Abstract Subgrade plain soil filling is a crucial process in road construction prone to particulate matter (PM) emissions. In this study, we conducted a key factor analysis and concentration prediction of PM emissions in a subgrade plain soil filling process based on interpretable machine learning algorithms. Real-time monitoring of particulate pollutant emissions, using a drone and distributed ground-fixed sensors, was conducted to collect data on a new national highway project using spatiotemporal Internet of Things technology. The interpretable machine learning models were developed using Bayesian optimization to predict PM 10 and PM 2.5 concentrations. The results revealed that extreme gradient boosting exhibited the highest predictive performance. Additionally, Shapley additive explanations, partial dependence plot, and individual conditional expectation provided enhanced interpretability. PM 2.5 background concentration and humidity mostly affected the prediction results. Higher PM 2.5 background concentration levels notably increased the predicted values of both PM 10 and PM 2.5 . Moreover, continuous PM emissions from construction activities can mask the natural reduction of PM 10 and PM 2.5 caused by high humidity. This study provides guidance for dust estimation and environmental protection during road construction. Significance Statement Particulate matter (PM) pollution is a major source of air pollution and health problems globally. PM exposure causes many premature deaths worldwide each year according to the World Health Organization. Subgrade plain soil filling is a crucial process in road construction prone to PM emissions. This study contributes to accurately monitor and predict PM by using spatiotemporal Internet of Things and interpretable machine learning, which helps to understand key influencing factors for better dust suppression during road construction. Further, it provides valuable data for environmental protection agencies to make informed decisions, thereby protecting ambient air quality and public health.

With the continuous expansion of global road networks, developing rapid, efficient, and cost-effective methods for pavement performance assessment is essential. This study used a vibration acceleration sensor to collect vehicle-induced vibration data and established an international roughness index (IRI) estimation model based on a tabular prior-data fitted network (TabPFN). To evaluate the model's effectiveness, a comparative experiment was conducted on a dataset of 957 samples. The TabPFN model was benchmarked against several mainstream models, including categorical boosting (CatBoost), random forest (RF), multilayer perceptron (MLP), support vector machine (SVM), and ridge regression (RR). Experimental results indicate that the TabPFN model significantly outperforms the baseline models. Compared with the suboptimal CatBoost model, TabPFN achieved reductions of 4.316% in mean absolute error (MAE) and 6.589% in root-mean-squared error (RMSE), with a coefficient of determination (R-2) of 0.883. The performance gap between the training and test sets remained within 6%. By integrating fivefold cross validation with Shapley additive explanations interpretability analysis, the study further confirmed that models trained on three-axis vibration features significantly outperform those trained on single-axis features. The proposed detection method effectively combines vibration data from low-cost hardware with the efficient TabPFN algorithm, providing a cost-effective and efficient framework for rapid, large-scale pavement health assessment across road networks.

Piezoionic hydrogel generators have attracted significant attention as highly promising energy conversion devices. However, their practical applications are constrained by insufficient output performance, particularly the limitation of operating frequency at <= 0.1 Hz and low charging rate. This study presents a rapidly preparable piezoionic hydrogel generator designed for fast charging in various dynamic scenarios. Surface-functionalized Super P carbon black nanoparticles strengthen electrostatic interactions and introduce active sites, achieving gelation within tens of seconds without external energy input. The synergistic effect of nanoparticles and lithium salts effectively inhibits ice crystal formation and ensures mechanical flexibility at -90 degrees C. Mechanistically, the positively charged nanoparticles act as "ion regulation switches," amplifying differences in ion mobility through selective adsorption of anions, inducing local enrichment of anions, and generating an exceptionally high output of 827.90 mV and 3.2 A m-2. This hydrogel also achieves two orders of magnitude improvement over conventional piezoionic generators. Its compatibility is demonstrated with both human movements (1 to 4 Hz) and low-frequency mechanical vibrations (10 Hz), capable of delivering an ultra-high charging rate of 146 mV s-1 for a 1 mF capacitor. This work paves the way for multi-scenario energy harvesting and portable power sources applications.

