Triclosan disturbs nitrogen removal in constructed wetlands: Responses of microbial structure and functions.

This study investigated the influence of wetland types (vertical and tidal flow constructed wetlands [CWs] [VFCW and TFCW, respectively]) and concentrations of triclosan (TCS) on the removal of pollutants (TCS and nitrogen) and microbial characteristics. The efficiency of TCS removal was significantly higher with 5 µg/L TCS (Phase B) than with 30 µg/L (Phase C) in the two CWs. The efficiencies of removal of NH4+-N and NO3--N were significantly inhibited in Phase C. Compared with the VFCW, the TFCW removed more NH4+-N at the same concentration of TCS, whereas less NO3--N was removed, and it even accumulated. Saccharimondales, an important functional genus with the highest abundance and more node connections with other genera, had a sharp decrease in relative abundance as the increasing concentrations of TCS of the two CWs conformed with its relative abundance and significantly negatively correlated with the concentration of TCS. Differentiated Roseobacter_Clade_CHAB-I-5_Lineage and Sphaerotilus were enriched in the VFCW and TFCW, respectively. The abundance of enzymes that catalyzed nitritation was significantly inhibited by TCS, whereas nitrate reductase (EC 1.7.99.4) catalyzed both denitrification and dissimilatory nitrate reduction to ammonium (DNRA), and nitrite reductase (NADH) (EC 1.7.1.15) that catalyzed DNRA comprised a larger proportion in the two CWs. Simultaneously, the abundances of two enzymes were higher in the TFCW than in the VFCW. The network analysis indicated that the main genera were promoted more by TCS in the VFCW, while inhibited in the TFCW. Moreover, the concentrations of nitrogen (NH4+-N, NO3--N, and TN) significantly positively correlated with TCS-resistant bacteria, and negatively correlated with most nitrogen-transforming bacteria with species that varied between the VFCW and TFCW. The results of this study provide a reference for the molecular biological mechanism of the simultaneous removal of nitrogen and TCS in the CWs.

Loneliness is related to smaller gray matter volumes in ACC and right VLPFC in people with major depression: a UK biobank study.

The anterior cingulate cortex (ACC) and right ventrolateral prefrontal cortex (VLPFC) are thought to have important roles in loneliness (feeling of social isolation/exclusion) experience or regulation and in the pathophysiology of their disturbance in major depressive disorder (MDD). However, the structural abnormalities of these regions and the correlates with loneliness in MDD across the healthy population have not fully been clarified. The study analyzed the link between loneliness and gray matter volumes (GMVs) in the ACC and right VLPFC among 1,005 patients with MDD and 7,247 healthy controls (HCs) using UK Biobank data. Significant reductions in GMV in the right VLPFC were found in MDD males compared to HCs. MDD males also showed a higher association between loneliness and reduced GMVs in the right VLPFC and bilateral ACC than HCs. No such associations were found in MDD females. The findings suggest that loneliness may influence brain structures crucial for emotion experience and regulation, particularly in middle-older aged men with MDD. This highlights the potential adverse effects of loneliness on brain structure in MDD and suggests that social engagement could have a positive impact.

Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning.

Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton yield. Results showed that it was recommended to predict soil salinity, crop evapotranspiration and cotton yield based on soil data (bulk density), meteorological factors, irrigation data and other data. Among them, meteorological factors include annual average temperature, total precipitation, year. Irrigation data include salinity in irrigation water, soil matric potential and irrigation water volume, while other data include soil depth, distance from dripper, days after sowing (for EC and soil salinity), fertilization rate (for yield and ET). The accuracy of the model has reached a satisfactory level, R2 in 0.78-0.99. The performance of stacking ensemble ML was better than that of a single model, i.e., gradient boosting decision tree (GBDT); random forest (RF); extreme gradient boosting regression (XGBR), with R2 increased by 0.02%-19.31%. In all input combinations, other data have a greater impact on the model accuracy, while the RMSE of the S1 scenario (input without meteorological factors) without meteorological data has little difference, which is -34.22%~19.20% higher than that of full input. Given the wide application of drip irrigation in cotton, we recommend the application of ensemble ML to predict soil salinity and crop evapotranspiration, thus serving as the basis for adjusting the irrigation schedule.

