in rheumatoid arthritis and systemic lupus erythematosus, therapeutic strategies, and challenges.

Metabolic Regulation-Mediated Reversion of the Tumor Immunosuppressive Microenvironment for Potentiating Cooperative Metabolic Therapy and Immunotherapy.

Tumor cells exhibit heightened glucose (Glu) consumption and increased lactic acid (LA) production, resulting in the formation of an immunosuppressive tumor microenvironment (TME) that facilitates malignant proliferation and metastasis. In this study, we meticulously engineer an antitumor nanoplatform, denoted as ZLGCR, by incorporating glucose oxidase, LA oxidase, and CpG oligodeoxynucleotide into zeolitic imidazolate framework-8 that is camouflaged with a red blood cell membrane. Significantly, ZLGCR-mediated consumption of Glu and LA not only amplifies the effectiveness of metabolic therapy but also reverses the immunosuppressive TME, thereby enhancing the therapeutic outcomes of CpG-mediated antitumor immunotherapy. It is particularly important that the synergistic effect of metabolic therapy and immunotherapy is further augmented when combined with immune checkpoint blockade therapy. Consequently, this engineered antitumor nanoplatform will achieve a cooperative tumor-suppressive outcome through the modulation of metabolism and immune responses within the TME.

Measuring resilience for Chinese-speaking populations: a systematic review of Chinese resilience scales.

Introduction: Despite the rapid growth of interdisciplinary resilience research in Chinese contexts, no study has systematically reviewed individual-level measurement scales for Chinese-speaking populations. We report a systematic review of scales developed for or translated/adapted to Chinese-speaking contexts, where we assessed how widely used scales fare in terms of their psychometric qualities. Methods: Studies included in this review must have been published in peer-reviewed English or Chinese journals between 2015-2020 and included self-reported resilience scales in Chinese-speaking populations. Searches were conducted in PsycINFO, CNKI (completed in May 2021), and PubMed (completed in January 2024). We developed coding schemes for extracting relevant data and adapted and applied an existing evaluation framework to assess the most frequently used resilience scales by seven methodological criteria. Results: Analyses of 963 qualified studies suggested that Chinese resilience scales were used in a diverse range of study contexts. Among 85 unique kinds of resilience measures, we highlighted and evaluated the three most frequently used translated scales and three locally developed scales (nine scales in total including variations such as short forms). In short, resilience studies in Chinese contexts relied heavily on the translated 25-item Connor-Davidson Resilience Scale, which scored moderately on the overall quality. The locally developed Resilience Scale for Chinese Adolescents and Essential Resilience Scale received the best ratings but could use further development. Discussion: We discussed how future work may advance widely used scales, and specified seven methodological recommendations for future resilience scale development with existing and new scales in and beyond the Chinese study contexts. We further addressed issues and challenges in measuring resilience as a process and called on researchers to further develop/evaluate process measures for Chinese-speaking populations.

Topological wetting states of microdroplets on closed-loop structured surfaces: Breakdown of the Gibbs equation at the microscale.

Microdroplets are a class of soft matter that has been extensively employed for chemical, biochemical, and industrial applications. However, fabricating microdroplets with largely controllable contact-area shape and apparent contact angle, a key prerequisite for their applications, is still a challenge. Here, by engineering a type of surface with homocentric closed-loop microwalls/microchannels, we can achieve facile size, shape, and contact-angle tunability of microdroplets on the textured surfaces by design. More importantly, this class of surface topologies (with universal genus value = 1) allows us to reveal that the conventional Gibbs equation (widely used for assessing the edge effect on the apparent contact angle of macrodroplets) seems no longer applicable for water microdroplets or nanodroplets (evidenced by independent molecular dynamics simulations). Notably, for the flat surface with the intrinsic contact angle ~0°, we find that the critical contact angle on the microtextured counterparts (at edge angle 90°) can be as large as >130°, rather than 90° according to the Gibbs equation. Experiments show that the breakdown of the Gibbs equation occurs for microdroplets of different types of liquids including alcohol and hydrocarbon oils. Overall, the microtextured surface design and topological wetting states not only offer opportunities for diverse applications of microdroplets such as controllable chemical reactions and low-cost circuit fabrications but also provide testbeds for advancing the fundamental surface science of wetting beyond the Gibbs equation.

Correlation Between Anesthesia Methods and Adverse Short-Term Postoperative Outcomes Depending on Frailty: A Prospective Cohort Study.

Purpose: This study aims to investigate how the type of anesthesia used during major orthopedic surgery may impact adverse short-term postoperative outcomes depending on frailty. Methods: To conduct this investigation, we recruited individuals aged 65 years and older who underwent major orthopedic surgery between March 2022 and April 2023 at a single institution. We utilized the FRAIL scale to evaluate frailty. The primary focus was on occurrences of death or the inability to walk 60 days after the surgery. Secondary measures included death within 60 days; inability to walk without human assistance at 60 days; death or the inability to walk without human assistance at 30 days after surgery, the first time out of bed after surgery, postoperative blood transfusion, length of hospital stay, hospital costs, and the occurrence of surgical complications such as dislocation, periprosthetic fracture, infection, reoperation, wound complications/hematoma. Results: In a study of 387 old adult patients who had undergone major orthopedic surgery, 41.3% were found to be in a frail state. Among these patients, 262 had general anesthesia and 125 had neuraxial anesthesia. Multifactorial logistic regression analyses showed that anesthesia type was not linked to complications. Instead, frailty (OR 4.04, 95% CI 1.04 to 8.57, P< 0.001), age (OR 1.05, 95% CI 1.00-1.10, P= 0.017), and aCCI scores, age-adjusted Charlson Comorbidity Index, (OR 1.36, 95% CI 1.12 to 1.66, P= 0.002) were identified as independent risk factors for death or new walking disorders in these patients 60 days after surgery. After adjusting for frailty, anesthesia methods was not associated with the development of death or new walking disorders in these patients (P > 0.05). Conclusion: In different frail populations, neuraxial anesthesia is likely to be comparable to general anesthesia in terms of the incidence of short-term postoperative adverse outcomes.

Photoinduced Dynamics of a Single-Walled Carbon Nanotube with a sp3 Defect: The Importance of Excitonic Effects.

Herein, we employed linear-response time-dependent functional theory nonadiabatic dynamic simulations to explore the photoinduced exciton dynamics of a chiral single-walled carbon nanotube CNT(6,5) covalently doped with a 4-nitrobenzyl group (CNT65-NO2). The results indicate that the introduction of a sp3 defect leads to the splitting of the degenerate VBM/VBM-1 and CBM/CBM+1 states. Both the VBM upshift and the CBM downshift are responsible for the experimentally observed redshifted E11* trapping state. The simulations reveal that the photoinduced exciton relaxation dynamics completes within 500 fs, which is consistent with the experimental work. On the other hand, we also conducted the nonadiabatic carrier (electron and hole) dynamic simulations, which completely ignore the excitonic effects. The comparison demonstrates that excitonic effects are indispensable. Deep analyses show that such effects induce several dark states, which play an important role in regulating the photoinduced dynamics of CNT65-NO2. The present work demonstrates the importance of including excitonic effects in simulating photoinduced processes of carbon nanotubes. In addition, it not only rationalizes previous experiments but also provides valuable insights that will help in the future rational design of novel covalently doped carbon nanotubes with superior photoluminescent properties.