Iron-promoted zirconia-alumina supported Ni catalyst for highly efficient and cost-effective hydrogen production via dry reforming of methane.

Developing cost-effective and high-performance catalyst systems for dry reforming of methane (DRM) is crucial for producing hydrogen (H2) sustainably. Herein, we investigate using iron (Fe) as a promoter and major alumina support in Ni-based catalysts to improve their DRM performance. The addition of iron as a promotor was found to add reducible iron species along with reducible NiO species, enhance the basicity and induce the deposition of oxidizable carbon. By incorporating 1 wt.% Fe into a 5Ni/10ZrAl catalyst, a higher CO2 interaction and formation of reducible "NiO-species having strong interaction with support" was observed, which led to an ∼80% H2 yield in 420 min of Time on Stream (TOS). Further increasing the Fe content to 2wt% led to the formation of additional reducible iron oxide species and a noticeable rise in H2 yield up to 84%. Despite the severe weight loss on Fe-promoted catalysts, high H2 yield was maintained due to the proper balance between the rate of CH4 decomposition and the rate of carbon deposit diffusion. Finally, incorporating 3 wt.% Fe into the 5Ni/10ZrAl catalyst resulted in the highest CO2 interaction, wide presence of reducible NiO-species, minimum graphitic deposit and an 87% H2 yield. Our findings suggest that iron-promoted zirconia-alumina-supported Ni catalysts can be a cheap and excellent catalytic system for H2 production via DRM.

Experimental study on the various varieties of photovoltaic panels (PVs) cooling systems to increase their electrical efficiency.

This study investigates the impact of cooling methods on the electrical efficiency of photovoltaic panels (PVs). The efficiency of four cooling techniques is experimentally analyzed. The most effective approach is identified as water-spray cooling on the front surface of PVs, which increases efficiency by 3.9% compared to the case without cooling. The results show that water-spray cooling raises the PV's temperature to 41°C, while improving its average daytime efficiency to 22%. Air-cooling, water-cooling in the tubes behind the PV, and aluminum oxide-water nanofluid cooling in the tubes behind the PV improve efficiency by 1.1%, 1.9%, and 2.7%, respectively. The findings highlight the potential of water-spray cooling as a cost-effective and efficient method to enhance PV efficiency and contribute to the global effort towards renewable energy.

Development of strontium aluminate-printed nonwoven fabric from recycled cotton cellulose for smart wearable photochromic applications.

Smart photochromic and fluorescent textile refers to garments that alter their colorimetric properties in response to external light stimulus. Cotton fibers have been reported as a main resource for many textile and non-textile industries, such as automobiles, medical devices, and furniture applications. Cotton is a natural fiber that is distinguished with breathability, softness, cheapness, and highly absorbent. However, there have been growing demands to find other resources for cotton textiles at high quality and low cost for various applications, such as sensor for harmful ultraviolet radiation. Herein, we present a novel method toward luminescent and photochromic nonwoven textiles from recycled cotton waste. Using the screen-printing technology, a cotton fabric that is both photochromic and fluorescent was developed using aqueous inorganic phosphor nanoparticles (10-18 nm)-containing printing paste. Both CIE Lab color coordinates and photoluminescence spectra showed that the transparent film printed on the nonwoven fabric develops a reversible green emission (519 nm) under ultraviolet light (365 nm), even at low pigment concentration (2%) in the printing paste. Colorfastness of printed fabrics showed high durability and photostability.

Usage of 3D prints with ceramic coating applied as neurological tools - preliminary research.

Purpose: The paper shows a preliminary study of the basic strength parameters of printed parts made of biocompatible polymers with ceramic layers applied to increase the strength of the tool cutting surface. Methods: The specimens were made from different materials and using different 3D printing technologies and the working surfaces that will eventually form the cutting element of the tool were coated with Al2O3. Gloss tests were conducted, properties of the coating, a scratch test of the coated surface, also evaluated surface to-pography. Results: Based on the conducted research, it was found that polymeric materials are characterized by sufficient strength and can be used for disposable tools, however, the use of thin layers of Al2O3 significantly increases the surface strength parameters, which may have a significant impact on the reliability and durability of the tools. The polymer surface covered with an Al2O3 layer is characterised by increased scratch resistance ranging from 24% to 75% depending on the core material and printing technology. The gloss of the surfaces is disproportionately low compared to currently used metal tools, which indicates that they can be used in endoscopic procedures. Conclusions: Based on the conducted research, it was found that the use of thin layers of Al2O3 covering polymer 3D prints is an excellent way to increase strength parameters such as scratch resistance, tribological parameters and light reflections arising on the surface as a result of endoscopic lighting are disproportionately small compared to metallic biomaterials. This gives great hope for using polymer 3D prints for personalised neurosurgical tools.