Metal-organic rotaxane frameworks constructed from a cucurbit[8]uril-based ternary complex for the selective detection of antibiotics.

Herein we report two 2D layered metal-organic rotaxane frameworks (MORFs), WUST-1 and WUST-2, constituted by a ternary host-guest complex based on cucurbit[8]uril (CB[8]) and an (E)-1-methyl-4-[4-(pyridin-4-yl)styryl] pyridinium (G1) ligand, and different metal ions and auxiliary linkers. Both MORFs are stable in water and highly fluorescence emissive, and can selectively sense nitrofurazone with low detection limits.

Facet modulation of nickel-ruthenium nanocrystals for efficient electrocatalytic hydrogen evolution.

Constructing highly active electrocatalysts towards hydrogen evolution reaction (HER) in both alkaline and acidic media is essential for achieving a sustainable energy economy. Here, a facile ethylene glycol reduction strategy was employed to design the nickel-ruthenium nanocrystals (Ni-Ru NC) with an exposed highly active Ru (101) facet as an efficient electrocatalyst for HER. Testings show Ni-Ru NC outperforms the benchmark catalyst Pt/C by delivering extraordinarily low overpotentials of 21.1 and 70.9 mV to drive 10 mA cm-2 in acidic and alkaline solutions, respectively. The results of experimental and theoretical studies suggest that Ni can modulate the electronic structure of the Ru NC and optimize the hydrogen adsorption free energy on Ru's surface, which accelerates the charge transfer kinetics and enhances the HER performance. The study support the potential application of facet-modulated Ru-based HER eleccatalyst in an alkaline environment.

Overlying water fluoride concentrations influence dissolved organic matter composition and migration from pore water in sediment via bacterial mechanisms.

Fluoride (F-) is widespread in aquatic environments; however, it is not clear whether the fluctuation of F- concentrations in overlying lake water affects the composition and migration of dissolved organic matter (DOM) from sediment. A case study was presented in Sand Lake, China, and an experiment was conducted to analyze the influence of different F- concentrations in overlying water on DOM characteristics. Diffusion resulted in similarities in DOM components between overlying and pore waters, and bacterial activities and enzyme variation resulted in differences between them. Higher F- concentrations in overlying water resulted in a higher pH of pore water, which favored the enrichment of protein-like substances. Higher F- concentrations caused lower DOM concentrations and lower maximum fluorescence intensities (Fmax) of protein-like components in pore water. The F- concentrations had significantly negative correlations with Shannon indexes (P < 0.05). Thiobacillus influenced the migration of tyrosine-like substances by decreasing the pH of pore water. Trichococcus and Fusibacter altered the Fmax of protein-like, humic-like, and fulvic-like substances. The F- concentrations affected the DOM composition and migration due to the response of functional bacterial communities, which were positively correlated with the relative abundance of Thiobacillus and negatively correlated with the relative abundances of Trichococcus and Fusibacter. The high F- concentrations influenced the biosynthesis and degradation of protein-like substances by shifting the abundances of the relevant enzymes. The results of this study may provide ideas for investigating DOM cycling under the influence of F-, especially in lakes with fluctuations in F- concentrations.

Can ensemble machine learning be used to predict the groundwater level dynamics of farmland under future climate: a 10-year study on Huaibei Plain.

Accurate and simple prediction of farmland groundwater level (GWL) is an important aspect of agricultural water management. A farmland GWL prediction model, GWPRE, was developed that integrates four machine learning (ML) models (support vector machine regression, random forest, multiple perceptions, and the stacking ensemble model) with weather forecasts. Based on the GWL and meteorological data of five monitoring wells (N1, N2, N3, N4, and N5) in Huaibei plain from 2010 to 2020, the feasibility of predicting GWL by meteorological factors and ML algorithm was tested. In addition, the stacking ensemble model and future meteorological data after Bayesian model averaging were introduced for the first time to predict GWL under future climate conditions. The results showed that GWL showed an increasing trend in the past decade, but it will decrease in the future. The performance of the stacking ensemble model was better than that of any single ML model, with RMSE reduced by 4.26 ~ 96.97% and the running time reduced by 49.25 ~ 99.40%. GWL was most sensitive to rainfall, and the sensitivity index ranged from 0.2547 to 0.4039. The fluctuation range of GWL of N1, N2, and N3 was 1.5 ~ 2.5 m in the next decade. Due to the possible high rainfall, the GWL decreased in 2024 under RCP 2.6 and 2026 under RCP 8.5. It is worth noting that although the stacking ensemble model can improve the accuracy, it is not always the best among ML models in terms of portability. Nevertheless, the stacking ensemble model was recommended for GWL prediction under climate change.

