Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has reached epidemic proportions worldwide and is the most frequent cause of chronic liver disease in developed countries. Within the spectrum of liver disease in MAFLD, steatohepatitis is a progressive form of liver disease and hepatocyte ballooning (HB) is a cardinal pathological feature of steatohepatitis. The accurate and reproducible diagnosis of HB is therefore critical for the early detection and treatment of steatohepatitis. Currently, a diagnosis of HB relies on pathological examination by expert pathologists, which may be a time-consuming and subjective process. Hence, there has been interest in developing automated methods for diagnosing HB. This narrative review briefly discusses the development of artificial intelligence (AI) technology for diagnosing fatty liver disease pathology over the last 30 years and provides an overview of the current research status of AI algorithms for the identification of HB, including published articles on traditional machine learning algorithms and deep learning algorithms. This narrative review also provides a summary of object detection algorithms, including the principles, historical developments, and applications in the medical image analysis. The potential benefits of object detection algorithms for HB diagnosis (specifically those combined with a transformer architecture) are discussed, along with the future directions of object detection algorithms in HB diagnosis and the potential applications of generative AI on transformer architecture in this field. In conclusion, object detection algorithms have huge potential for the identification of HB and could make the diagnosis of MAFLD more accurate and efficient in the near future.

Differentiation and risk stratification of basal cell carcinoma with deep learning on histopathologic images and measuring nuclei and tumor microenvironment features.

BACKGROUND: Nuclear pleomorphism and tumor microenvironment (TME) play a critical role in cancer development and progression. Identifying most predictive nuclei and TME features of basal cell carcinoma (BCC) may provide insights into which characteristics pathologists can use to distinguish and stratify this entity. OBJECTIVES: To develop an automated workflow based on nuclei and TME features from basaloid cell tumor regions to differentiate BCC from trichoepithelioma (TE) and stratify BCC into high-risk (HR) and low-risk (LR) subtypes, and to identify the nuclear and TME characteristics profile of different basaloid cell tumors. METHODS: The deep learning systems were trained on 161 H&E -stained sections which contained 51 sections of HR-BCC, 50 sections of LR-BCC and 60 sections of TE from one institution (D1), and externally and independently validated on D2 (46 sections) and D3 (76 sections), from 2015 to 2022. 60%, 20% and 20% of D1 data were randomly splitted for training, validation and testing, respectively. The framework comprised four stages: tumor regions identification by multi-head self-attention (MSA) U-Net, nuclei segmentation by HoVer-Net, quantitative feature by handcrafted extraction, and differentiation and risk stratification classifier construction. Pixel accuracy, precision, recall, dice score, intersection over union (IoU) and area under the curve (AUC) were used to evaluate the performance of tumor segmentation model and classifiers. RESULTS: MSA-U-Net model detected tumor regions with 0.910 precision, 0.869 recall, 0.889 dice score and 0.800 IoU. The differentiation classifier achieved 0.977 ± 0.0159, 0.955 ± 0.0181, 0.885 ± 0.0237 AUC in D1, D2 and D3, respectively. The most discriminative features between BCC and TE contained Homogeneity, Elongation, T-T_meanEdgeLength, T-T_Nsubgraph, S-T_HarmonicCentrality, S-S_Degrees. The risk stratification model can well predict HR-BCC and LR-BCC with 0.920 ± 0.0579, 0.839 ± 0.0176, 0.825 ± 0.0153 AUC in D1, D2 and D3, respectively. The most discriminative features between HR-BCC and LR-BCC comprised IntensityMin, Solidity, T-T_minEdgeLength, T-T_Coreness, T-T_Degrees, T-T_Betweenness, S-T_Degrees. CONCLUSIONS: This framework hold potential for future use as a second opinion helping inform diagnosis of BCC, and identify nuclei and TME features related with malignancy and tumor risk stratification.

A novel pipeline for computerized mouse spermatogenesis staging.

