ACS Applied Electronic Materials最新文献

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have emerged as promising candidates for memory cells and data storage devices, thanks to their exceptional electrical properties and high data storage capabilities enabled by their layered structures. Despite the significant role of charge traps induced by defects in TMD-based memory devices in contributing to hysteresis (ΔV) as a memory window, there remains a lack of research on how different energy levels of these traps specifically affect ΔV. In this study, we report the simultaneous measurement of the spatially distributed ΔV and energy-dependent trap density (D_t) in a MoS₂/hBN structure by using Kelvin probe force microscopy. We observed a strong correlation of 0.61 between the ΔV and D_t in the trap states at 0.4–0.8 eV below the conduction band (E_C), which is attributed to sulfur vacancies (SVs) in MoS₂. Additionally, a slight correlation of 0.3 between the ΔV and D_t in the trap states at approximately 0.4 eV below the E_C was observed, arising from the trap states via the hybridization of individual SVs, aligning well with previous findings. Furthermore, thiol molecule treatment on MoS₂ completely mitigates these correlations by healing the SVs. Our technique, capable of quantifying the energy levels of trap states and their impact on hysteresis, provides crucial insights into the origins of charge trap sources and their charge trapping mechanisms. These insights are essential for the development of TMD-based memory devices and data storage cells.

This study presents a comprehensive comparison between the packed bed and monolith contactor configurations for direct air capture (DAC) via process modeling of a temperature-vacuum swing adsorption (TVSA) process. We investigate various design parameters to optimize performance across different contactor geometries, including pellet size, monolith wall thickness, active sorbent content in monoliths, and packed bed structure configurations, considering both a traditional long column (PB₄₀) and multiple shorter columns configured in parallel (PB₅). Our parametric analysis assesses specific exergy consumption, sorbent, and volume requirements across different operating conditions of a five-step TVSA cycle. For minimizing sorbent requirements, PB₅ and monoliths with over 80% sorbent loading were the best-performing contactor designs with overlapping performance in the low-exergy region. Beyond this region, PB₅ faced limitations in reducing sorbent requirements further and was constrained by a maximum velocity at which it is sensible to operate without substantially increasing the exergy demand. In contrast, monoliths decreased sorbent requirements with minimal exergy increase due to reduced mass transfer resistances and lower pressure drop associated with their thin walls. The analysis of volume requirement-specific exergy Pareto fronts revealed that PB₅ was less competitive with this metric due to the requirements for additional void space in the contactor configuration. The study also revealed that optimal sorbent loading for reducing volume requirements in monoliths differed from those minimizing sorbent usage, with the most effective loading being below 100%. Thus, the optimal contactor design varies depending on the goals of minimizing sorbent and volume requirements, and the choice and design of the contactor will depend on the relative costs of these factors. Lastly, our findings challenge the assumption that higher velocities are always preferable for direct air capture, suggesting instead that the operating velocity depends on the contactor configuration.

Hydroxylamine, as an important reducing agent, disinfectant, foaming agent, and biocide, plays a role in both human life and industrial production. However, its synthesis is confronted with challenges, such as high pollution and large consumption. Here, we propose a coordination tailoring strategy to design 47 graphene-supported single iron atom catalysts (SACs), namely, Fe@C_xZ_y (Z = B, N, O, P, and S), for the reduction of nitric oxide to hydroxylamine. Using density functional theory calculations, we demonstrated the great impact of the coordination environment on the stability, catalytic selectivity, and activity of the Fe site. We identified that the experimentally available Fe@N₄ possesses an ultralow theoretical limiting potential of −0.32 V compared to that of other catalysts. A comprehensive investigation of the electronic properties elucidates the underlying active origin and reaction mechanism of the nitric oxide reduction reaction to hydroxylamine on Fe@N₄. These results not only explain the catalytic origin of synthesized SACs for the NH₂OH production but also offer theoretical guidance for further optimizing high-performance catalysts.

