Adsorption performance and mechanisms of mercaptans removal from gasoline oil using core-shell AC-based adsorbents: Role of intra-particles space

Sulfur compound detection such as mercaptans in liquid fuels is undesirable because sulfur is the main sourcing emission of sulfur oxide (SOx) into the air. The use of activated carbon (AC) has proven to efficiently remove mercaptans. In the meantime, it is limited by the generation of the second pollution in oil, and the difficulties of recovery and regeneration. To address these issues, a core-shell structured AC with high mechanical strength and big intra-particles space were synthesized and demonstrated to efficiently remove organic pollutants from an aqueous solution without generation of the second pollution in our previous work. However, the performance, characteristics, and mechanism of mercaptans adsorption from gasoline oil by core-shell structured AC was still unclear. In this study, the mercaptans adsorption behaviors using core-shell powdered activated carbon (CSAC) and core-shell granulated activated carbon (CSGAC), along with raw PAC, PAC-core, raw GAC, and GAC-core were carried out. The results showed that both the CSAC and CSGAC adsorbents effectively removed sulfur-based pollutants and were provided with good recovery and recyclability without second pollution in gasoline oil. The CSGAC exhibited a higher mercaptans removal efficiency compared to those of CSAC as a result of the bigger intra-particles space. PAC-based adsorbents, presented the shrinking of removal efficiency after regeneration. The Pseudo-second-order kinetics and Langmuir isotherms models were dominated for mercaptans adsorption by both CSAC and CSGAC. Furthermore, the interactions between mercaptans and the composites were probably ascribed to the Van der Waals force, hydrophobic compatibility, pore texture, and π-π dispersion interaction.

Pore texture analysis in automated 3D breast ultrasound images for implanted lightweight hernia mesh identification: a preliminary study

Background Precise visualization of meshes and their position would greatly aid in mesh shrinkage evaluation, hernia recurrence risk assessment, and the preoperative planning of salvage repair. Lightweight (LW) meshes are able to preserve abdominal wall compliance by generating less post-implantation fibrosis and rigidity. However, conventional 3D imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) cannot visualize the LW meshes. Patients sometimes have to undergo a second-look operation for visualizing the mesh implants. The goal of this work is to investigate the potential advantages of Automated 3D breast ultrasound (ABUS) pore texture analysis for implanted LW hernia mesh identification. Methods In vitro, the appearances of four different flat meshes in both ABUS and 2D hand-held ultrasound (HHUS) images were evaluated and compared. In vivo, pore texture patterns of 87 hernia regions were analyzed both in ABUS images and their corresponding HHUS images. Results In vitro studies, the imaging results of ABUS for implanted LW meshes are much more visualized and effective in comparison to HHUS. In vivo, the inter-class distance of 40 texture features was calculated. The texture features of 2D sectional plans (axial and sagittal plane) have no significant contribution to implanted LW mesh identification. Significant contribution was observed in coronal plane. However, since the mesh may have spatial variation such as shrinkage after implantation surgery, the inter-class distance of 3D coronal plane pore texture features are bigger than 2D coronal plane, so the contribution of 3D coronal plane pore texture features are more valuable than 2D coronal plane for implanted LW mesh identification. The use of 3D pore texture features significantly improved the robustness of the identification method in distinguishing between LW mesh and fascia. Conclusions An innovative new ABUS provides additional pore texture visualization, by separating the LW mesh from the fascia tissues. Therefore, ABUS has the potential to provides more accurate features to characterize pore texture patterns, and ultimately provide more accurate measures for implanted LW mesh identification.

Pore texture analysis in automated 3D breast ultrasound images for implanted lightweight hernia mesh identification: a preliminary study

Background Precise visualization of meshes and their position would greatly aid in mesh shrinkage evaluation, hernia recurrence risk assessment, and the preoperative planning of salvage repair. Lightweight (LW) meshes are able to preserve abdominal wall compliance by generating less post-implant fibrosis and rigidity. However, conventional 3D imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) cannot visualize the LW meshes. Patients sometimes have to undergo a second-look operation for visualizing the mesh implants. The goal of this work is to investigate the potential advantages of Automated 3D breast ultrasound (ABUS) pore texture analysis for implanted LW hernia mesh identification. Methods In vitro, the appearances of four different flat meshes in both ABUS and 2D hand-held ultrasound (HHUS) images were evaluated and compared. In vivo, pore texture patterns of 87 hernia regions were analyzed both in ABUS images and their corresponding HHUS images. Results In vitro studies, the imaging results of ABUS for implanted LW meshes are much more visualized and effective in comparison to HHUS. In vivo, the inter-class distance of 40 texture features was calculated. The texture features of 2D sectional plans (axial and sagittal plane) have no significant contribution to implanted LW mesh identification. Significant contribution was observed in coronal plane. However, since the mesh may have spatial variation such as shrinkage after implant surgery, the inter-class distance of 3D coronal plane pore texture features are bigger than 2D coronal plane, so the contribution of 3D coronal plane pore texture features are more valuable than 2D coronal plane for implanted LW mesh identification. The use of 3D pore texture features significantly improved the robustness of the identification method in distinguishing the LW mesh and fascia. Conclusions An innovative new automated 3D breast ultrasound (ABUS) provides additional pore texture visualization, by separating the LW mesh from the fascia tissues. Therefore, ABUS having the potential to provide more accurate features to characterize pore texture patterns, and ultimately provide more accurate measures for implanted LW mesh identification.