MOTIVATION: Differentiating 12 stages of the mouse seminiferous epithelial cycle is vital towards understanding the dynamic spermatogenesis process. However, it is challenging since two adjacent spermatogenic stages are morphologically similar. Distinguishing Stages I-III from Stages IV-V is important for histologists to understand sperm development in wildtype mice and spermatogenic defects in infertile mice. To achieve this, we propose a novel pipeline for computerized spermatogenesis staging (CSS). RESULTS: The CSS pipeline comprises four parts: (i) A seminiferous tubule segmentation model is developed to extract every single tubule; (ii) A multi-scale learning (MSL) model is developed to integrate local and global information of a seminiferous tubule to distinguish Stages I-V from Stages VI-XII; (iii) a multi-task learning (MTL) model is developed to segment the multiple testicular cells for Stages I-V without an exhaustive requirement for manual annotation; (iv) A set of 204D image-derived features is developed to discriminate Stages I-III from Stages IV-V by capturing cell-level and image-level representation. Experimental results suggest that the proposed MSL and MTL models outperform classic single-scale and single-task models when manual annotation is limited. In addition, the proposed image-derived features are discriminative between Stages I-III and Stages IV-V. In conclusion, the CSS pipeline can not only provide histologists with a solution to facilitate quantitative analysis for spermatogenesis stage identification but also help them to uncover novel computerized image-derived biomarkers. AVAILABILITY AND IMPLEMENTATION: https://github.com/jydada/CSS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Multi-tissue segmentation model of whole slide image of pancreatic cancer based on multi task and attention mechanism].

Accurate segmentation of whole slide images is of great significance for the diagnosis of pancreatic cancer. However, developing an automatic model is challenging due to the complex content, limited samples, and high sample heterogeneity of pathological images. This paper presented a multi-tissue segmentation model for whole slide images of pancreatic cancer. We introduced an attention mechanism in building blocks, and designed a multi-task learning framework as well as proper auxiliary tasks to enhance model performance. The model was trained and tested with the pancreatic cancer pathological image dataset from Shanghai Changhai Hospital. And the data of TCGA, as an external independent validation cohort, was used for external validation. The F1 scores of the model exceeded 0.97 and 0.92 in the internal dataset and external dataset, respectively. Moreover, the generalization performance was also better than the baseline method significantly. These results demonstrate that the proposed model can accurately segment eight kinds of tissue regions in whole slide images of pancreatic cancer, which can provide reliable basis for clinical diagnosis.

Deep SED-Net with interactive learning for multiple testicular cell types segmentation and cell composition analysis in mouse seminiferous tubules.

The development of mouse spermatozoa is a continuous process from spermatogonia, spermatocytes, spermatids to mature sperm. Those developing germ cells (spermatogonia, spermatocyte, and spermatids) together with supporting sertoli cells are all enclosed inside seminiferous tubules of the testis, their identification is key to testis histology and pathology analysis. Automated segmentation of all these cells is a challenging task because of their dynamical changes in different stages. The accurate segmentation of testicular cells is critical in developing computerized spermatogenesis staging. In this paper, we present a novel segmentation model, SED-Net, which incorporates a squeeze-and-excitation (SE) module and a dense unit. The SE module optimizes and obtains features from different channels, whereas the dense unit uses fewer parameters to enhance the use of features. A human-in-the-loop strategy, named deep interactive learning, is developed to achieve better segmentation performance while reducing the workload of manual annotation and time consumption. Across a cohort of 274 seminiferous tubules from stages VI to VIII, the SED-Net achieved a pixel accuracy of 0.930, a mean pixel accuracy of 0.866, a mean intersection over union of 0.710, and a frequency weighted intersection over union of 0.878, respectively, in terms of four types of testicular cell segmentation. There is no significant difference between manual annotated tubules and segmentation results by SED-Net in cell composition analysis for tubules from stages VI to VIII. In addition, we performed cell composition analysis on 2346 segmented seminiferous tubule images from 12 segmented testicular section results. The results provided quantitation of cells of various testicular cell types across 12 stages. The rule reflects the cell variation tendency across 12 stages during development of mouse spermatozoa. The method could enable us to not only analyze cell morphology and staging during the development of mouse spermatozoa but also potentially could be applied to the study of reproductive diseases such as infertility.

Designed Core-Shell Fe3O4@Polydopamine for Effectively Removing Uranium(VI) from Aqueous Solution.

Adsorbents with the combination of magnetic separation and removal performance are expected for reducing the adverse impact of nuclear pollution. In this study, the core-shell Fe3O4@polydopamine (Fe3O4@PDA) was successfully synthesized and used for removal of uranium (U(VI)) ion from aqueous solution. The abundant N-containing groups derived from PDA exist as the chelate sites for U(VI) and contribute greatly for U(VI) removal. Experimental results show that Fe3O4@PDA (56.39 mg g-1) exhibits greater sorption capacity for U(VI) removal compared with the pure Fe3O4 (9.17 mg g-1). The sorption isotherm can be well fitted with Freundlich model and the sorption process is endothermic and spontaneous. The removal of U(VI) can be explained by the complexation of U(VI) with -NH-, -NH2 and C-O in the surface of Fe3O4@PDA by X-ray photoelectron spectroscopy (XPS) analysis.