In Situ Construction of Bifunctional N-Doped Carbon-Anchored Co Nanoparticles for OER and ORR.

Designing highly active and more durable oxygen electrocatalysts for regenerative metal-air batteries and water splitting is of practical significance. Herein, an advanced Co/N-C-800 catalyst composed of abundant Co-Nx structures and carbon defects derived from cobalt phthalocyanine is synthesized. Remarkably, this catalyst exhibits favorable catalytic performance toward the oxygen evolution reaction (OER) with a receivable overpotential of 274 mV in an alkaline medium achieving a current density of 10 mA cm-2 and a Tafel slope of 43.6 mV decade-1, outperforming the commercial RuO2 catalyst. It further displays a high half-wave potential (0.82 V) for the oxygen reduction reaction in 0.1 M KOH. Theoretical calculations reveal that the Co-Nx active sites along with the carbon defects can decrease the adsorption energy of intermediates (OH*, O*, and OOH*) and enhance the electron-transfer ability, thus boosting the OER process.

Functional genera for efficient nitrogen removal under low C/N ratio influent at low temperatures in a two-stage tidal flow constructed wetland.

A two-stage tidal flow constructed wetland (referred to as TFCW-A and TFCW-B) was used to treat low chemical oxygen demand/total nitrogen (COD/TN or simply C/N) ratio influent at low temperatures (<15 °C). The influence of the flooding-resting time (A: 8 h-4 h, B: 4 h-8 h) and effluent recirculation on nitrogen removal and microbial community characteristics were explored. TFCW-B achieved optimal average nitrogen removal efficiency with effluent recirculation (96.05% ammonium nitrogen (NH4+-N); 78.43% TN) and led to nitrate nitrogen (NO3--N) accumulation due to the lack of a carbon source and longer resting time. Ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) were inhibited at low temperatures. Except for nrfA, AOA, AOB, narG and nirS were separated by the flooding-resting time rather than by spatial position. Furthermore, the dominant genera in TFCW-A were Arthrobacter, Rhodobacter, Pseudomonas, and Solitalea, whereas prolonging resting time promoted the growth of Thauera and Zoogloea in TFCW-B. Spearman correlation analysis showed that Zoogloea and Rhodobacter had the strongest correlations with other genera. Moreover, the NH4+-N concentration was significantly positively influenced by Arthrobacter, Rhodobacter, Pseudomonas, and Solitalea but negatively influenced by Thauera and Zoogloea. There was no significant correlation between TN and the dominant genera. This study not only provides a practicable system for wastewater treatment with a low C/N ratio but also presents a theoretical basis for the regulation of microbial communities in nitrogen removal systems at low temperatures.

Controlled release urea improves rice production and reduces environmental pollution: a research based on meta-analysis and machine learning.

To reveal the comprehensive impacts of controlled release urea (CRU) on rice production, nitrogen (N) loss, and greenhouse gas (GHG) emissions, a research based on global meta-analysis and machine learning (ML) was conducted. The results revealed that the CRU application instead of conventional fertilizer can increase rice yield, N use efficiency (NUE), and net benefits by 5.24%, 20.18%, and 9.30%, respectively, under the same amount of N. Furthermore, the emission of N2O and CH4, global warming potential (GWP), the loss of N leaching, and NH3 volatilization were respectively reduced by 25.64%, 18.33%, 21.10%, 14.90%, and 35.88%. The enhancing effects of CRU on rice yield and NUE were greater when the nitrogen application rate was 150 kg N ha-1. Nevertheless, the reducing effects of CRU on GHG emission reduction, nitrogen leaching, and NH3 volatilization was greater at high nitrogen application rate (≥150 kg ha-1). Mitigating effects of CRU on N2O and CH4 emission were significant when soil pH ≥ 6, while CRU posed a measurable effect on reducing nitrogen leaching and NH3 volatilization in paddy fields with soil organic carbon lower than 15 g kg-1 and pH lower than 6. Based on the data collected from meta-analysis, the results of ML demonstrated that it was feasible to use soil data and N application rate to predict N losses in rice fields under CRU. The performance of random forest is better than multilayer perceptron regression in predicting N losses from paddy fields. Thus, it is necessary to promote the application of CRU in paddy fields, especially in coarse soil, in which scenario the environmental pollution would be decreased and the rice yields, NUE, and net benefits would be increased. Meanwhile, machine learning models can be used to predict N losses in CRU paddy fields.