Steady-state detection of evaporation process based on multivariate data fusion.

In this paper, we introduce an innovative multivariable data fusion strategy for adaptive steady-state detection, specifically tailored for the alumina evaporation process. This approach is designed to counteract the production instabilities that often arise from frequent alterations in production conditions. At the core of our strategy is the application of an adaptive denoising algorithm based on the Gaussian filter, which adeptly eliminates erroneous data from selected variables without compromising the fidelity of the original signal. Subsequently, we implement a multivariable R-test methodology, integrated with the adaptive Gaussian filter, to conduct a thorough and precise steady-state detection via data fusion. The efficiency of this method is rigorously validated using actual data from industrial processes.Our findings reveal that this strategy markedly enhances the stability and efficiency (by 10%) of the alumina evaporation process, thereby offering a substantial contribution to the field. Moreover, the versatility of this approach suggests its potential applicability in a wide range of industrial settings, where similar production challenges prevail. This study not only advances the domain of process control but also underscores the significance of adaptive strategies in managing complex, variable-driven industrial operations.

Do the methods for cleaning the base of brackets used in indirect bonding interfere with adhesion to tooth enamel?

OBJECTIVE: The objective of this study was to evaluate the shear bond strength of metal brackets bonded with indirect bonding, under different surface treatment protocols. MATERIAL AND METHODS: 40 bovine teeth were randomly divided into four groups (n = 10), according to the type of surface treatment: G1 = 70% alcohol, G2 = air/water spray, G3 = 100-µm aluminum oxide blasting, G4 = direct boning. After drying, the standard Edgewise central incisor brackets were bonded with light-cured resin. The brackets were moved from the plaster models by means of a transfer tray made with condensation silicone, and bonded to the surface of the enamel with self-curing adhesive. The samples were submitted to shear tests by a universal test machine. Data were analyzed with SPSS 20.0 by the one-way ANOVA test and the Tukey post-test. RESULTS: No statistically significant difference (p=0.174) was observed between the mean forces measured between the group for shear strength values of the groups during the test: G1 (5.33 MPa), G2 (3.52 MPa) and G3 (4.58 MPa). CONCLUSION: The bracket surface treatment protocols presented similarities in shear bond strength test. However, alcohol 70% and oxide blasting presented higher absolute values of resistance than the water group.

Artificial Neural Network analysis on the effect of mixed convection in triangular-shaped geometry using water-based Al2O3 nanofluid.

The objective of the study is to investigate the fluid flow and heat transfer characteristics applying Artificial Neural Networks (ANN) analysis in triangular-shaped cavities for the analysis of magnetohydrodynamics (MHD) mixed convection with varying fluid velocity of water/Al2O3 nanofluid. No study has yet been conducted on this geometric configuration incorporating ANN analysis. Therefore, this study analyzes and predicts the complex interactions among fluid flow, heat transfer, and various influencing factors using ANN analysis. The process of finite element analysis was conducted, and the obtained results have been verified by previous literature. The Levenberg-Marquardt backpropagation technique was selected for ANN. Various values of the Richardson number (0.01 ≤ Ri ≤ 5), Hartmann number (0 ≤ Ha ≤ 100), Reynolds number (50 ≤ Re ≤ 200), and solid volume fraction of the nanofluid (ϕ = 1%, 3% and 4%) have been selected. The ANN model incorporates the Gauss-Newton method and the method of damped least squares, making it suitable for tackling complex problems with a high degree of non-linearity and uncertainty. The findings have been shown through the use of streamlines, isotherm plots, Nusselt numbers, and the estimated Nusselt number obtained by ANN. Increasing the solid volume fraction improves the rate of heat transmission for all situations with varying values of Ri, Re, and Ha. The Nusselt number is greater with larger values of the Ri and Re parameters, but it lessens for higher value of Ha. Furthermore, ANN demonstrates exceptional precision, as evidenced by the Mean Squared Error and R values of 1.05200e-6 and 0.999988, respectively.

Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste.

Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyramid Segmentation Transformer Net) for grain and pore segmentation in SEM images, which merges multi-scale feature maps through operations like recombination and upsampling to predict and generate segmentation maps. These maps are used to predict the corresponding porosity at ceramic grain boundaries. To increase segmentation accuracy and minimize loss, we employ several strategies. (1) We train the micro-pore detection and segmentation model using publicly available Al2O3 and custom Y2O3 ceramic SEM images. We calculate the pixel percentage of segmented pores in SEM images to determine the surface porosity at the corresponding locations. (2) Utilizing high-temperature hot pressing sintering, we prepared and captured scanning electron microscope images of Y2O3 ceramics, with which a Y2O3 ceramic dataset was constructed through preprocessing and annotation. (3) We employed segmentation penalty cross-entropy loss, smooth L1 loss, and structural similarity (SSIM) loss as the constituent terms of a joint loss function. The segmentation penalty cross-entropy loss helps suppress segmentation loss bias, smooth L1 loss is utilized to reduce noise in images, and incorporating structural similarity into the loss function computation guides the model to better learn structural features of images, significantly improving the accuracy and robustness of semantic segmentation. (4) In the decoder stage, we utilized an improved version of the multi-head attention mechanism (MHA) for feature fusion, leading to a significant enhancement in model performance. Our model training is based on publicly available laser-sintered Al2O3 ceramic datasets and self-made high-temperature hot-pressed sintered Y2O3 ceramic datasets, and validation has been completed. Our Pix Acc score improves over the baseline by 12.2%, 86.52 vs. 76.01, and the mIoU score improves from by 25.5%, 69.10 vs. 51.49. The average relative errors on datasets Y2O3 and Al2O3 were 6.9% and 6.36%, respectively.

Enhancing flame retardancy and heat insulation performances of polyamide 66 composite film by adding CNC/Al2O3 nanohybrids.

Polyamide 66 (PA66) has garnered significant attention due to its exceptional properties; unfortunately, its flammability is challenging. Adding flame retardants (FRs) is a primary approach to enhance PA66 flame retardancy. This study developed a highly flame-retardant PA66 composite film by adding corn-like functional nanohybrids (CNC/Al2O3). Interestingly, CNC/Al2O3 nanohybrids not only formed hydrogen bond interactions with PA66 but also improved crystallization properties as heterogeneous nucleating agents, resulting in the excellent mechanical properties of PA66 composite film. Remarkably, the incorporation of 3 wt% CNC/Al2O3 nanohybrids into PA66 matrix contributed to increasing the LOI to 28.5 %. The pHRR, THR, and TSR were reduced obviously by 55.7 %, 15.3 %, and 65.2 %, respectively. The excellent flame retardancy of PA66 composite film was attributed to the forming of a compact carbon layer catalyzed by the CNC/Al2O3 nanohybrids. Besides, the homogeneous distribution of CNC/Al2O3 nanohybrids endowed the composite film with excellent heat insulation, and the heat insulation rate was up to 31.9 %. Thus, such PA66 composite films with excellent flame retardancy, heat insulation, and mechanical properties could meet the broader application requirements.

Analysis of structural defects and their influence on red-emitting γ-Al2O3:Mn4+,Mg2+ nanowires using positron annihilation spectroscopy.

The present paper reported on the analysis of structural defects and their influence on the red-emitting γ-Al2O3:Mn4+,Mg2+ nanowires using positron annihilation spectroscopy (PAS). The nanowires were synthesized by hydrothermal method and low-temperature post-treatment using glucose as a reducing agent. X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence (PL), and photoluminescence excitation (PLE) were utilized, respectively, for determining the structural phase, morphology and red-emitting intensity in studied samples. Three PAS experiments, namely, positron annihilation lifetime (PAL), Doppler broadening (DB), and electron momentum distribution (EMD), were simultaneously performed to investigate the formations of structural defects in synthesized materials. Obtained results indicated that the doping concentration of 0.06% was optimal for the substitution of Mn4+ and Mg2+ to two Al3+ sites and the formation of oxygen vacancy (VO)-rich vacancy clusters (2VAl + 3VO) and large voids (~0.7 nm) with less Al atoms. Those characteristics reduced the energy transfer between Mn4+ ions, thus consequently enhanced the PL and PLE intensities. Moreover, this optimal doping concentration also effectively controlled the size of nanopores (~2.18 nm); hence, it is expected to maintain the high thermal conductivity of γ-Al2O3 nanowire-phosphor. The present study, therefore, demonstrated a potential application of γ-Al2O3 nanowire-phosphor in fabricating the high-performance optoelectronic devices.

