Although optical properties play a critical role in photocatalysis, numerical studies of how nano-morphologies influence them remain scarce. Here, a combined experimental-computational approach was employed to compare how nano-morphologies of TiO2 nanotube arrays (TiNAs) and colloidal TiO2 nanoparticles (TiNPs) influence their optical properties. Morphologies were characterized by SEM and TEM, optical properties were measured by UV-vis spectroscopy, and absorption and scattering spectra alongside electric field distributions were simulated. SEM and TEM reveal that TiNAs are vertically aligned, open-ended nanotubes (diameter 25-115 nm, length 800-3700 nm), whereas TiNPs form rough-surfaced spherical agglomerates (30-50 nm) of 5 nm quantum dots. For TiNAs, the absorbance in both experimental and simulated UV-vis spectra increase with nanotube diameter and length but decline with increasing inter-tube spacing. TiNPs exhibit pronounced UV scattering that intensifies with wavelength; both absorption and scattering intensities increase monotonically with nanoparticle size. Electric field simulations reveal local electric field enhancement in both TiNAs and TiNPs via light scattering. Owing to their distinct nano-morphologies and optical properties, TiNAs and TiNPs can be synergistically integrated to broaden spectral utilization and enhance photocatalytic efficiency. This work elucidates how TiO2 nano-morphologies influence its optical properties, providing guidelines for studying morphology-optical property relationships of other photocatalysts.

In this study, an in-depth exploration of filled paper was conducted to understand its structural and permeability characteristics. Cotton linter pulp and precipitated calcium carbonate (PCC) filler were utilized to prepare pure fiber paper, and PCC1 and PCC2 filled papers with different filler particle sizes. Then, the pore structure parameters of paper samples were characterized by mercury intrusion porosimetry, and the X-ray computed tomography (X-CT) scanning was carried out. Subsequently, the 3D microstructures were established based on the X-CT slice images, and the filler characteristic parameters and filler 3D distribution were quantitatively analyzed. Finally, permeation simulations in the thickness and horizontal directions were performed. The findings indicate that filling changes the paper porosity, and the pore tortuosity varies with direction. The estimated pore-throat radius distribution shows specific patterns for different papers. The fillers have different distribution characteristics in the paper samples. Moreover, the paper permeability differs with direction, with small-sized filler having a significant impact on fluid penetration in the thickness direction. Overall, this study provides an effective method for investigating internal paper filler and its distribution, which contributes to the understanding of paper structure-performance relationships. Application: This research offers an effective exploratory approach for investigating paper fillers from the perspective of computer simulation, facilitating the structural design and performance optimization of paper-based functional materials.

This study investigates a lab-scale biochemical treatment system for papermaking wastewater to accurately quantify Greenhouse Gas (GHG) emissions. An interpretable data-driven modeling framework was developed by integrating deep learning, SHapley Additive exPlanations (SHAP), and Generalized Additive Model (GAM). Key factors were selected based on the mechanisms of GHG formation in wastewater treatment, with redundant features eliminated through Spearman correlation and Variance Inflation Factor (VIF) analyses. With the refined inputs and GHG indicators, Convolutional Neural Network (CNN), Long Short-Term Memory Network (LSTM), Bidirectional LSTM (BiLSTM), CNN-LSTM, and CNN-BiLSTM were constructed and evaluated using both training and test datasets. Among them, the CNN-BiLSTM hybrid model demonstrated the highest prediction accuracy. SHAP analysis based on the CNN-BiLSTM model was then applied to identify key factors influencing GHG emissions. GAM was then used to establish functional relationships between factor values and SHAP values, revealing the process conditions for reducing GHG emissions. The interpretable modeling approach developed in this study, can not only accurately quantify direct GHG emissions but also provide a technical basis for further emission reduction. This approach offers both an effective tool for GHG emissions quantification and valuable insights for GHG emissions control during the papermaking wastewater biochemical treatment stage.

