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Frontiers in Chemistry 2024The deterioration of mild steel in an acidic environment poses a significant challenge in various industries. The emergence of effective corrosion inhibitors has drawn...
Unraveling the corrosion inhibition behavior of prinivil drug on mild steel in 1M HCl corrosive solution: insights from density functional theory, molecular dynamics, and experimental approaches.
The deterioration of mild steel in an acidic environment poses a significant challenge in various industries. The emergence of effective corrosion inhibitors has drawn attention to studies aimed at reducing the harmful consequences of corrosion. In this study, the corrosion inhibition efficiency of Prinivil in a 1M HCl solution through various electrochemical and gravimetric techniques has been investigated for the first time. The results demonstrated that the inhibition efficiency of Prinivil expanded from 61.37% at 50 ppm to 97.35% at 500 ppm concentration at 298 K. With a regression coefficient ( ) of 0.987, K value of 0.935 and E value of 43.024 kJ/mol at 500 ppm concentration of inhibitor, a strong affinity of Prinivil for adsorption onto the metal surface has been significantly found. Scanning electron microscopy (SEM) and contact angle measurement analyses further support the inhibitory behavior of Prinivil, demonstrating the production of a defensive layer on the surface of mild steel. Additionally, molecular dynamics (MD) and Monte Carlo simulations were employed to investigate the stability and interactions between Prinivil and the metallic surface (Fe (1 1 0)) at the atomic level. The computed results reveal strong adsorption of Prinivil upon the steel surface, confirming its viability as a corrosion inhibitor.
PubMed: 38947959
DOI: 10.3389/fchem.2024.1403118 -
ACS Applied Electronic Materials Jun 2024Extensive research efforts of strained germanium (Ge) are currently underway due to its unique properties, namely, (i) possibility of band gap and strain engineering to...
Extensive research efforts of strained germanium (Ge) are currently underway due to its unique properties, namely, (i) possibility of band gap and strain engineering to achieve a direct band gap, thus exhibiting superior radiative properties, and (ii) higher electron and hole mobilities than Si for upcoming technology nodes. Realizing lasing structures is vital to leveraging the benefits of tensile-strained Ge (ε-Ge). Here, we use a combination of different analytical tools to elucidate the effect of the underlying InGaAs/InAlAs and InGaAs overlaying heterostructures on the material quality and strain state of ε-Ge grown by molecular beam epitaxy. Using X-ray analysis, we show the constancy of tensile strain in sub-50 nm ε-Ge in a quantum-well (QW) heterostructure. Further, effective carrier lifetime using photoconductive decay as a function of buffer type exhibited a high (low) defect-limited carrier lifetime of ∼68 ns (∼13 ns) in 0.61% (0.66%) ε-Ge grown on an InGaAs (InAlAs) buffer. These results correspond well with the measured surface roughness of 1.289 nm (6.303 nm), consistent with the surface effect of the ε-Ge/III-V heterointerface. Furthermore, a reasonably high effective lifetime of ∼78 ns is demonstrated in a QW of ∼30 nm 1.6% ε-Ge, a moderate reduction from ∼99 ns in uncapped ε-Ge, alluding to the surface effect of the overlying heterointerface. Thus, the above results highlight the prime quality of ε-Ge that can be achieved via III-V heteroepitaxy and paves a path for integrated Ge photonics.
PubMed: 38947953
DOI: 10.1021/acsaelm.4c00347 -
ACS Applied Electronic Materials Jun 2024Flexible temperature sensors are becoming increasingly important these days. In this work, we explore graphene oxide (GO)/poly(vinyl alcohol) (PVA) nanocomposites for...