Hybrid Polystyrene-Plasmonic Systems as High Binding Density Biosensing Platforms.

Sensitive, accurate, and early detection of biomarkers is essential for prompt response to medical decisions for saving lives. Some infectious diseases are deadly even in small quantities and require early detection for patients and public health. The scarcity of these biomarkers necessitates signal amplification before diagnosis. Recently, we demonstrated single-molecule-level detection of tuberculosis biomarker, lipoarabinomannan, from patient urine using silver plasmonic gratings with thin plasma-activated alumina. While powerful, biomarker binding density was limited by the surface density of plasma-activated carbonyl groups, that degraded quickly, resulting in immediate use requirement after plasma activation. Therefore, development of stable high density binding surfaces such as high binding polystyrene is essential to improving shelf-life, reducing binding protocol complexity, and expanding to a wider range of applications. However, any layers topping the plasmonic grating must be ultra-thin (<10 nm) for the plasmonic enhancement of adjacent signals. Furthermore, fabricating thin polystyrene layers over alumina is nontrivial because of poor adhesion between polystyrene and alumina. Herein, we present the development of a stable, ultra-thin polystyrene layer on the gratings, which demonstrated 63.8 times brighter fluorescence compared to commercial polystyrene wellplates. Spike protein was examined for COVID-19 demonstrating the single-molecule counting capability of the hybrid polystyrene-plasmonic gratings.

Two-step construction of KPDMS/Al2O3 ultra-barriers for wearable sensors.

Wearable devices hold significant potential in healthcare and medical diagnostics. One major challenge in realizing this potential is the low barrier property of polymer substrates, which fail to withstand surrounding moisture and biofluids. In this work, a two-step strategy involving ALI followed by a UV-curing process is developed to fabricate a K48PDMS/Al2O3 ultra-barrier with high barrier property of 7.82 × 10-5 g m-2 day-1 under stretching strain, representing one of the highest values among current works. Moreover, the K48PDMS/Al2O3 barrier enables Ca-tested devices to exhibit extended operational lifetimes of up to 12 days in simulated rain. It also ensures the high sensitivity of strain sensors for real-time monitoring of health-related physiological signals, even when exposed to aggressive solutions such as PBS, KOH, and glucose. A clear "filling-cross-linking" mechanism is revealed, involving the filling of the void spaces within polymer chains followed by the cross-linking of polymer side chains to enhance the density of the hybrid layer. Adjusting porosity and functional group density ensures complete Al2O3 infiltration into the polymer. The cross-linking increases from 12.31% to 73.79% compared to the UV-curing process alone due to the presence of Al2O3, further enhancing the density of the hybrid layer and its barrier properties. The proposed strategy in our work shows great potential for providing highly reliable encapsulation for wearable electronics.

Restoration-mediated protein substances preferentially drive underlying bauxite residue macroaggregate formation during the simulated ecological reconstruction process.