Conductive hydrogels, with their excellent stretchability and self-healing properties, have become key sensing components in wearable electronic devices. However, their application in monolithically integrated stretchable electronics is limited by interfacial adhesion, electrical performance, electronic integration compatibility and traditional hydrogel fabrication processes. Here, we discover that super P carbon nanoparticles serve as an activating agent during hydrogel gelation without extra energy sources. These nanoparticles are utilized to prepare a direct ink writing (DIW) hydrogel for in-situ writing of sensor arrays directly onto wearable substrates (nitrile glove, etc.). This approach effectively prevents the aging effects that are caused by thermal curing or ultraviolet curing on flexible substrates. The integrated hydrogel forms an interlocking structure and noncovalent interactions with the nitrile substrate, providing a robust and conformal interface. The hydrogel sensor is capable of detecting micrometer-scale deformations of 0.01% on the glove surface, with a low hysteresis of 1.39% and durability of over three months. Besides, this hydrogel can form stable interfaces with liquid metals, allowing for integration with liquid metal circuits on a nitrile substrate via DIW, which can replace traditional printed circuit boards to fulfill complex functions. These strategies successfully achieve fully integrated wearable electronics, offering potential for long-term human-machine interaction in outdoor environments.

Gemcitabine (GTB), a clinically approved nucleoside analogue for cancer treatment, faces therapeutic limitations due to rapid enzymatic deactivation by cytidine deaminase (CDA) in tumor microenvironments. Over 90% of systemically administered GTB undergoes catalytic conversion to inactive 2'-deoxy-2',2'-difluorouracil metabolites through CDA-mediated deamination. To address this pharmacological challenge, we developed a multifunctional codelivery nanosystem through strategic engineering of reactive oxygen species (ROS)-generating, mitochondria-targeting CPUL1-TPP (CT) nanoaggregates. These self-assembling CT/GTB complexes were further optimized with DSPE-MPEG2k (DP) and Angiopep-2-conjugated DSPE-MPEG2k (Ang-DP) to create blood-brain barrier (BBB)-penetrating Ang-DP@CT/GTB nanoparticles, enhancing both physiological stability and low-density lipoprotein receptor-related protein 1 (LRP1)-mediated glioma targeting. Comparative analyses revealed that Ang-DP@CT/GTB nanoparticles significantly enhanced GTB's antiglioblastoma efficacy compared to free drug administration in both in vitro and in vivo models. Mechanistic investigations demonstrated that the nanosystem upregulates heme oxygenase-1 (HO-1), subsequently downregulating CDA expression to mitigate GTB metabolism. This coordinated molecular modulation prolongs GTB's therapeutic activity while leveraging the ROS-generating capacity of CT components for synergistic tumor suppression. The BBB-permeable codelivery platform exemplifies a rational design paradigm for multifunctional carrier-free pure nanodrugs (PNDs), demonstrating how clinical drug reformulation can overcome inherent pharmacokinetic limitations. This nanotechnology-driven approach provides critical insights for optimizing chemotherapeutic performance through metabolic pathway regulation and targeted delivery engineering.

Precursor nanoparticles that form spontaneously on hydrolysis of silica source in aqueous solutions of tetrapropylammonium (TPA) hydroxide evolve to (TPA)- silicalite-1, a molecular-sieve crystal that serves as a model for the self-assembly of porous inorganic materials in the presence of organic structure-directing agents. The structure and role of these nanoparticles are of practical significance for the fabrication of 3-dimensional (3D) ordered porous materials and molecular-sieve films, but still remain elusive. Here we show experimental findings of nanoparticle and crystal evolution by controllable manipulation of silicalite-1 synthesis. We have investigated detailed structural features of MFI precursors, which involves precise temperature control during synthesis, fine purification of 6-10 nm silicalite-1 subcrystals (SCs) as starting materials, and subsequent compression via an ice-templating method. SCs aggregate into MFI crystals with unidirectional orientation-indicating that SCs possess at least partial MFI structure and a slab-like morphology. This synthetic route is not only facile and environmentally friendly but also highly reproducible. We believe this method holds great promise for advancing the application of membrane-based separation processes in the natural gas industry and organic liquid separation.

Multimodal sensing in thermomechanically coupled environments, such as lithium-ion battery monitoring, remains constrained by inter-modal interference and low sensitivity to environmental changes. This work presents a decoupling strategy using a modulus-heterogeneous "rotating square" auxetic structure to vertically separate a thermoresistive temperature sensor array from a piezoelectric strain sensor array. This design near-perfectly eliminates thermo-mechanical crosstalk, enabling simultaneous detection of subtle thermal and mechanical variations over a wide temperature range. Specifically, the rigid regions of the auxetic structure rotate under tensile strain to isolate the temperature sensors from deformation, while the stretchable regions expand laterally to enhance in-plane strain in the potassium sodium niobate (KNN)-based piezoelectric layer, compensating for its intrinsically low d31 coefficient. Benefiting from this architecture, the thermoresistive sensor provides stable, independent responses from 25 to 130 degrees C with 0.1 degrees C resolution. Simultaneously, the first developed piezoelectric unit, based on a lead-free KNN ceramic framework, achieves 100% stretchability and reliably detects surface protrusions as small as 5 mu m without thermal interference. When deployed on a pouch-cell battery, the sensor array reliably detects both overheating and swelling, offering a compact and robust dual-parameter sensing solution with strong potential for structural health monitoring in complex environments.