Flexible temperature sensors are becoming increasingly important these days. In this work, we explore graphene oxide (GO)/poly(vinyl alcohol) (PVA) nanocomposites for potential application in temperature sensors. The influence of the mixing ratio of both materials, the reduction temperature, and passivation on the sensing performance has been investigated. Various spectroscopic techniques revealed the composite structure and atomic composition. These were complemented by semiempirical quantum chemical calculations to investigate rGO and PVA interaction. Scanning electron and atomic force microscopy measurements were carried out to evaluate dispersion and coated film quality. The temperature sensitivity has been evaluated for several composite materials with different compositions in the range from 10 to 80 °C. The results show that a linear temperature behavior can be realized based on rGO/PVA composites with temperature coefficients of resistance (TCR) larger than 1.8% K and a fast response time of 0.3 s with minimal hysteresis. Furthermore, humidity influence has been investigated in the range from 10% to 80%, and a minor effect is shown. Therefore, we can conclude that rGO/PVA composites have a high potential for excellent passivation-free, humidity-independent, sensitive, and fast response temperature sensors for various applications. The GO reduction is tunable, and PVA improves the rGO/PVA sensor performance by increasing the tunneling effect and band gap energy, consequently improving temperature sensitivity. Additionally, PVA exhibits minimal water absorption, reducing the humidity sensitivity. rGO/PVA maintains its temperature sensitivity during and after several mechanical deformations.
PubMed: 38947952
DOI: 10.1021/acsaelm.4c00729 -
Frontiers in Oncology 2024Accurate tumor target contouring and T staging are vital for precision radiation therapy in nasopharyngeal carcinoma (NPC). Identifying T-stage and contouring the Gross...
BACKGROUND
Accurate tumor target contouring and T staging are vital for precision radiation therapy in nasopharyngeal carcinoma (NPC). Identifying T-stage and contouring the Gross tumor volume (GTV) manually is a laborious and highly time-consuming process. Previous deep learning-based studies have mainly been focused on tumor segmentation, and few studies have specifically addressed the tumor staging of NPC.
OBJECTIVES
To bridge this gap, we aim to devise a model that can simultaneously identify T-stage and perform accurate segmentation of GTV in NPC.
MATERIALS AND METHODS
We have developed a transformer-based multi-task deep learning model that can perform two tasks simultaneously: delineating the tumor contour and identifying T-stage. Our retrospective study involved contrast-enhanced T1-weighted images (CE-T1WI) of 320 NPC patients (T-stage: T1-T4) collected between 2017 and 2020 at our institution, which were randomly allocated into three cohorts for three-fold cross-validations, and conducted the external validation using an independent test set. We evaluated the predictive performance using the area under the receiver operating characteristic curve (ROC-AUC) and accuracy (ACC), with a 95% confidence interval (CI), and the contouring performance using the Dice similarity coefficient (DSC) and average surface distance (ASD).
RESULTS
Our multi-task model exhibited sound performance in GTV contouring (median DSC: 0.74; ASD: 0.97 mm) and T staging (AUC: 0.85, 95% CI: 0.82-0.87) across 320 patients. In early T category tumors, the model achieved a median DSC of 0.74 and ASD of 0.98 mm, while in advanced T category tumors, it reached a median DSC of 0.74 and ASD of 0.96 mm. The accuracy of automated T staging was 76% (126 of 166) for early stages (T1-T2) and 64% (99 of 154) for advanced stages (T3-T4). Moreover, experimental results show that our multi-task model outperformed the other single-task models.
CONCLUSIONS
This study emphasized the potential of multi-task model for simultaneously delineating the tumor contour and identifying T-stage. The multi-task model harnesses the synergy between these interrelated learning tasks, leading to improvements in the performance of both tasks. The performance demonstrates the potential of our work for delineating the tumor contour and identifying T-stage and suggests that it can be a practical tool for supporting clinical precision radiation therapy.
PubMed: 38947898
DOI: 10.3389/fonc.2024.1377366 -
Frontiers in Robotics and AI 2024Electrohydraulic soft actuators are a promising soft actuation technology for constructing bio-inspired underwater robots owing to the features of this technology such...
Electrohydraulic soft actuators are a promising soft actuation technology for constructing bio-inspired underwater robots owing to the features of this technology such as large deformations and forces, fast responses, and high electromechanical efficiencies. However, this actuation technology requires high voltages, thereby limiting the use of these actuators in water and hindering the development of underwater robots. This paper describes a method for creating bio-inspired underwater robots using silicone-layered electrohydraulic soft actuators. The silicone layer functions as an insulator, enabling the application of high voltages underwater. Moreover, bending and linear actuation can be achieved by applying the silicone layers on one or both sides of the actuator. As a proof of concept, bending and linear actuators with planar dimensions of 20 mm × 40 mm (length × width) are fabricated and characterized. Underwater actuation is observed in both types of actuators. The bending actuators exhibit a bending angle and blocked force of 39.0° and 9.6 mN, respectively, at an applied voltage of 10 kV. Further, the linear actuators show a contraction strain and blocked force of 6.6% and 956.1 mN, respectively, at an applied voltage of 10 kV. These actuators are tested at a depth near the surface of water. This ensured that they can operate at least at that depth. The actuators are subsequently used to implement various soft robotic devices such as a ray robot, a fish robot, a water-surface sliding robot, and a gripper. All of the robots exhibit movements as expected; up to 31.2 mm/s (0.91 body length/s) of locomotion speed is achieved by the swimming robots and a retrieve and place task is performed by the gripper. The results obtained in this study indicate the successful implementation of the actuator concept and its high potential for constructing bio-inspired underwater robots and soft robotics applications.