Constructing a restoration strategy from bauxite residue to Technosols is a cost-effective and sustainable strategy for addressing the ecological and environmental issues caused by high alkalinity, salinity, and fine-grained bauxite residues. However, the quantitative contribution of restoration strategies on the upper bauxite residue-derived Technosols to the underlying untreated bauxite residue in the short term remains poorly understood. This study investigated the mediating mechanisms of vegetation and microbial metabolic effects on the alkalinity, nutrient content, and structure of the underlying bauxite residue (20-50 cm) through a simulated ecological reconstruction of the bauxite residue stockpile. Results indicated that implementing plant restoration strategies resulted in the content of polyphenolic compounds, lipids, tannins, and carbohydrates in bauxite residue dissolved organic matter (DOM) increased significantly from 52.5, 8.2, 3.3, and 2.0 % to 54.4, 10.4, 5.6, and 2.8 %, respectively, while the content of condensed aromatics, unsaturated hydrocarbons, and proteins/amino sugars decreased significantly from 15.5, 12.0, and 6.5 % to 12.1, 9.7, and 5.1 %, respectively. The newly produced molecules were concentrated in regions with low O/C and high H/C ratios, suggesting that short-term vegetation restoration strategies facilitate the transformation of substrate DOM towards easily decomposable and highly bioavailable substances. This led to the migration of the newly produced molecules to the underlying bauxite residue, and as a result, the protein and soluble microbial products of the underlying bauxite residue increased significantly, as well as the pH, exchangeable Na, and < 0.054 mm particles decreased from 10.2, 44.2 cmol kg-1, and 28.1 % to 9.7, 27.1 cmol kg-1, and 19.4 %, respectively, available nitrogen, urease, and 1-2 mm particles increased from 7.3 mg kg-1, 0.2 U mg-1, and 14.5 % to 7.6 mg kg-1, 0.3 U kg-1, and 21.7 %, respectively. Results of the structural equation model further confirmed that plant biomass, proteins/amino sugars, and condensed aromatics in the upper Technosol were the main factors controlling the aggregate formation of the underlying bauxite residue by mediating the protein-dominated biogenic organic matter produced by microbial metabolism.

A cost-effective method for the sensitive detection of levofloxacin using a 3D composite electrode composed of nail polish, graphite and aluminium oxide.

The potential impact on human health and the environment has spurred significant interest in detecting and quantifying pharmaceutical compounds across various matrices, from environmental to biological samples. Here, we present an electrochemical approach for determining levofloxacin in drug, synthetic urine, water, and breast milk samples. An affordable sensor was constructed using 3D printing and composite material based on nail polish, graphite, and aluminum oxide. The conductive composite material was characterized spectroscopically, electrochemically, and by imaging techniques. Subsequently, an electrochemical method based on square wave voltammetry was optimized and applied. The method exhibited good sensitivity (5.11 ± 0.0912 µA L µmol-1 cm-2) and enhanced stability (RSD = 7.2%), with electrochemical responses correlating with the concentration of levofloxacin in the samples tested, yielding recovery values in the range of 98 to 111%. The developed method demonstrated a robust linear working range from 2 to 100 µmol L-1 and a nanomolar detection limit of 128 nmol L-1, rendering it suitable for quantitative analysis. The sensor also shows promise as a platform for the sensitive detection of pharmaceutical compounds, contributing to greater safety and sustainability in these domains.

Discovery of a new volcanic soil material, "Akahoya," as an adsorbent for bacterial and viral pathogens and its application to environmental purification.

Akahoya is a volcanic soil rich in alumina, primarily deposited in Kyushu, Japan. We have found that Akahoya adsorbs bacteria in the water surrounding cattle grazing areas, suggesting a potential for environmental purification. This study investigated the spectrum of microorganisms adsorbed by Akahoya using a column filled with Akahoya through which a suspension of microorganisms was passed. Shirasu soil, another volcanic soil with a different chemical composition, was used as a control. Akahoya effectively adsorbed a diverse range of microorganisms including Escherichia coli, Campylobacter jejuni, Vibrio parahaemolyticus, Salmonella Enteritidis, Staphylococcus aureus, Clostridium perfringens, spores of Bacillus subtilis and Bacillus anthracis, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), murine norovirus, and avian influenza virus (H3N2), whereas Shirasu soil did not adsorb any of the organisms examined. Moreover, bacteria naturally present in river water, such as aerobic bacteria, total coliforms, and Enterobacteriaceae as indicators of river contamination, as well as E. coli added artificially to sterilized river water, were reduced to below the detection limit (<1 CFU/mL) after being passed through Akahoya. Additionally, the number of viable E. coli continued to decrease after contact with Akahoya for 1 month, suggesting bactericidal effects. Notably, the adsorption of E. coli to Akahoya was influenced by the concentration of phosphate and the pH of the suspension due to the interaction between the surface phosphorylation of organisms and Al2O3, the major chemical component of Akahoya. The present results demonstrate the remarkable ability of Akahoya to remove phosphate and microbes, suggesting that Akahoya could be used for water purification processes.IMPORTANCEAlthough a safe and sufficient water supply is essential for the maintenance of hygienic conditions, a major challenge is to develop a comprehensive effective, sustainable, and cost-effective technological approach for the treatment and purification of contaminated water. In this study, we demonstrated that a novel volcanic soil, Akahoya, which has unlimited availability, is a highly effective adsorbent for a wide range of bacterial and viral pathogens, suggesting its potential as a sustainable resource for this purpose. It was suggested that the adsorption of microorganisms on Akahoya was mediated by phosphate groups present on the surface structures of microorganisms, which bind to the alumina component of Akahoya according to the phosphate concentration and pH of the liquid phase. The present findings highlight the exceptional ability of Akahoya to eliminate or reduce phosphate and microorganisms effectively in water purification processes, thus contributing to the development of efficient and sustainable solutions for addressing water pollution challenges.