Long-term trends in water quality and influence of water recharge and climate on the water quality of brackish-water lakes: A case study of Shahu Lake.

This study aimed to assess the long-term fluctuations in water quality and the influence of Yellow River water recharge and climatic condition on the water environmental index of a typical brackish-water lake. This study investigated several surface water quality parameters and their relationships with the water quality index (WQI) and trophic status index (TSI) of Shahu Lake from 2011 to 2018. A health risk assessment was conducted, and the correlations among water recharge, climatic conditions, and the aforementioned elements were determined. Results show that the water quality in this lake went from good to moderate and back to good as reflected in the changes in its WQI values from 2011 to 2018. The relative water quality inferiority of this lake in 2015 and 2016 was attributed to the significant increase in its CODMn, TP, TN, NH3-N, and fluoride (F-) concentrations during these years. A combination of these parameters could rapidly predict water quality through a stepwise multiple linear regression. During the study period (except in the frozen season), Shahu Lake maintained a eutrophic status every month (especially in July) irrespective of the spatial changes resulting from low secchi depth and high TP. The limiting nutrient of Shahu Lake changed from phosphorus to both nitrogen and phosphorus, especially during summer, due to seasonal variations and exogenous inputs. The lake had an acceptable health risk level, and water recharge both had positive and negative effects on this lake as reflected in the significant decrease or increase in the concentrations of its principal parameters. This condition was also attributed to temperature and precipitation, which resulted in significant TSI variations. The findings of this study provide ways of estimating and forecasting water quality and trophic status and a basis for managing and improving similar brackish-water lakes.

Hydrogen-Etched Bifunctional Sulfur-Defect-Rich ReS2 /CC Electrocatalyst for Highly Efficient HER and OER.

The design on synthesizing a sturdy, low-cost, clean, and sustainable electrocatalyst, as well as achieving high performance with low overpotential and good durability toward water splitting, is fairly vital in environmental and energy-related subject. Herein, for the first time the growth of sulfur (S) defect engineered self-supporting array electrode composed of metallic Re and ReS2 nanosheets on carbon cloth (referred as Re/ReS2 /CC) via a facile hydrothermal method and the following thermal treatment with H2 /N2 flow is reported. It is expected that, for example, the as-prepared Re/ReS2 -7H/CC for the electrocatalytic hydrogen evolution reaction (HER) under acidic medium affords a quite low overpotential of 42 mV to achieve a current density of 10 mA cm-2 and a very small Tafel slope of 36 mV decade-1 , which are comparable to some of the promising HER catalysts. Furthermore, in the two-electrode system, a small cell voltage of 1.30 V is recorded under alkaline condition. Characterizations and density functional theory results expound that the introduced S defects in Re/ReS2 -7H/CC can offer abundant active sites to advantageously capture electron, enhance the electron transport capacity, and weaken the adsorption free energy of H* at the active sites, being responsible for its superior electrocatalytic performance.

Response Characteristics of Nitrifying Bacteria and Archaea Community Involved in Nitrogen Removal and Bioelectricity Generation in Integrated Tidal Flow Constructed Wetland-Microbial Fuel Cell.