PubMed: 38947862
DOI: 10.3389/frobt.2024.1298624 -
ACS Omega Jun 2024This research combines industrial engineering principles with chemical process modeling to explore the capture of CO from natural gas under cryogenic conditions. The...
This research combines industrial engineering principles with chemical process modeling to explore the capture of CO from natural gas under cryogenic conditions. The study specifically investigates the Solid-Vapor (S-V) phase equilibrium in a methane-carbon dioxide (CH-CO) system. The study employs Response Surface Methodology (RSM) to develop a robust model for predicting phase behavior in industrial gas separation processes. The model is validated using experimental data, offering enhanced operational insights into cryogenic CO capture in industrial applications. The developed RSM model is particularly valuable as it can predict the mole fractions of methane and CO at various temperatures and pressures in the solid-vapor region of phase equilibrium, where limited experimental data make it difficult to estimate these components accurately. The key contribution of this study is to validate the RSM model's available experimental data, and the model can further be used to predict the process conditions at which high methane composition (yCH) can be achieved. The developed model showed good agreement when the results were compared with previous experimental studies. The utilization of chemical engineering data to forecast previously unknown conditions in gas separation processes broadens the scope of industrial process optimization in this work.
PubMed: 38947852
DOI: 10.1021/acsomega.4c01526 -
ACS Omega Jun 2024Carbon-based nanopowders have been used as ionization materials for laser desorption ionization-mass spectrometry (LDI-MS) and are very efficient at detection in low /...
Carbon-based nanopowders have been used as ionization materials for laser desorption ionization-mass spectrometry (LDI-MS) and are very efficient at detection in low / regions. In this study, we aimed to develop a new sheet-type graphite material that possessed a randomly grooved nanostructured surface consisting of developed sp-conjugated atomic carbon to facilitate the desorption/ionization of small compounds in LDI-MS. The graphite sheet exhibited higher UV absorption and provided higher ionization efficiency and survival yield in the LDI-MS detection of a thermometer ion, 4-chloro-benzopyridinium, than those of highly oriented graphite plates. These properties demonstrate that the present graphite sheet is suited for use as an LDI-MS material. Graphite sheet-assisted LDI-MS successfully detected various substances, including amino acids, peptides, and polyethylene glycol polymers, with higher ion intensities and less noise than those associated with conventional organic matrix-assisted LDI-MS (MALDI-MS). Furthermore, graphite sheet-assisted LDI-MS analysis provided more peaks (252 peaks) derived from soy sauce than those obtained by MALDI-MS (36 peaks) and required fewer preparation processes (dilution and air-dried) compared with previously established graphite carbon black-assisted LDI-MS (171 peaks) in the positive mode. This study demonstrates that graphite sheet-assisted LDI-MS has the potential for small organic compound analyses in the biomedical and food science fields.
PubMed: 38947851
DOI: 10.1021/acsomega.4c04524 -
ACS Omega Jun 2024Increased deposition of amyloid-β (Aβ) plaques in the brain is a frequent pathological feature observed in human immunodeficiency virus (HIV)-positive patients....