Correction: Plasma-induced grafting of polyacrylamide on graphene oxide nanosheets for simultaneous removal of radionuclides.

Correction for 'Plasma-induced grafting of polyacrylamide on graphene oxide nanosheets for simultaneous removal of radionuclides' by Wencheng Song et al., Phys. Chem. Chem. Phys., 2015, 17, 398-406.

Enhanced Photocatalytic Simultaneous Removals of Cr(VI) and Bisphenol A over Co(II)-Modified TiO2.

To enhance the electron-hole separation and boost the practical performance of commercial titania (Degussa P25) under natural solar light, in this work, P25 was modified with Co(II) species (CoP25) through post-treatment with decomposition of Co-ethylenediaminetetraacetic acid precursors in a wet chemical anchoring process. With appropriate Co(II) loading amount as molecular cocatalyst, the resulted CoP25-4 showed significantly improved photocatalytic performance for Cr(VI) reduction and bisphenol A (BPA) oxidation under UV-light irradiation. The coexistence of Cr(VI) and BPA promoted mutually the degradation of both pollutants. Under simulated solar light (AM 1.5G) illumination, the Cr(VI) reduction rate over CoP25-4 was 8.5 times enhanced compared with that over P25, whereas the simultaneous degradation rate of BPA over CoP25-4 was 8 times higher than that over P25. Further investigations indicated that the covalent atomic Co(II) anchoring on P25 significantly promoted the photogenerated electron-hole separation and facilitated Cr(VI) reduction via the formation of a Co(I) intermediate and simultaneously boosted BPA oxidation. Our results demonstrated a facile strategy to modify P25 with remarkably improved performance for the practical application in environmental pollution management under natural light excitation.

Efficient elimination of Cr(VI) from aqueous solutions using sodium dodecyl sulfate intercalated molybdenum disulfide.

In recent years, the heavy metal ions have been immoderately released into the ecological system and result in potential hazardous to public health. Herein, the sodium dodecyl sulfate intercalated molybdenum disulfide (SDS-MoS2) was synthesized for the adsorption of Cr(VI). The SDS molecule was flat and vertically intercalated into the interlayer of MoS2, which was further evidenced by density functional theory calculations. The capture of Cr(VI) on the sphere-like SDS-MoS2 relied on solution pH. The retention of Cr(VI) on SDS-MoS2 attained 63.92 mg/g, and the removal process was endothermic, spontaneous and increased with temperature increasing. The main removal mechanism of Cr(VI) onto SDS-MoS2 was Cr(VI) fixing on the surface of the composites by chemisorption involving possible Cr-S coordination bonding. More importantly, Cr(VI) passed into the increased interlamination and reacted at the interlamination of SDS-MoS2, which was further proved at molecular level. The results can provide critical information for the application of SDS-MoS2 in Cr(VI) elimination or other kinds of pollutants removal in natural aquatic environment.

Metal-organic framework-based materials: superior adsorbents for the capture of toxic and radioactive metal ions.

Highly efficient removal of metal ion pollutants, such as toxic and nuclear waste-related metal ions, remains a serious task from the biological and environmental standpoint because of their harmful effects on human health and the environment. Recently, highly porous metal-organic frameworks (MOFs), with excellent chemical stability and abundant functional groups, have represented a new addition to the area of capturing various types of hazardous metal ion pollutants. This review focuses on recent progress in reported MOFs and MOF-based composites as superior adsorbents for the efficient removal of toxic and nuclear waste-related metal ions. Aspects related to the interaction mechanisms between metal ions and MOF-based materials are systematically summarized, including macroscopic batch experiments, microscopic spectroscopy analysis, and theoretical calculations. The adsorption properties of various MOF-based materials are assessed and compared with those of other widely used adsorbents. Finally, we propose our personal insights into future research opportunities and challenges in the hope of stimulating more researchers to engage in this new field of MOF-based materials for environmental pollution management.

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers.

Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States. One critical question with these tumors is identifying which patients will receive added benefit from adjuvant chemotherapy. Nuclear pleomorphism (variance in nuclear shape and morphology) is an important constituent of breast grading schemes, and in ER+ cases, the grade is highly correlated with disease outcome. This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative (LN-), ER+ BCa could help stratify patients into discrete (<10 years short-term vs. >10 years long-term survival) outcome groups independent of standard clinical and pathological parameters. We considered a tissue microarray (TMA) cohort of 276 ER+, LN- patients comprising 150 patients with long-term and 126 patients with short-term overall survival, wherein 177 randomly chosen cases formed the modeling set, and 99 remaining cases the test set. Segmentation of individual nuclei was performed using multiresolution watershed; subsequently, 615 features relating to nuclear shape/texture and orientation disorder were extracted from each TMA spot. The Wilcoxon's rank-sum test identified the 15 most prognostic quantitative histomorphometric features within the modeling set. These features were then subsequently combined via a linear discriminant analysis classifier and evaluated on the test set to assign a probability of long-term vs. short-term disease-specific survival. In univariate survival analysis, patients identified by the image classifier as high risk had significantly poorer survival outcome: hazard ratio (95% confident interval) = 2.91(1.23-6.92), p = 0.02786. Multivariate analysis controlling for T-stage, histology grade, and nuclear grade showed the classifier to be independently predictive of poorer survival: hazard ratio (95% confident interval) = 3.17(0.33-30.46), p = 0.01039. Our results suggest that quantitative histomorphometric features of nuclear shape and orientation are strongly and independently predictive of patient survival in ER+, LN- BCa.

l-cysteine intercalated layered double hydroxide for highly efficient capture of U(VI) from aqueous solutions.

l-cysteine intercalated Mg/Al layered double hydroxide (Cys-LDH) composites were fabricated and applied for treating the U(VI) contaminated wastewater under various conditions. Interaction mechanisms and adsorption properties were investigated by using batch experiments with spectroscopy analysis. The adsorption isotherms and kinetics were fitted perfectly with the Langmuir isotherm and the pseudo-second-order model, respectively. The significant maximum adsorption capacity of Cys-LDH (211.58 mg/g) compared to LDH was attributed to the larger number of functional groups on Cys-LDH. The presence of humic acid (HA) decreased U(VI) elimination on Cys-LDH at high pH but increased U(VI) removal at low pH. Typically, the presence of various anions (such as NO3-, Cl-, ClO4- and SO42-) did not obviously affect U(VI) adsorption on Cys-LDH, while the coexisted CO32- significantly affected U(VI) elimination. The predominate adsorption were determined to be the formation of Cys-U(VI)-Cys complexes with cysteine in the Cys-LDH interlayers. The results demonstrated that the Cys-LDH are promising adsorbents for efficient elimination and extraction of radionuclides in actual environmental contamination management.

Adsorption, Aggregation, and Deposition Behaviors of Carbon Dots on Minerals.

The increased production of carbon dots (CDs) and the release and accumulation of CDs in both surface and groundwater has resulted in the increasing interest in their research. To assess the environmental behavior of CDs, the interaction between CDs and goethite was studied under different environmental conditions. Electrokinetic characterization of CDs suggested that the ζ-potential and size distribution of CDs were affected by pH and electrolyte species, indicating that these factors influenced the stability of CDs in aqueous solutions. Traditional Derjaguin-Landau-Verwey-Overbeek theory did not fit well the aggregation process of CDs. Results of the effects of pH and ionic strength suggested that electronic attraction dominated the aggregation of CDs. Compared with other minerals, hydrogen-bonding interactions and Lewis acid-base interactions contributed to the aggregation of CDs, in addition to van der Waals and electrical double-layer forces. Adsorption isotherms and microscopic Fourier transformed infrared spectroscopy indicated that chemical bonds were formed between CDs and goethite. These findings are useful to understand the interaction of CDs with minerals, as well as the potential fate and toxicity of CDs in the natural environment, especially in soils and sediments.

Macroscopic, Spectroscopic, and Theoretical Investigation for the Interaction of Phenol and Naphthol on Reduced Graphene Oxide.

Interaction of phenol and naphthol with reduced graphene oxide (rGO), and their competitive behavior on rGO were examined by batch experiments, spectroscopic analysis and theoretical calculations. The batch sorption showed that the removal percentage of phenol or naphthol on rGO in bisolute systems was significantly lower than those of phenol or naphthol in single-solute systems. However, the overall sorption capacity of rGO in bisolute system was higher than single-solute system, indicating that the rGO was a very suitable material for the simultaneous elimination of organic pollutants from aqueous solutions. The interaction mechanism was mainly π-π interactions and hydrogen bonds, which was evidenced by FTIR, Raman and theoretical calculation. FTIR and Raman showed that a blue shift of C═C and -OH stretching modes and the enhanced intensity ratios of ID/IG after phenols sorption. The theoretical calculation indicated that the total hydrogen bond numbers, diffusion constant and solvent accessible surface area of naphthol were higher than those of phenol, indicating higher sorption affinity of rGO for naphthol as compared to phenol. These findings were valuable for elucidating the interaction mechanisms between phenols and graphene-based materials, and provided an essential start in simultaneous removal of organics from wastewater.