Developing a portable, real-time, and efficient sensor for formaldehyde (HCHO) detection remains a challenge in environmental health applications. In this work, a flower-like hierarchical ZnCo2O4/In2O3 heterojunction composite was fabricated via hydrothermal and calcination methods. The incorporation of ZnCo2O4 reduced the operating temperature of the In2O3 sensor from 300 degrees C to 258 degrees C and enhanced its gas-sensing performance towards HCHO, including selectivity and gas response. Notably, the 3 mol% ZnCo2O4/In2O3 sensor exhibited the best gas-sensing performance for HCHO, demonstrating a response value of 107.2 toward 100 ppm HCHO-a 16-fold enhancement compared to In2O3 sensor. The developed device also achieved rapid response/recovery kinetics (51/52 s), excellent humidity tolerance, a low detection threshold of 63 ppb, and remarkable long-term stability for up to 50 days. Furthermore, the enhanced HCHO sensing capability observed in the 3 mol% ZnCo2O4/In2O3 composite primarily stems from the creation of p-n heterostructures between ZnCo2O4 and In2O3, high specific surface area, and optimizing electron transport dynamics. By utilizing the developed ZnCo2O4/In2O3 based sensor, a wireless HCHO detection system was successfully designed, demonstrating the significant potential of our strategy in practical sensor applications.

Hydrogen sulfide (H2S) gas poses significant health hazards even at low concentrations, underscoring the need for H2S sensors. The varied sensitivity of CuO to H2S is considerable in existing studies, yet the underlying response mechanism remains underexplored. To investigate the factors influencing the gas-sensing performance for CuO to H2S, CuOs synthesized by five methods possess a gradient changed sensing performance. The properties of CuOs were characterized through the analysis methods of XRD, XPS, BET, TPD-CO2, TPD-NH3 and SEM. Moreover, assisted by the DFT simulation, the gas-sensing mechanism were revealed from the insights of oxygen vacancy and surface chemistry. The important findings are as follows. (1) There are no direct correlations between the specific surface area and the quantity of acidic or basic active sites of CuO. (2) The excellent selectivity of CuO to H2S relies on the strong adsorption energy of H2S, and oxygen vacancy and adsorption jointly determine the response value. (3) The gas sensing process of CuO to H2S leads to the productions of Cu-S bonds, and the final products of SO2 and Cu-SO4. These investigation results provide constructive suggestions for the development of high-performance metal oxide sensors.

An improved Mass–Spring Model (iMSM) is developed by adding central springs to the conventional Mass–Spring Models (MSMs) of tubular structures. This improvement is necessary to model fibers that have enough stiffness so that they do not collapse under transverse loading. Such is the case with many pulp fibers used in papermaking. Four different types of pulp fibers (Aspen CTMP, Aspen BCTMP, Birch BCTMP, and Spruce BKP) were simulated in the study. A geometric model and iMSM of a single fiber were developed, in which the topological structure of iMSM is explained in detail. The mass of mass points and the elastic coefficient of different springs in iMSM were calculated using axial tensile and torsional responses. A dynamic simulation of transverse bending of the fiber over a rigid cylinder and subjected to a transverse pressure was used to determine the effective elastic modulus for four different single fibers and compared to experimental values with an average relative error of 8.49%. The dynamic simulations were completed in 1.04–2.64 min for the four different paper fibers representing sufficient speeds to meet the needs of most real application scenarios. The acceptable accuracy and the fast simulation speed with the developed iMSM fiber model demonstrate the feasibility of the methodology in analyzing paper structures as well as similar fiber-based materials.

As a byproduct of the chemical pulping process, black liquor presents substantial potential as a renewable energy resource. Due to the low efficiency and high emissions of conventional direct combustion methods, some innovative black liquor combustion technologies have been proposed. To investigate the comprehensive environmental impacts of black liquor combustion technologies, four black liquor combustion scenarios were compared, direct combustion (S1), gasification (S2), supercritical water gasification (S3), and supercritical water liquefaction (S4), with further integrated technical, environmental, and economic analyses conducted. Using Aspen Plus simulations, the energy outputs and operational efficiency of S1-S4 are assessed. OpenLCA software is employed to quantify their environmental impacts across multiple categories, and their economic viability is evaluated through life cycle cost analysis. The study results indicate that S4 offers the highest thermal efficiency and energy output, but with significant environmental impacts. S2 is the most environmentally sustainable due to relatively low emissions. Meanwhile, S1 is economically viable for small-scale operations. Finally, S3 presents the robust economic potential with balanced performance. This research provides meaningful insights for promoting sustainable biomass energy production and guiding policy in the pulp and paper industry.