Water pollution caused by antibiotics poses a serious threat to human health and ecosystems. Rapid and efficient removal of antibiotic pollution in water by photocatalysts is one of the effective means to protect the environment and public health. Herein, a wide-spectral responsive upconversion NaGdF4:Yb,Tm@Mn-MOFs core-shell nanostructures were built by coating hexagonal NaGdF4:Yb,Tm cores with amino-functionalized manganese carboxylate MOFs (Mn-MOFs) shells, which exhibited good water dispersibility. Mn-MOFs catalysts is mainly concentrated in the ultraviolet region, while NaGdF4:Yb,Tm nanoparticles can transform infrared light into visible light or even higher energy ultraviolet light, which is harvested by the Mn-MOFs. The optimized nanostructures were tested under simulated solar light (After 120 min irradiation) in the degradation of tetracycline, oxytetracycline hydrochloride and tetracycline hydrochloride, while their degradation rates reached 70%, 72% and 75%, respectively. The better photocatalytic mechanism for antibiotics than its individual components was elucidated, which provides a potential strategy to broaden the full spectrum absorption of the wide bandgap semiconductors and apply for the field of environmental remediation.

It is still crucial to produce mass high-quality graphene through simple and low-cost methods for its wide applications. Herein, a simple and fast method by combining inexpensive transition metal catalysts with electrochemistry to exfoliate natural flake graphite is reported. The electrode is prepared in a sandwich structure, where the titanium mesh will enwrap the nickel net coated with graphite powder. This method can quickly achieve the large-scale preparation of graphene within 15 min. The quality of graphene with large lateral size and few layers has been characterized by XRD, SEM, TEM, Raman, and AFM. The possible electrochemical exfoliation mechanism has been proposed. Oxygen evolution reaction occurs at the anode due to the transition metal catalysts, and hydrogen ions (H+) are generated along with oxygen, H+ and SO42- ions will form a local strong acid. The formation of strong acidic H2SO4 in-situ around electrode will oxidize the edge of the graphite, allowing the intercalation of SO42-, H2O, SO2 and O-2 into the graphite sheets, which will inflate the graphite and exfoliate of graphite into graphene. This strategy is reliable, environmentally friendly, and suitable for industrial production.

The management of transportation infrastructure, particularly urban road networks, faces significant challenges due to limited financial resources. To overcome this hurdle, many have turned to public-private partnerships (PPPs) to enhance the economic value of transportation infrastructure outputs. However, monetizing the value of urban road networks and their surrounding areas remains a complex issue. Urban road networks are complex and vast systems, requiring a comprehensive approach to assess their true value accurately. This study proposes a novel model aimed at monetizing the assets of urban road networks. Unlike previous approaches that solely focus on physical values, our methodology also considers social values in relation to the performance, and spatial importance of urban road networks. The model employs the asset replacement cost as the foundational component and incorporates unquantifiable factors that contribute to economic externalities. Additionally, it takes into account the physical condition of the roads, allowing for the depreciation of road assets. Furthermore, we investigate the impact of social values on roads, a crucial aspect often overlooked in existing studies. This comprehensive approach was demonstrated through a case study in a city in China, where a section of the urban road network was selected for evaluation. The results showcased the model's effectiveness in evaluating the assets of each link in the urban road network. Moreover, it revealed the evolution pattern based on the spatial distribution of various assets and their influence on the overall asset valuation of the road network. The proposed methodology also provides a theoretical foundation to transition from road infrastructure management to asset management. Beyond its academic contributions, our model offers valuable insights for decision-makers, enabling investment analyses and trade-offs in PPPs aimed at enhancing road network assets. By utilizing this approach, stakeholders can make informed decisions to optimize the economic benefits of urban road infrastructure and ensure sustainable transportation systems for the future.

Investigating on the effect of sodium formate mediated double regulation in TiO2 photocatalytic reduction of cadmium is firstly reported. Multiple characterized methods were used to characterize and confirmed the successful reduction of Cd2+ to the form of metal elements by sodium formate-P25 system. The metal elements were attached to the surface of the composite photocatalyst were directly observed by SEM. The removal efficiency of Cd2+ for the composite photocatalyst was tested. When the addition of sodium for-mate was 1 g/L, the maximum removal rate of Cd2+ was 94.8% within 10 min. Further experiments showed the mechanism and activity of the combined catalysis of sodium formate and photocatalysis and the role of composite photocatalyst in photocatalytic activity. This is mainly due to the bidentate chelation between sodium formate and TiO2 which makes it possible to adsorb heavy metal ions and the transfer of photo-generated electrons on the bidentate complex, which improves the survival time of the electrons and re-duces the metal ions. (C) 2021 Published by Elsevier B.V.