This study explores nitrogen removal performance, bioelectricity generation, and the response of microbial community in two novel tidal flow constructed wetland-microbial fuel cells (TFCW-MFCs) when treating synthetic wastewater under two different chemical oxygen demand/total nitrogen (COD/TN, or simplified as C/N) ratios (10:1 and 5:1). The results showed that they achieved high and stable COD, NH4 +-N, and TN removal efficiencies. Besides, TN removal rate of TFCW-MFC was increased by 5-10% compared with that of traditional CW-MFC. Molecular biological analysis revealed that during the stabilization period, a low C/N ratio remarkably promoted diversities of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in the cathode layer, whereas a high one enhanced the richness of nitrite-oxidizing bacteria (NOB) in each medium; the dominant genera in AOA, AOB, and NOB were Candidatus Nitrosotenuis, Nitrosomonas, and Nitrobacter. Moreover, a high C/N ratio facilitated the growth of Nitrosomonas, while it inhibited the growth of Candidatus Nitrosotenuis. The distribution of microbial community structures in NOB was separated by space rather than time or C/N ratio, except for Nitrobacter. This is caused by the differences of pH, dissolved oxygen (DO), and nitrogen concentration. The response of microbial community characteristics to nitrogen transformations and bioelectricity generation demonstrated that TN concentration is significantly negatively correlated with AOA-shannon, AOA-chao, 16S rRNA V4-V5-shannon, and 16S rRNA V4-V5-chao, particularly due to the crucial functions of Nitrosopumilus, Planctomyces, and Aquicella. Additionally, voltage output was primarily influenced by microorganisms in the genera of Nitrosopumilus, Nitrosospira, Altererythrobacter, Gemmata, and Aquicella. This study not only presents an applicable tool to treat high nitrogen-containing wastewater, but also provides a theoretical basis for the use of TFCW-MFC and the regulation of microbial community in nitrogen removal and electricity production.

Robust nitrate removal and bioenergy generation with elucidating functional microorganisms under carbon constraint in a novel multianode tidal constructed wetland coupled with microbial fuel cell.

This study investigated synthetic wastewater treatment under low inflow C/N ratio and characterized NO3--N-transforming and electricity-producing bacteria in a multi-anode tidal constructed wetland-microbial fuel cell (TFCW-MFC). The optimal concurrent average removal rates of NH4+-N and NO3--N were 73% and 78%, respectively, under a flood/rest/flood time of 4 h/2h/4h in "tide" mode accompanied by one recirculation. The lowest NO3--N concentration among all anodes was observed when the electrode gap was 45 cm. Similarly, the 45 cm anode exhibited selective enrichment of Variovorax and Azoarcus. Correction analysis showed that the high relative abundance of Azoarcus was crucial in enhancing NO3--N removal, and the internal resistance significantly decreased as the relative abundance of Acidovorax increased. These results suggest that NO3--N removal and bioelectricity generation can be promoted in a TFCW-MFC with limited carbon by improving the culture conditions for specific genera.

New linker installation in metal-organic frameworks.

In this Frontier article, we provide a brief overview of recent progress in the new organic component installation in metal-organic frameworks (MOFs) by single-crystal to single-crystal transformation. We discuss the criteria for the MOFs which could provide accessible vacant sites for new linker installation. We highlight three different categories of linker installation based on the nature and the roles of the new linkers. The present challenges and future opportunities in this field are also discussed.

Epitaxial Growth and Integration of Insulating Metal-Organic Frameworks in Electrochemistry.

With tunable pore size and rich active metal centers, metal-organic frameworks (MOFs) have been regarded as the one of the promising materials for catalysis. Prospectively, employing MOFs in electrochemistry would notably broaden the scope of electrocatalysis. However, this application is largely hindered by MOFs' conventionally poor electrical conductivity. Integrating MOFs without compromising their crystalline superiority holds a grand challenge to unveil their pristine electrocatalytic properties. In this work, we introduce an epitaxial growth strategy to accomplish the efficient integration of the insulating MOFs into electrochemistry. Particularly, with pristine-graphene-templated growth, the two-dimensional (2D) single-crystal MOF possesses a large lateral size of ∼23 µm and high aspect ratio up to ∼1500 and exhibits a significant electrochemical enhancement, with a charge transfer resistance of ∼200 ohm and a 30 mA cm-2 current density at only 0.53 V versus a reversible hydrogen electrode. The epitaxial strategy could be further applied to other 2D substrates, such as MoS2. This MOF/graphene 2D architecture sheds light on integrating insulating MOFs into electrochemical applications.

Interface construction in microporous metal-organic frameworks from luminescent terbium-based building blocks.