Influence of Surface Pretreatment on the Bond Strength of a Resin Luting Cement to Saliva-contaminated Enamel and Dentin.

OBJECTIVES: This study aimed to evaluate the influence of surface pretreatment on the shear bond strength (SBS) of a resin luting cement to enamel and dentin with saliva contamination. The surface free energies (SFE) of the adherent surfaces were also determined. METHODS AND MATERIALS: Bovine enamel and dentin were used in this study. For the saliva-contamination, human saliva was applied to the adherent surface for 60 seconds and then air-dried, and the specimens without saliva contamination served as controls. One group of contaminated surfaces was untreated (SC), and the others were pretreated with Katana Cleaner (KC), Multi Etchant (ME), or Ultra-Etch (UE). Fifteen specimens were prepared to measure the SBS for each test group.The mixed resin luting cement paste was applied to the alumina-blasted surface of a stainless-steel rod and placed on the prepared tooth surface. The luting cement was light irradiated for 40 seconds. The bonded specimens were stored for 24 hours at 37°C and half of the bonded specimens underwent 10,000 thermal cycles. The SBS and SFE of the specimens after different pre-treatments were measured. RESULTS: The two-way ANOVA revealed that the factors of pretreatment agent and storage condition had a significant effect on the SBS to enamel and dentin. The SFE values of the SC group were significantly lower than those of the other groups in both enamel and dentin. The SFE of pretreated surface was material dependent. CONCLUSIONS: A pretreatment agent containing functional monomers was shown to be effective in removing saliva contaminants and in creating an effective bonding surface for the resin luting cement.

Assessment of cranial reconstruction utilizing various implant materials: finite element study.

The human head can sometimes experience impact loads that result in skull fractures or other injuries, leading to the need for a craniectomy. Cranioplasty is a procedure that involves replacing the removed portion with either autologous bone or alloplastic material. While titanium has traditionally been the preferred material for cranial implants due to its excellent properties and biocompatibility, its limitations have prompted the search for alternative materials. This research aimed to explore alternative materials to titanium for cranial implants in order to address the limitations of titanium implants and improve the performance of the cranioplasty process. A 3D model of a defective skull was reconstructed with a cranial implant, and the implant was simulated using various stiff and soft materials (such as alumina, zirconia, hydroxyapatite, zirconia-reinforced PMMA, and PMMA) as alternatives to titanium under 2000N impact forces. Alumina and zirconia implants were found to reduce stresses and strains on the skull and brain compared to titanium implants. However, PMMA implants showed potential for causing skull damage under current loading conditions. Additionally, PMMA and hydroxyapatite implants were prone to fracture. Despite these findings, none of the implants exceeded the limits for tensile and compressive stresses and strains on the brain. Zirconia-reinforced PMMA implants were also shown to reduce stresses and strains on the skull and brain compared to PMMA implants. Alumina and zirconia show promise as alternatives to titanium for the production of cranial implants. The use of alternative implant materials to titanium has the potential to enhance the success of cranial reconstruction by overcoming the limitations associated with titanium implants.

Tailoring structural and optical properties of Cu(II)-induced MgAl2O4 nanoparticles and their response to toxic dyes under solar illumination.