Two-dimensional (2D) MXene provides large surface area for the adsorption and interaction of H2O molecules, which is highly desirable for the construction of humidity-sensing materials. However, the drawbacks, involving easy stacking and poor mechanical strength, pose a huge challenge to its practical application. Herein, inspired by nacred "brick-mortar" nanostructure, a nanopaper humidity sensor made of flexible TEMPO-oxidated cellulose nanofibers/MXene/silver nanowires (TOCNFs/MXene/AgNWs) was developed by vacuum-assisted filtration self-assembly strategy. The synergism of 1D TOCNFs, AgNWs "mortar" and 2D MXene "bricks" endows the nanopaper with superb tensile strength (146.3 MPa), modulus (16.9 GPa), and superior bending durability, and the obtained TOCNFs/MXene/AgNWs nanopaper humidity sensor exhibits high response value of 90% at 97% RH with a low MXene addition of 20 wt%. Furthermore, the unique photothermal response property of MXene accelerates the desorption of H2O molecules during sensor recovery, realizing the reversible sensing performance. The proposed humidity sensing mechanism lies in the variation of MXene interlayer d-spacing induced by adsorbing ambient H2O molecules and the swelling of TOCNFs. Lastly, the sensor demonstrates the possibilities in human respiration monitoring, non-contact sensing, and humidity actuating.

Humidity sensors are of great significance in the domains of wearable electronic products, environmental and food quality monitoring, and human healthcare. In general, they necessitate an external power source in the form of a battery. Despite considerable efforts, developing self-powered sensing systems without reliance on an external power supply remains a major challenge. Herein, an electrochemical humidity sensor with primary battery structure based on redox reaction was designed, in which polydopamine (PDA)-modified MXene/TEMPO-oxidized cellulose nanofibers/LiCl (PDMM/TOCNFs/LiCl) composite film serves as electrolyte layer. The introduction of TOCNFs confers outstanding structural stability and superior tensile strength upon the composite film. Importantly, the hygroscopic and ionic conductivity properties of the PDMM/TOCNFs/LiCl electrolyte allow the sensor to generate spontaneous voltage over a wide relative humidity (RH) range of 11 – 91%. In addition, the developed sensor exhibits excellent humidity-sensing performances, including high voltage response, fast response/recovery time, and superior humidity-sensing stability. Moreover, mussel-inspired PDA improves the ambient stability of MXene by engineering interfacial interactions, which imparts the hygroscopic PDMM/TOCNFs/LiCl composite film with desirable stability for practical applications. Finally, the potential applications of the sensor and the composite film in human respiration, non-contact sensing, and humidity actuating are demonstrated. This work paves the way for the development of an innovative self-powered humidity sensing system.

Wastewater treatment plants (WWTPs) have been regarded as the main sources of greenhouse gas (GHG) emissions. This study compares the influent characteristics of industrial wastewater represented by the WWTP of paper mill and that of domestic sewage represented by the Benchmark Simulation Model No. 1 (BSM1) under stormy weather. The various sources of GHG emissions from the two processes are calculated, and the contribution of each source to the total GHG emissions is assessed. Firstly, based on the mass balance analysis and the recognized emission factors, a GHG emission calculation model was established for the on-site and off-site GHG emission sources from the WWTP of paper mill. Simultaneously, a GHG emission experimental model was established by determining the dissolved concentrations of carbon dioxide (CO2) and nitrous oxide (N2O) in the papermaking wastewater, to verify the accuracy of the developed GHG calculation model. Subsequently, an optimum aeration rate for the paper mill was investigated to comply with the discharging norms. Under the optimum aeration rate of 10 h-1, the obtained calculation accuracies of CO2 and N2O emissions were 94.6 % and 91.1 %, respectively. The mean total GHG emission in the WWTP of paper mill was 550 kg CO2-eq·h-1, of which 44.6 % came from the on-site emission sources and 55.4 % from the off-site emission sources. It was also uncovered that the electrical consumption for aeration was the largest contributor to the total GHG emissions with a proportion of 25.2 %, revealing that the control strategy of the aeration rate is highly significant in reducing GHG emissions in WWTP of paper mills.