Objective: The purpose of this study is to investigate the crystal structure of bacteria-contaminated bovine dentin after Er:YAG laser irradiation at various energy densities from macroscale, microscale, and nanoscale. Background: Er:YAG laser can change the morphology and chemical components of dentin. Few preliminary researchers investigate the laser effect on crystal in dentin tissue. Methods: Twenty dentin specimens from bovine incisors were cocultured with S. mutans (UA 159) and divided into four groups with diverse Er:YAG laser irradiation energy (0, 6.37, 12.73, 19.11J/cm(2)). The ultrastructure of dentin before and after laser irradiation was investigated with nanoanalytical electron microscopy. X-ray diffraction provided the information of lattice parameters in dentin. The morphology of dentin was observed by scanning electron microscopy. High-resolution transmission electron microscope images and selected-area electron diffraction patterns were obtained for characterizing crystal domain size, structure, and microenvironment of dentin. Results: The combination of these methods disclosed that there exist mineralized, demineralized, and remineralized dentin in the bacteria-invaded dentin and can be feasibly recognized using morphological features. Laser treatments influence hydroxyapatite (HAp) crystals in dentin tissue in different ways: needle HAp in mineralized dentin tissue keeps intact with laser irradiation of no higher than 19.11J/cm(2); laser irradiation improves the crystallinity of lamella HAp by domain growth and rearranges its growth orientations. Conclusions: We report an unprecedented presence of remineralization zone consisting of lamella HAp crystals with distinct high-index planes. These findings have broad implications on the role of laser operation in driving biomineralization and shed new insights into a possible relationship between laser irradiation and remineralization.

The accurate evaluation and prediction of highway network traffic state can provide effective information for travelers and traffic managers. Based on the deep learning theory, this paper proposes an evaluation and prediction model of highway network traffic state, which consists of a Fuzzy C-means (FCM) algorithm-based traffic state partition model, a Long Short-Term Memory (LSTM) algorithm-based traffic state prediction model, and a K-Means algorithm-based traffic state discriminant model. The highway network in Hebei Province is employed as a case study to validate the model, where the traffic state of highway network is analyzed using both predicted data and real data. The dataset contains 536,823 pieces of data collected by 233 continuous observation stations in Hebei Province from September 5, 2016, to September 12, 2016. The analysis results show that the model proposed in this paper has a good performance on the evaluation and prediction of the traffic state of the highway network, which is consistent with the discriminant result using the real data.

Freeway is an important component of transportation system. Bottleneck areas on freeway reduce driving safety and traffic efficiency. The development of intelligent connected technology provides a new idea for traffic management. In order to alleviate traffic congestion on the freeway bottleneck area, this paper proposes a variable speed limit (VSL) control method in intelligent connected environment. In this paper, the METANET model is improved by combining intelligent connected environment and VSL control theory. The total traffic capacity (TTC), total travel time (TTT), and total speed difference (TSD) are used to build multiobjective function. The microsimulation at SUMO by using the data from PeMS is employed as a case study to validate the proposed model. The results show that the VSL online control method in intelligent connected environment has better control effect. And the improvement is more obvious with increasing penetration rate of intelligent connected vehicle (ICV).

Paper-structured catalysts present a new branch for achieving desired service merits due to their excellent structural compatibility and fluid diffusion efficiency, whereas synergic mechanism is the main constraint for the rational design. Here, we proposed a series of K-Cu supported paper catalysts (xK-yCu/mTZP) with excellent catalytic activity and stability by using TiO2-ZrO2 mesoporous fibers as matrix. The abundant synergic effects were found in the quaternary K-Cu-Ti-Zr component system, as evidenced by XPS, H-2-TPR, CO2-TPD, etc. The experimental and DFT calculation results showed that addition of copper species as K-stabilizer can inhibit the mobility of potassium, and provide an opportunity for the phase separation following the reaction of 8ZrTiO(4) + K2O -> K2Ti8O17 + 8ZrO(2)(t). As a result, the mobility of free K was confined, leading to improved stability of the paper catalysts. The 15K-5Cu/mTZP exhibited the highest catalytic activity, thermal stability and reusability among all the samples. As far as we know, this is the first study on synergic effects of paper catalysts between matrix fibers and binary active ingredients. The findings afford a promising platform for exploring novel paper catalysts with hierarchical porous structure towards many catalytic applications.