The Preparation of Boron-doped Activated Alumina by impregnating boron in the period of boehmite

This paper systematically studied the pore structure, crystal phase, surface acidity and the chemical environment of aluminum of boron-doped γ-alumina, by impregnating boron in the period of boehmite. The nitrogen adsorption, XRD, FTIR etc. technique was used to determine the pore texture, crystallography, acid/base properties and aluminum coordination. the XRD spectrum of boria-alumina have no significant change due to the addition of boron. The specific surface area and pore volume diameter of B-Al2O3 increase significantly. The NMR spectra of B-Al2O3 shows that boron changed the chemical environment of aluminum, which caused differences in the physical and chemical properties of the surface.

Pore Texture Analysis in Automated 3D Breast Ultrasound Images for Implanted Lightweight Hernia Mesh Identification: A Preliminary Study

Background: Precise visualization of meshes and their position would greatly aid in mesh shrinkage evaluation, hernia recurrence risk assessment, and the preoperative planning of salvage repair. Lightweight (LW) meshes are able to preserve abdominal wall compliance by generating less post-implant fibrosis and rigidity. However, conventional 3D imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) cannot visualize the LW meshes. Patients sometimes have to undergo a second-look operation for visualizing the mesh implants. The goal of this work is to investigate the potential advantages of Automated 3D breast ultrasound (ABUS) pore texture analysis for implanted LW hernia mesh identification.Methods: In vitro, the appearances of four different flat meshes in both ABUS and 2D hand-held ultrasound (HHUS) images were evaluated and compared. In vivo, pore texture patterns of 87 hernia regions were analyzed both in ABUS images and their corresponding HHUS images.Results: In vitro studies, the imaging results of ABUS for implanted LW meshes are much more visualized and effective in comparison to HHUS. In vivo, the inter-class distance of 40 texture features was calculated. The texture features of 2D sectional plans (axial and sagittal plane) have no significant contribution to implanted LW mesh identification. Significant contribution was observed in coronal plane. However, since the mesh may have spatial variation such as shrinkage after implant surgery, the inter-class distance of 3D coronal plane pore texture features are bigger than 2D coronal plane, so the contribution of 3D coronal plane pore texture features are more valuable than 2D coronal plane for implanted LW mesh identification. The use of 3D pore texture features significantly improved the robustness of the identification method in distinguishing the LW mesh and fascia.Conclusions: An innovative new automated 3D breast ultrasound (ABUS) provides additional pore texture visualization, by separating the LW mesh from the fascia tissues. Therefore, ABUS having the potential to provide more accurate features to characterize pore texture patterns, and ultimately provide more accurate measures for implanted LW mesh identification.

Pore texture analysis in automated 3D breast ultrasound images for implanted lightweight hernia mesh identification: a preliminary study

BackgroundPrecise visualization of meshes and their position would greatly aid in mesh shrinkage evaluation, hernia recurrence risk assessment, and the preoperative planning of salvage repair. Lightweight (LW) meshes are able to preserve abdominal wall compliance by generating less post-implant fibrosis and rigidity. However, conventional 3D imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) cannot visualize the LW meshes. Patients sometimes have to undergo a second-look operation for visualizing the mesh implants. The goal of this work is to investigate the potential advantages of Automated 3D breast ultrasound (ABUS) pore texture analysis for implanted LW hernia mesh identification.MethodsIn vitro, the appearances of four different flat meshes in both ABUS and 2D hand-held ultrasound (HHUS) images were evaluated and compared. In vivo, pore texture patterns of 87 hernia regions were analyzed both in ABUS images and their corresponding HHUS images. ResultsIn vitro studies, the imaging results of ABUS for implanted LW meshes are much more visualized and effective in comparison to HHUS. In vivo, the inter-class distance of 40 texture features were calculated. The texture features of 2D sectional plans (axial and sagittal plane) have no significant contribution for implanted LW mesh identification. Significant contribution was observed in coronal plane. However, since the mesh may have spatial variation such as shrinkage after implant surgery, the inter-class distance of 3D coronal plane pore texture features are bigger than 2D coronal plane, so the contribution of 3D coronal plane pore texture features are more valuable than 2D coronal plane for implanted LW mesh identification. The use of 3D pore texture features significantly improved the robustness of the identification method in distinguishing the LW mesh and fascia.ConclusionsAn innovative new automated 3D breast ultrasound (ABUS) provides additional pore texture visualization, by separating the LW mesh from the fascia tissues. Therefore, ABUS having the potential to provide more accurate features to characterize pore texture patterns, and ultimately provide more accurate measures for implanted LW mesh identification.