Interfaces between the pores and the skeletons in metal-organic frameworks (MOFs) define the places where the materials interact with the incoming guests, and constructing functionalized interfaces in MOFs is crucial for various applications. In this report, by using the platform of the well-known terbium-based 12-connected building units, four isoreticular MOFs, FDM-34-37, with fcu-a topology in single crystal form were obtained with linear organic linkers featuring diversified edge lengths (from 17.4 to 23.8 Å) and functionalities (naphthalene, bipyridine, stilbene, and rotatable triphenyl rings). With the surface areas of up to 1850 m2 g-1, these MOFs feature distinct pores with fine-tuned sizes. Furthermore, the relationship between the luminescence originated from the terbium, and the energy transfer between the metals and the linkers on the interfaces were carefully investigated. With characteristic luminescence and potentially active sites from both the metals and the linkers, these MOFs show prospects in various applications.

Photochemical cycloaddition and temperature-dependent breathing in pillared-layer metal-organic frameworks.

Single crystallinity of metal-organic frameworks (MOFs) enables the studies of their flexible behaviors with atomic precision. Here, we investigated the structural transformations triggered by photochemical cycloaddition and with temperature-dependent breathing in a series of pillared-layer MOF structures using a variety of pyrazolecarboxylate linkers for the layers and bipyridyl linkers as the pillars. The ethylenic double bonds from the pillars in close proximity undergo quantitative and seteroselective photochemical [2 + 2] cycloaddition upon UV irradiation, transforming the MOFs into structures with cyclobutane-based pillars. Furthermore, reversible breathing of the new pillared-layer MOF was evidenced by the 10.8% unit cell parameter change along c axis upon temperature change between 298 and 173 K. As revealed by single crystal X-ray diffraction, this transformation originates from the relative flattening of the wavy layers upon cooling. These two different types of characteristic structural transformations responding to inherent reactions and external stimuli happen at single crystalline state, providing a well-defined robust system with controlled flexibility.

Reversible Redox Activity in Multicomponent Metal-Organic Frameworks Constructed from Trinuclear Copper Pyrazolate Building Blocks.

Inorganic functionalization of metal-organic frameworks (MOFs), such as incorporation of multiple inorganic building blocks with distinct metals into one structure and further modulation of the metal charges, endows the porous materials with significant properties toward their applications in catalysis. In this work, by an exploration of the role of 4-pyrazolecarboxylic acid (H2PyC) in the formation of trinuclear copper pyrazolate as a metalloligand in situ, four new MOFs with multiple components in order were constructed through one-pot synthesis. This metalloligand strategy provides multicomponent MOFs with new topologies (tub for FDM-4 and tap for FDM-5) and is also compatible with a second organic linker for cooperative construction of complex MOFs (1,4-benzenedicarboxylic acid for FDM-6 and 2,6-naphthalenedicarboxylic acid for FDM-7). The component multiplicity of these MOFs originates from PyC's ability to separate Cu and Zn on the basis of their differentiated binding affinities toward pyrazolate and carboxylate. These MOFs feature reversible and facile redox transformations between CuI3(PyC)3 and CuII3(µ-OH)(PyC)3(OH)3 without altering the connecting geometries of the units, thus further contributing to the significant catalytic activities in the oxidation of CO and aromatic alcohols and the decomposition of H2O2. This study on programming multiple inorganic components into one framework and modulating their electronic structures is an example of functionalizing the inorganic units of MOFs with a high degree of control.

Transfer-Free Fabrication of Graphene Scaffolds on High-k Dielectrics from Metal-Organic Oligomers.

In situ fabrication of graphene scaffold-ZrO2 nanofilms is achieved by thermal annealing of Zr-based metal-organic oligomers on SiO2 substrates. The structural similarities of the aromatic moieties in the ligand (phenyl-, naphthyl-, anthryl-, and pyrenyl-) compared to graphene play a major role in the ordering of the graphene scaffolds obtained. The depth profiling analysis reveals ultrathin carbon-pure or carbon-rich surfaces of the graphene scaffold-ZrO2 nanofilms. The graphene scaffolds with ∼96.0% transmittance in the visible region and 4.8 nm in thickness can be grown with this non-chemical vapor deposition method. Furthermore, the heterogeneous graphene scaffold-ZrO2 nanofilms show a low sheet resistance of 17.0 kΩ per square, corresponding to electrical conductivity of 3197 S m(-1). The strategy provides a facile method to fabricate graphene scaffolds directly on high-k dielectrics without transferring process, paving the way for its application in fabricating electronic devices.