Increased deposition of amyloid-β (Aβ) plaques in the brain is a frequent pathological feature observed in human immunodeficiency virus (HIV)-positive patients. Emerging evidence indicates that HIV regulatory proteins, particularly the transactivator of transcription (TAT) protein, could interact with Aβ peptide, accelerating the formation of Aβ plaques in the brain and potentially contributing to the onset of Alzheimer's disease in individuals with HIV infection. Nevertheless, the molecular mechanisms underlying these processes remain unclear. In the present study, we have used long all-atom molecular dynamics simulations to probe the direct interactions between the TAT protein and Aβ peptide at the molecular level. Sampling over 28.0 μs, our simulations show that TAT protein induces a shift in the Aβ monomer ensemble toward elongated conformations, exposing aggregation-prone regions on the surface and thereby inducing subsequent aggregation. TAT protein also appears to enhance the stability of preformed Aβ fibrils, while increasing the β-sheet content within these fibrils. Our atomistically detailed simulations qualitatively agree with previous in vitro and in vivo studies. Importantly, our simulations identify key interactions between Aβ and the TAT protein that drive the Aβ aggregation process and stabilize the preformed Aβ aggregates, which are particularly challenging to obtain through current experimental techniques.
PubMed: 38947850
DOI: 10.1021/acsomega.4c02643 -
ACS Omega Jun 2024The automotive industry is always seeking novel solutions to improve the durability and the performance of textile materials used in vehicles. Indeed, especially after...
The automotive industry is always seeking novel solutions to improve the durability and the performance of textile materials used in vehicles. Indeed, especially after the coronavirus pandemic, antibacterial treatments have gained interest for their potential of ensuring cleanliness and safety toward microbial contamination within vehicles. This study gives a panoramic view of the durability of antibacterial treatments applied on textile materials in the automotive industry, focusing on their performance after experiencing accelerated aging processes. Two different textile materials, a fabric and a synthetic leather, both treated with antibacterial agents, were tested according to ISO 22196 and ISO 20743 standards, respectively, using two model microorganisms, and . The impact of mechanical, thermal, and solar aging on the antibacterial properties has been evaluated. In addition, scanning electron microscope (SEM) analysis was performed to investigate the surface morphology of the materials before and after aging. Furthermore, contact angle measurements were conducted. The results suggest that neither mechanical nor thermal aging processes determined diminished antibacterial action. It was determined, instead, that the most damaging stressor for both textile materials was UV aging, causing severe surface alterations and a reduction in antibacterial activity.
PubMed: 38947847
DOI: 10.1021/acsomega.4c01272 -
ACS Omega Jun 2024Pesticides that protect crops from insects and other pests are some of the main causes of water pollution. Imidacloprid (IMC) is the most widely used insecticide in the...
Highly Efficient Photocatalytic Degradation of Imidacloprid Based on Iron Metal-Organic Frameworks of Mesoporous NH-MIL-88b/Graphite Carbon Nitride Nanocomposites by Visible Light Driven in Aqueous Media.
Pesticides that protect crops from insects and other pests are some of the main causes of water pollution. Imidacloprid (IMC) is the most widely used insecticide in the world and should be removed from the environment. This work aims to prepare mesoporous nanocomposites to increase the photodegradation efficiency of IMC. To improve the surface properties and enhance the photocatalytic activity, mesoporous nanocomposites with different weight ratios of graphite carbon nitride (CN = 125, 250, and 500 mg) were prepared by the solvothermal method. Mesoporous NH-MIL-88b(Fe)/graphite carbon nitride (CN = 250 mg, NH-MCN-2) nanocomposites showed the best photocatalytic performance. To save the time and cost of the experiments, central composite design (CCD) and response surface methodology (RSM) were used and the results were obtained as the initial concentration of IMC (20 mg L), amount of photocatalyst (0.76 g L), pH = 5, and degradation time ∼46 min. The maximum photocatalytic degradation efficiency estimated by the model was obtained at 96.31%, which is very close to the actual value of 95.47%. The mesoporous NH-MCN-2 nanocomposite showed excellent stability and suitable reusability with a maximum degradation of 84.5% after five cycles. Results obtained from kinetic studies indicated a rate constant value of 0.08 min, and isotherm models showed that equilibrium data are more consistent with the Langmuir model in photocatalytic degradation. Electrochemical experiments showed significant improvement in the electron transfer rate and photocatalytic activity of the mesoporous NH-MCN-2 nanocomposite. Different trapping agents were used to investigate the effective active species in IMC photodegradation, and it was determined that the hole (h) and OH radical (OH) play the main role. The possible mechanism for IMC photocatalytic degradation was suggested by Mott-Schottky (M-S) electrochemical impedance.
PubMed: 38947846
DOI: 10.1021/acsomega.3c10281