Segregation, the opposite of mixing, poses a common challenge in granular systems. Using a rotating drum as the basic mixing equipment, the fundamental focus of this study is to quantify undesirable segregation. The impact of particle level parameters (size, density, their combination, mass fraction) and system parameters (filling %, rotational speed, and baffle) on the segregation index within the rotating drum is first assessed using the discrete element method (DEM). Later, the machine learning (ML) model is applied in conjunction with DEM to expand and fill in the parameter space for particle-level parameters in a computationally efficient way, providing accurate predictions of segregation in less time. The DEM results are validated by comparing them with experimental data, ensuring their accuracy and reliability. The results show that optimal mixing is achieved when the total filling percent in a system is 36.3% while maintaining an equal proportion of particles. The highest level of mixing occurs at 60 rotations per minute, with fine particles concentrating near the drum’s core and coarser particles distributed around the periphery. The presence of 3–4 baffles optimally enhances mixing performance. Four ML models─linear regression, polynomial regression, support vector regression, and random forest (RF) regression─are trained using data from DEM simulations to predict the segregation index (SI). An error analysis is performed to pick the best model out of the four ML models. The analysis reveals that the RF model accurately predicts the SI. Using the RF model, the SI can be reliably predicted for any value of the seven features studied using DEM. An example 3D surface plot is generated by considering just two (out of 7) of the most important particle level parameters: size and density. The result shows that while both particle size and density contribute to segregation, variations in particle size appear to have a more pronounced effect on the SI compared to particle density.

Background: Qinglian Hongqu decoction (QLHQD), a traditional Chinese herbal remedy, shows potential in alleviating metabolic issues related to nonalcoholic fatty liver disease (NAFLD). However, its precise mode of action remains uncertain. Objective: This study aims to evaluate the efficacy and mechanisms of QLHQD in treating NAFLD. Methods: This study utilized a NAFLD mouse model to assess the effects of QLHQD on lipid metabolism, including blood lipids and hepatic steatosis, as well as glucose metabolism, including blood glucose levels, OGTT results, and serum insulin. Network pharmacology, bioinformatics, and molecular docking were used to explore how QLHQD may improve NAFLD treatment. Key proteins involved in these mechanisms were validated via WB and immunohistochemistry. Additionally, the expression of downstream pathway targets was examined to further validate the insulin resistance mechanism by which QLHQD improves NAFLD. Results: Animal studies demonstrated that QLHQD alleviated lipid abnormalities, hepatic steatosis, blood glucose levels, the insulin resistance index, and the OGTT results in NAFLD mice (P < 0.05 or 0.01). Network pharmacology and bioinformatics analyses indicated that the effects of QLHQD on NAFLD might involve bile acid secretion pathways. Subsequent validation through Western blotting, immunohistochemistry, and qPCR demonstrated that QLHQD may influence fat metabolism and insulin sensitivity in NAFLD mice via the FXR/TGR5/GLP-1 signaling pathway. Conclusion: QLHQD significantly alleviates glucose and lipid metabolism disorders in a high-fat diet-induced NAFLD mouse model. Its mechanism of action may involve the activation of the FXR/TGR5/GLP-1 signaling pathway in the gut, which reduces lipid accumulation and insulin resistance.

The presence of dyes and heavy metals in wastewater represents a significant environmental and public health hazard, necessitating the development of efficient materials for their removal. In this study, we modified hydrolyzed polyacrylonitrile (PAN-H) and combined it with β-cyclodextrin (β-CD) by using an electrostatic spinning technique to fabricate composite nanofibrous membranes for water treatment applications. The resulting PAN-H/β-CD nanofiber membranes exhibit spindle-shaped fibers and porous structures with a high density of charged functional groups, which significantly enhance their selective adsorption capacity compared to pure PAN fibers. Furthermore, post-treatment with a sodium bicarbonate solution further improved this capacity, resulting in the membranes demonstrating a remarkable adsorption efficiency for cationic dyes. The adsorption process conformed to the Langmuir and pseudo-second-order kinetic models, with maximum adsorption capacities of 216.94 mg/g for methylene blue (MB), 471.59 mg/g for malachite green (MG), 299 mg/g for crystal violet (CV), and 43.95 mg/g for copper ions. The selective adsorption of these positively charged contaminants, particularly cationic dyes and metallic copper, indicates that PAN-H/β-CD membranes have significant potential for the treatment of wastewater containing similar pollutants.