Worldwide environmental challenges pose critical problems with the growth of the global economy. Addressing these issues requires the development of an eco-friendly and sustainable catalyst for degrading organic dye pollutants. In this study, copper-doped magnesium aluminates (CuxMg1-xAl2O4) with x = 0.0-0.8 were synthesized using a citrate-based combustion route. The inclusion of Cu(II) significantly impacted the structural, microstructural, optical, and photocatalytic activity of the catalyst. Rietveld analysis of X-ray diffraction powder profiles revealed single-phase spinels crystallized in the face-centered cubic unit cell with Fd 3 ¯ m space group. Chemical states of the ions, surface morphology, and elemental investigation were analyzed by X-ray photoelectron spectroscopy, field-emission scanning electron microscopy, and energy-dispersive X-ray spectroscopy, respectively. UV-visible and diffuse reflectance spectroscopies confirmed the reduction of the band gap due to Cu(II) doping, validated by first-principle investigations using the WIEN2k code. The catalyst with x = 0.8 showed higher photocatalytic efficacy (90% and 93%) for removing two azo organic dye pollutants, rhodamine B and methyl orange, respectively, within 120 min. Degradation kinetics followed a pseudo-first-order mechanism. The doped (0.8) sample was structurally and morphologically stable and reusable under visible irradiation, retaining performance after three runs. Scavenger studies confirmed hydroxyl and superoxide radicals' involvement in the degradation. This work presents an effective approach to enhancing CuxMg1-xAl2O4 catalysts' photodegradation performance, with potential applications in pharmaceuticals and wastewater remediation.

WSe2 Negative Capacitance Field-Effect Transistor for Biosensing Applications.

Field-effect transistor (FET) biosensors based on two-dimensional (2D) materials are highly sought after for their high sensitivity, label-free detection, fast response, and ease of on-chip integration. However, the subthreshold swing (SS) of FETs is constrained by the Boltzmann limit and cannot fall below 60 mV/dec, hindering sensor sensitivity enhancement. Additionally, the gate-leakage current of 2D material biosensors in liquid environments significantly increases, adversely affecting the detection accuracy and stability. Based on the principle of negative capacitance, this paper presents for the first time a two-dimensional material WSe2 negative capacitance field-effect transistor (NCFET) with a minimum subthreshold swing of 56 mV/dec in aqueous solution. The NCFET shows a significantly improved biosensor function. The pH detection sensitivity of the NCFET biosensor reaches 994 pH-1, nearly an order of magnitude higher than that of the traditional two-dimensional WSe2 FET biosensor. The Al2O3/HfZrO (HZO) bilayer dielectric in the NCFET not only contributes to negative capacitance characteristics in solution but also significantly reduces the leakage in solution. Utilizing an enzyme catalysis method, the WSe2 NCFET biosensor demonstrates a specific detection of glucose molecules, achieving a high sensitivity of 4800 A/A in a 5 mM glucose solution and a low detection limit (10-9 M). Further experiments also exhibit the ability of the biosensor to detect glucose in sweat.

Impact of samarium on magnetic and optoelectronic properties of magnesium-based MgSm2X4 (X = S and Se) spinels for spintronics.

Investigating novel compounds has become necessary due to the need for sophisticated materials in optoelectronic devices and spintronics. Because of their unique properties, magnesium-based spinels MgSm2X4 (X = S and Se) are very promising for these applications. We used the spin-polarized PBEsol for structural properties and the PBEsol functional for mechanical behavior, both using the WIEN2k code. Both compounds' stability in the magnetic and non-magnetic phases was validated by the Birch-Murnaghan equation of state, and their stability in the cubic phase was verified by the Born stability criterion. Their ductile character was shown by the computation of Pugh's ratio and Poisson ratio. Both MgSm2S4 and MgSm2Se4 display metallic behavior in the spin-up channel and semiconducting behavior in the spin-down channel, indicating a half-metallic nature, according to TB-mBJ potential calculations. With total magnetic moments of 20 µB, both materials showed ferromagnetic properties. Samarium ions contributed 5.27 µB for MgSm2S4 and 5.34 µB for MgSm2Se4. Furthermore, we computed optical parameters in the energy range of 0 to 15 eV, such as absorption, extinction coefficient, reflectivity, dielectric function, and refractive index. Our results demonstrate the potential of MgSm2X4 spinels for future technological developments by revealing their prospective optoelectronic and spintronic applications.