Flexible and easy fabrication gas sensors can be utilized in various applications. In this study, we have proposed and prepared zinc oxide (ZnO) nanorods and reduced grapheme oxide (rGO) nanocomposite materials, fully printed on highly transparent paper substrates, and thoroughly investigated and optimized the performance of these gas sensors to ethanol at room temperature (25 °C). Among them, the average length of the ZnO nanorods is 200 nm and the diameter is 30 nm, integrated with rGO, the two-dimensional ZnO/rGO nanocomposites were obtained. The ratios of ZnO and rGO in the materials were controlled, ZnO/rGO nanocomposites ink was prepared, and thin films were coated on paper substrate to acquire transparent flexible paper gas sensors. Furthermore, the fabricated ZnO/rGO paper-based gas sensors achieved ppb grade detection of ethanol at room temperature (25 °C) with high performance (favorable selectivity, high gas sensitivity, good stability, and rapid response/recovery time). Specially, the proposed paper-based gas sensors are not only transparent but are also better in breathability, biocompatibility, and biodegradability, which have great application prospects in handheld or wearable electronic devices for the detection of trace ethanol at room temperature.

389 Background: Urinary and seminal cell-free DNA (cfDNA) have been recognized as promising biomarkers of prostate cancer. DNA methylation signal in tumor is increasingly used as tumor diagnosis and longitudinal monitoring indicator. However, the clinical utility of cfDNA from expressed prostatic secretions (EPS) remains unknown. Methods: The prospective study includes 50 prostate cancer (PC) patients and equivalent benign prostatic hyperplasia (BPH) patients, where EPS samples were collected after the prostatic massage of each patient. Cell-free DNA from EPS was extracted and treated by PredicineEPIC, a liquid biopsy comprehensive DNA methylation assay. The study developed integrated bioinformatic algorithms to profile the genome-wide epigenomic characteristics and investigate tumor-specific methylation patterns. Results: The initial exploratory cohort included 5 PC and 11 BPH cases. PredicineEPIC whole-genome DNA methylation of EPS identified over 300 differentially methylated regions (DMRs). Prostate cancers were distinguished from the BPH group by an unsupervised clustering method, suggesting that the identified DMRs embody the specific profiles of malignant tumors. Additionally, this study detected genome-wide copy number variation burden (CNB) in parallel. A risk model was built for cancer risk assessment based on methylation and CNB characteristics. Conclusions: This study demonstrated the feasibility of methylation profiling of cfDNA in EPS in prostate cancer. This non-invasive liquid biopsy approach could sensitively navigate prostate cancer from benign prostatic hyperplasia, suggesting future direction of methylation-based liquid biopsy in detecting prostate cancer.

Because of its biodegradability, biocompatibility, strong hydrophilicity, and high specific surface area, nanocellulose has been considered as a potential material for flexible humidity sensors. Herein, we developed a TiO2/CNC humidity sensor with good flexibility based on the nanocellulose (CNC) prepared by the enzymatic method. Nano TiO2 with a positive charge was adsorbed on the surface of CNC with a negative charge, and conductive fibers were obtained by an electrostatic self-assembly process. The TiO2/CNC composite exhibits high optical transmittance (84.5% at 600 nm), flexibility (the tensile elongation reaches 57.82%), and robust mechanical property (the tensile strength reaches 44.66 MPa). The obtained TiO2/CNC humidity sensor achieved high humidity response (R0/R = 450.9), rapid response/recovery speed (22/13 s), folding durability (20 times), and long-term stability (40 days). TiO2/CNC had outstanding performance in actual respiratory rate detection, and the assembled TiO2/CNC skin moisture detector with flexibility and transparency could monitor human body moisture in real-time, showing its potential as a smart wearable device.