Bauxite residue (or red mud) is a highly alkaline waste generated during the extraction of alumina. As a result of the substantial accumulation of bauxite residue in tailings facilities, there is a growing interest in exploring the potential for reusing this material for other purposes. The main objective of this study is to evaluate the use of activated bauxite residue (ABR) for remediating oil sands process-affected water (OSPW) and as a supplement to municipal wastewater treatment through bench-scale, proof-of-concept studies. The ABR is produced through a reduction roasting process that alters the physicochemical properties of bauxite residue, resulting in the generation of potentially effective adsorbent media. The treatment performance via chemical and biological activity removals (cytotoxicity, estrogenicity, and mutagenicity) was also assessed. For OSPW, ABR treatment resulted in the effective removal of recalcitrant acid-extractable organics (AEOs), with kinetics following the pseudo-second-order and comparable adsorption capacity to other waste materials (e.g., petroleum coke). ABR also effectively reduced the estrogenicity and mutagenicity of OSPW, albeit cytotoxicity increased at higher dosages, possibly due to some components leaching out of the material (e.g., metals). For municipal wastewater, ABR treatment reduced fecal coliform concentrations (>99%), total phosphorus (up to 98%), total ammonia-nitrogen (63%), estrogenicity (nondetectable), and mutagenicity (nondetectable), especially in the primary effluent. The ultimate end use of ABR is for the recovery of valuable metals (especially iron) and as a construction material, but additional work is needed to optimize the dosage (currently in the g/L range) and maximize the use of ABR as an adsorbent prior to its subsequent uses.

Here, we report a benchtop scale two-stage polyamidation process for the synthesis of diacid/diamine (AA-BB) type polyamides (PAs) in quantities sufficient (30 g+) to obtain ASTM dogbones, IZOD bars, and rheology specimens with molecular weights ranging from 15 to 35 kDa and minimal to no discoloration. Despite the extensive body of research in recent years reporting biobased AA-BB type PAs, the scale and molecular weights reported by many researchers are often inadequate for meaningful comparisons with industrial resins. Commercially produced PAs usually use an initially high-pressure, moderate-temperature oligomerization reaction to prevent the diacid’s decarboxylation and the diamine’s evaporation. Subsequently, a second stage employs a higher temperature at reduced pressure and inert sweep gas for molecular weight enrichment without significant oxidative degradation. We have sourced commercial hardware and made simple modifications, such as a robust agitator capable of wall-sweeping, to ensure uniform heat and mass transfer. The resulting PAs exhibit mechanical properties on par with industrially sourced controls, demonstrating the effectiveness of our approach in bridging the gap between academic and industrial PAs. This eliminates one of the significant roadblocks associated with developing new industrially relevant polyamides and should be broadly applicable to researchers struggling with the challenges of polyamidation.

Diels–Alder chemistry was exploited to develop a remote-controllable drug release platform on magnetic nanoparticles (MNPs). For this purpose, MNPs were decorated with anionic poly(styrenesulfonic acid-co-furfuryl methacrylate) (poly(SS-co-FMA)) and cationic poly(allylamine hydrochloride) by layer-by-layer assembly. The decorated MNPs successfully underwent DA reaction to produce covalent bonding between FMA (diene) and maleimide (dienophile)-terminated model drug. Thermal treatment above 80 °C caused the retro Diels–Alder reaction (rDA) between FMA and the drug, resulting in drug release. The retro DA could be also achieved by applying an alternating-current (AC) magnetic field to the decorated MNPs. This could spatially limit the heat generation around MNP without heating entire system. Drug release could be also accelerated with the irradiation time when a threshold temperature was met or exceeded the required energy for rDA reaction. Our results highlight the potential of DA chemistry as a new strategy to provide a remote controllable drug release platform for improving the therapeutic efficiency.