Plasma-Facilitated Synthesis of Amidoxime/Carbon Nanofiber Hybrids for Effective Enrichment of 238U(VI) and 241Am(III).

Plasma- and chemical-grafted amidoxime/carbon nanofiber hybrids (p-AO/CNFs and c-AO/CNFs) were utilized to remove 238U(VI) and 241Am(III) from aqueous solutions, seawater, and groundwater. Characteristic results indicated more nitrogen-containing groups in p-AO/CNFs compared to c-AO/CNFs. The maximum adsorption capacities of p-AO/CNFs at pH 3.5 and T = 293 K (588.24 mg of 238U(VI)/g and 40.79 mg of 241Am(III)/g from aqueous solutions, respectively) were significantly higher than those of c-AO/CNFs (263.18 and 22.77 mg/g for 238U(VI) and 241Am(III), respectively), which indicated that plasma-grafting was a highly effective, low-cost, and environmentally friendly method. Adsorption of 238U(VI) on AO/CNFs from aqueous solutions was significantly higher than that of 238U(VI) from seawater and groundwater; moreover, AO/CNFs displayed the highest effective selectivity for 238U(VI) compared to the other radionuclides. Adsorption of 238U(VI) onto AO/CNFs created inner-sphere complexes (e.g., U-C shells) as shown by X-ray absorption fine structure analysis, which was supported by surface complexation modeling. Three inner-sphere complexes gave excellent fits to pH-edge and isothermal adsorption of 238U(VI) on the AO/CNFs. These observations are crucial for the utilization of plasma-grafted, AO-based composites in the preconcentration and immobilization of lanthanides and actinides in environmental remediation.

Surface Modification of Graphene Oxides by Plasma Techniques and Their Application for Environmental Pollution Cleanup.

Graphene oxides (GOs) have come under intense multidisciplinary study because of their unique physicochemical properties and possible applications. The large amount of oxygen-containing functional groups on GOs leads to a high sorption capacity for the removal of various kinds of organic and inorganic pollutants from aqueous solutions in environmental pollution cleanup. However, the lack of selectivity results in difficulty in the selective removal of target pollutants from aqueous solutions in the presence of other coexisting pollutants. Herein, the surface grafting of GOs with special oxygen-containing functional groups using low-temperature plasma techniques and the application of the surface-modified GOs for the efficient removal of organic and inorganic pollutants in environmental pollution are reviewed. This paper gives an account of our research on the application of GO-based nanomaterials in environmental pollution cleanup, including: (1) the synthesis and surface grafting of functional groups on GOs, summarizing various types of low-temperature plasma techniques for the synthesis of graphene/GOs; and (2) the application of graphene/GOs and their composites for the efficient removal of organic and inorganic pollutants from aqueous solutions, including the interaction mechanism according to recently published results.

Macroscopic and Microscopic Investigation of U(VI) and Eu(III) Adsorption on Carbonaceous Nanofibers.

The adsorption mechanism of U(VI) and Eu(III) on carbonaceous nanofibers (CNFs) was investigated using batch, IR, XPS, XANES, and EXAFS techniques. The pH-dependent adsorption indicated that the adsorption of U(VI) on the CNFs was significantly higher than the adsorption of Eu(III) at pH < 7.0. The maximum adsorption capacity of the CNFs calculated from the Langmuir model at pH 4.5 and 298 K for U(VI) and Eu(III) were 125 and 91 mg/g, respectively. The CNFs displayed good recyclability and recoverability by regeneration experiments. Based on XPS and XANES analyses, the enrichment of U(VI) and Eu(III) was attributed to the abundant adsorption sites (e.g., -OH and -COOH groups) of the CNFs. IR analysis further demonstrated that -COOH groups were more responsible for U(VI) adsorption. In addition, the remarkable reducing agents of the R-CH2OH groups were responsible for the highly efficient adsorption of U(VI) on the CNFs. The adsorption mechanism of U(VI) on the CNFs at pH 4.5 was shifted from inner- to outer-sphere surface complexation with increasing initial concentration, whereas the surface (co)precipitate (i.e., schoepite) was observed at pH 7.0 by EXAFS spectra. The findings presented herein play an important role in the removal of radionuclides on inexpensive and available carbon-based nanoparticles in environmental cleanup applications.