In the study, for an existing paper mill, to realize the fault diagnosis and further fault signal reconstruction for the papermaking SBR wastewater treatment process, a novel model-based SBR-EKF (Extended Kalman Filter) fault diagnosis model has been proposed. Combining the SBR process model and EKF method, using the field 120 sets of normal data of dissolved oxygen (DO) and level (L) from a paper mill, the model-based SBR-EKF fault diagnosis model for the papermaking SBR wastewater treatment process was established, and the weighted sum of squared residuals thresholds (WSSR0) was determined off-line. Subsequently, based on the normal data, four common types of faults, fixed bias, drift bias, total failure, and precision degradation, were generated and applied to the developed SBR-EKF model for on-line monitoring. The fault diagnostic results show that, by comparing the calculated WSSR with the obtained WSSR0, the developed model-based SBR-EKF model demonstrated acceptable fault detection rates for DO and L. Moreover, using the filtered value of the SBR-EKF model, the effective signal reconstructions for L and DO were realized. These investigation results reveal the effectiveness of the proposed SBR-EKF fault diagnosis model, achieving fault diagnosis with acceptable precision and reconstructed signal.

Using cotton pulp fibers as raw material, through composite enzymolysis and purification, two different forms of high-purity cellulose nanocrystals were obtained, namely spherical CNCs (SCNCs) and rod-like CNCs (RCNCs). Vacuum filtration was used to obtain pure SCNCs film and pure RCNCs film. The films were characterized by scanning electron microscopy, ultraviolet–visible spectrometry, and X-ray diffraction and tested for their mechanical properties. The films were shown to have good light transmittance and softness, and the structures were unchanged compared with the cellulose raw materials. This article mainly introduces the preparation process of high-purity cellulose nanocrystals films and provides data support for subsequent research.

The microscopic porous structure of paper directly affects its properties.In this study, cotton, hardwood, and softwood pulps were used as raw materials and capillary flow porometer was employed to explore the effects of fiber materials, beating degree, and basis weight on porous structure and permeability of paper.The results showed that with the increase in beating degree and basis weight, the pore size of paper decreased gradually for all fiber materials; the distribution range and peak value of pore size shifted to smaller-size range and permeability also decreased.Compared with the influencing factor of basis weight, beating operation had a greater impact on the size and distribution of paper pore diameter, which further affected the permeability of paper.These results are beneficial to controlling the structure of paper and promoting the design and development of porous paper-based materials.

Understanding the pore structure of paper and its permeability behavior is important for designing paper-based materials. In this study, the three-dimensional structure of paper was investigated using X-ray computed tomography, and the representative elementary volume (REV) was determined to be 400 × 400 × 450 pixels by the porosity criterion. The pore structural parameters of the REV were experimentally validated. Permeability simulations were carried out in the thickness direction (perpendicular to the paper plane, denoted as the Z direction), horizontal direction (any direction of the paper plane, denoted as the X–Y plane), double outlet, and triple outlet conditions. The simulated permeability in the thickness direction (1.69 µm 2 ) was very close to the experimental value (1.88 µm 2 ). The calculated permeability in the horizontal direction (8.38 µm 2 ) was much greater than that in the thickness direction, revealing that the paper had a high pore connectivity and large pore size in the horizontal direction, giving it a high permeability. Compared with the single outlet case, in the case of the double and triple outlet boundary conditions, more fluid flowed out from the side outlets, and the internal pressure declined faster. This study provides an approach for the structural design and performance optimization of paper-based materials.

本研究以X射线断层扫描(CT)为测试手段,结合数字图像处理技术,建立了表征纸张孔隙结构和表面形貌的方法,研究了涂布对纸张三维结构的影响,从结构角度阐释了涂布影响纸张性能的内在机理.结果表明,涂布后纸张的孔隙率、孔径和配位数减小,孔隙迂曲率升高,使得流体流经孔隙时的阻力增大从而增加其阻隔性;另外,涂布还改变了纸张的表面微观形貌,使纸张表面轮廓均方根偏差降低,减小纸张表面起伏,提高纸张平滑度.基于X射线CT技术对涂布纸张进行三维结构表征有助于明晰纸基材料结构与性能之间的关系,推动新型纸基材料的研发.