The insufficient utilization of sunlight of ZnO, due to its broad band gap, results in low efficiency for photocatalytic hydrogen production. In this work, plasmonic noble metal nanoparticles (NPs) with different shapes (spheres and rods) were combined with mesoporous ZnO forming core-shell nanostructure to enhance the photocatalytic efficiency of ZnO in visible-light region. The photoelectrochemical water splitting activities of the metal@ZnO core-shell nanocomposites (NCs) were investigated. The photocurrent response of metal@ZnO NCs was found higher than pure ZnO or the mixture of metal NPs and ZnO ascribed to the effective charge transfer mechanism. It was also found that the photocurrent of metal@ZnO NCs was related to the thickness of ZnO and there was optimized shell for each kind of metal cores. Moreover, the introduction of Ag shell can get a higher photoelectrocatalytic efficiency compared to pure Au NPs core due to lower Schottky barrier between Ag and ZnO and wider extinction range in the visible light of Au@Ag NPs.

Maintaining the high photocatalytic activity and stability of Ag3PO4 in practical applications is a still a major challenge. In this study, a series of Ag3PO4@polypyrrole (PPy) core-shell structure photocatalysts were prepared successfully by facile in-situ oxidative polymerization. A transmission electron microscopy image of the composite showed that the PPy shell with a thickness of 5-10 nm was coated tightly on the surface of the Ag3PO4 particle core. X-ray diffractometer and X-ray photoelectron spectroscopy analyses demonstrated that the silver ions were reduced to metallic Ag during polymerization. Ultraviolet-visible diffuse reflectance spectra indicated that the light response range of PA-5 broadened from 300 to 630 nm. Compared with pure Ag3PO4, the composites exhibited higher photocatalytic activities and better photostability, especially Ag3PO4@PPy with a PPy content of 5 wt% (PA-5). The degradation rate of PA-5 with organic dyes exceeded 98% within 15 min under visible light irradiation. Even after five repeated reactions, PA-5 still maintained a high degradation rate of 94.98%. The degradation rate of the pure Ag3PO4 decreased significantly from 94.53% to 60.33% after five cycles. Based on the experimental results, a reasonable mechanism is proposed for the Z-scheme electron-transfer photocatalytic system with metallic Ag as an ohmic contact.

Highly flexible and active potassium-supported sepiolite paper catalysts were fabricated via a facile wet paper-making method.

NaGdF4 is one of the most commonly employed phosphor host matrices for lanthanide doping and is one of the most efficient infrared-to-visible up-conversion fluorescent host materials. Although the structure, morphology and luminescence properties of NaREF4 have been sufficiently investigated, there are very few reported instances of introducing localized order/crystallinity by electron-beam (e-beam) irradiation. In this work, we studied the phase transformation of Gd2O3 from an amorphous to crystalline form via manipulation by e-beam irradiation. The amorphous Gd2O3 occurs as an impurity in the cubic-NaGdF4 nanoparticles (NPs). The structural evolutions, including the transformation from amorphous to crystalline, the recrystallization process and the formation of the graphene@NP core-shell structure, are discussed in detail. We also propose an evolution scheme, in which the e-beam manipulation of the organic-containing NPs induces a subtle structural transformation, depending in principle on the microenvironment of the NPs.

For constructing next-generation lithium-ion batteries with advanced performances, pursuit of high-capacity Li-rich cathodes has caused considerable attention. So far, the low discharge specific capacity and serious capacity fading are strangling the development of Fe-based Li-rich materials. To activate the extra-capacity of Fe-based Li-rich cathode materials, a facile molten salt method is exploited using an al-kaline mixture of LiOH–LiNO3 –Li 2 O2 in this work. The prepared Li 1.09 (Fe 0.2 Ni 0.3 Mn 0.5 ) 0.91 O2 material yields high discharge specific capacity and good cycling stability. The discharge specific capacity shows an up-ward tendency at 0.1 C. After 60 cycles, a high reversible specific capacity of ～250 mAh g 1 is delivered. The redox of Fe 3 /Fe 4 and Mn 3 /Mn 4 are gradually activated during cycling. Notably, the redox reaction of Fe2 /Fe 3 can be observed reversibly below 2 V, which is quite different from the material prepared by a traditional co-precipitation method. The stable morphology of fine nanoparticles (10 0–30 0 nm) is considered benefiting for the distinctive electrochemical performances of Li 1.09 (Fe 0.2 Ni 0.3 Mn 0.5 ) 0.91 O2 . This study demonstrates that molten salt method is an inexpensive and effective approach to activate the extra capacity of Fe-based Li-rich cathode material for high-performance lithium-ion batteries.