Coagulation Behavior of Graphene Oxide on Nanocrystallined Mg/Al Layered Double Hydroxides: Batch Experimental and Theoretical Calculation Study.

Graphene oxide (GO) has attracted considerable attention because of its remarkable enhanced adsorption and multifunctional properties. However, the toxic properties of GO nanosheets released into the environment could lead to the instability of biological system. In aqueous phase, GO may interact with fine mineral particles, such as chloridion intercalated nanocrystallined Mg/Al layered double hydroxides (LDH-Cl) and nanocrystallined Mg/Al LDHs (LDH-CO3), which are considered as coagulant molecules for the coagulation and removal of GO from aqueous solutions. Herein the coagulation of GO on LDHs were studied as a function of solution pH, ionic strength, contact time, temperature and coagulant concentration. The presence of LDH-Cl and LDH-CO3 improved the coagulation of GO in solution efficiently, which was mainly attributed to the surface oxygen-containing functional groups of LDH-Cl and LDH-CO3 occupying the binding sites of GO. The coagulation of GO by LDH-Cl and LDH-CO3 was strongly dependent on pH and ionic strength. Results of theoretical DFT calculations indicated that the coagulation of GO on LDHs was energetically favored by electrostatic interactions and hydrogen bonds, which was further evidenced by FTIR and XPS analysis. By integrating the experimental results, it was clear that LDH-Cl could be potentially used as a cost-effective coagulant for the elimination of GO from aqueous solutions, which could efficiently decrease the potential toxicity of GO in the natural environment.

Environmental Remediation and Application of Nanoscale Zero-Valent Iron and Its Composites for the Removal of Heavy Metal Ions: A Review.

The presence of heavy metals in the industrial effluents has recently been a challenging issue for human health. Efficient removal of heavy metal ions from environment is one of the most important issues from biological and environmental point of view, and many studies have been devoted to investigate the environmental behavior of nanoscale zerovalent iron (NZVI) for the removal of toxic heavy metal ions, present both in the surface and underground wastewater. The aim of this review is to show the excellent removal capacity and environmental remediation of NZVI-based materials for various heavy metal ions. A new look on NZVI-based materials (e.g., modified or matrix-supported NZVI materials) and possible interaction mechanism (e.g., adsorption, reduction and oxidation) and the latest environmental application. The effects of various environmental conditions (e.g., pH, temperature, coexisting oxy-anions and cations) and potential problems for the removal of heavy metal ions on NZVI-based materials with the DFT theoretical calculations and EXAFS technology are discussed. Research shows that NZVI-based materials have satisfactory removal capacities for heavy metal ions and play an important role in the environmental pollution cleanup. Possible improvement of NZVI-based materials and potential areas for future applications in environment remediation are also proposed.

Adsorption of 4-n-Nonylphenol and Bisphenol-A on Magnetic Reduced Graphene Oxides: A Combined Experimental and Theoretical Studies.

Adsorption of 4-n-nonylphenol (4-n-NP) and bisphenol A (BPA) on magnetic reduced graphene oxides (rGOs) as a function of contact time, pH, ionic strength and humic acid were investigated by batch techniques. Adsorption of 4-n-NP and BPA were independent of pH at 3.0- 8.0, whereas the slightly decreased adsorption was observed at pH 8.0-11.0. Adsorption kinetics and isotherms of 4-n-NP and BPA on magnetic rGOs can be satisfactorily fitted by pseudo-second-order kinetic and Freundlich model, respectively. The maximum adsorption capacities of magnetic rGOs at pH 6.5 and 293 K were 63.96 and 48.74 mg/g for 4-n-NP and BPA, respectively, which were significantly higher than that of activated carbon. Based on theoretical calculations, the higher adsorption energy of rGOs + 4-n-NP was mainly due to π-π stacking and flexible long alkyl chain of 4-n-NP, whereas adsorption of BPA on rGOs was energetically favored by a lying-down configuration due to π-π stacking and dispersion forces, which was further demonstrated by FTIR analysis. These findings indicate that magnetic rGOs is a promising adsorbent for the efficient elimination of 4-n-NP/BPA from aqueous solutions due to its excellent adsorption performance and simple magnetic separation, which are of great significance for the remediation of endocrine-disrupting chemicals in environmental cleanup.