ACS Materials Au最新文献

To solve the bioavailability of nonsteroidal anti-inflammatory drugs and reduce their clinical risks, this study combined density functional theory (DFT) calculations with experiments and investigated the mechanism of in vitro transdermal absorption of choline ketoprofen gel and the pharmacokinetics of choline ketoprofen in rats. High-performance liquid chromatography (HPLC) was used to analyze the in vitro transdermal effect of ketoprofen in rats and the concentration of ketoprofen in the plasma of rats, which were administered choline ketoprofen by gavage. After the transdermal treatment, the rat skin was subjected to Hematoxylin and Eosin (H&E) staining and observe changes in skin structure. The results indicate that choline ketoprofen gel is superior to ketoprofen gel in terms of transdermal ability. Its transdermal rate is 1.4-2.2 times that of ketoprofen gel. The results show that the interaction force between choline ketoprofen and phospholipids is approximately 2.5 times that between ketoprofen and phospholipids, causing edema in epidermal cells and the dermis, which enlarges the intercellular space and then enhances the transdermal absorption capacity of ketoprofen. Compared with the ketoprofen suspension, the peak concentration of ketoprofen increased from 7.708 to 39.495 mg·L^-1 (p < 0.05) for ketoprofen choline, and the relative bioavailability was 479.86%. It can be seen that the drug ionic liquid pathway can improve the absorption of drugs by the body and can better exhibit the dual functions of ionic liquids (penetration enhancers, surfactants, etc.) and drugs. These preliminary research results can lay the foundation for in-depth research on ketoprofen ionic liquid gels.

Current infrared sensing devices are based on costly materials with relatively few viable alternatives known. To identify promising candidate materials for infrared photodetection, we have developed a high-throughput screening methodology based on high-accuracy r²SCAN and HSE calculations in density functional theory. Using this method, we identify ten already synthesized materials between the inverse perovskite family, the barium silver pnictide family, the alkaline pnictide family, and ZnSnAs₂ as top candidates. Among these, ZnSnAs₂ emerges as the most promising candidate due to its experimentally verified band gap of 0.74 eV at 0 K and its cost-effective synthesis through Bridgman growth. BaAgP also shows potential with an HSE-calculated band gap of 0.64 eV, although further experimental validation is required. Lastly, we discover an additional material, Ca₃BiP, which has not been previously synthesized, but exhibits a promising optical spectra and a band gap of 0.56 eV. The method applied in this work is sufficiently general to screen wider bandgap materials in high-throughput and now extended to narrow-band gap materials.

The rational exploration and design of high-performance, stable electrocatalysts are crucial for efficient renewable energy storage, conversion, and utilization. Artificial intelligence (AI) is revolutionizing this field by significantly reducing the time and cost associated with conventional trial-and-error experimentation and density functional theory (DFT) calculations. Advancements in data quality, computing power, and algorithms have positioned AI as a key enabler in understanding electrocatalytic mechanisms, designing advanced materials, analyzing structures, and predicting performance. This review highlights the pivotal role of AI in electrocatalyst discovery, focusing on the critical aspects of data, descriptors, and machine learning models. We discuss various AI approaches, including their applications in accelerating DFT calculations, exploring reaction mechanisms, designing electrocatalysts, and predicting performance, providing a comprehensive overview of the current state-of-the-art. We also address the challenges and opportunities in leveraging AI for electrocatalyst development, emphasizing the importance of data quality, model selection, and collaborative research. This review aims to guide researchers in effectively utilizing AI to accelerate the discovery and optimization of electrocatalysts for a renewable energy future.

Ge_1-x-y Si _y Sn _x quantum dots (QDs) are an attractive class of low-to-nontoxic and earth-abundant semiconductors exhibiting size and composition-tunable optical properties. Their electronic structure can be modified by varying elemental composition and quantum confinement to achieve tunable absorption and photoluminescence (PL) across the visible to near-IR spectrum. Alloying with Sn enhances oscillator strengths, whereas decreasing size and incorporating Si increase energy gaps. Herein, we report a facile colloidal route to produce Ge_1-x-y Si _y Sn _x QDs with narrow size dispersity (4.0 ± 0.4 - 5.2 ± 0.6 nm) and variable Si (y = 0.030 - 0.252) and Sn (x = 0.044 - 0.059) compositions and investigate the influence of core/surface species on optical properties. Structural analysis reveals an expanded diamond cubic Ge lattice, a red-shifted Ge-Ge Raman peak, and the emergence of a Ge-Si peak with increasing Si composition. Successful alloying of Si and Sn into Ge host lattice is confirmed by electron microscopy, suggesting homogeneous solid solution behavior of ternary QDs. Surface analysis further indicates the presence of Ge⁰/Si⁰/Sn⁰ core species alongside charged Ge ⁿ⁺/Si ⁿ⁺/Sn ⁿ⁺ (1 ≤ n ≥ 4) surface species coordinated to passivating organic ligands. The effects of confinement and surface/core elemental composition on optical properties were revealed through composition-tunable absorption onsets (1.15 - 2.33 eV) and associated Tauc direct (1.86 - 3.03 eV) and indirect (1.01 - 1.81 eV) energy gaps achieved for QDs with x = 0.044 - 0.059 and y = 0.030 - 0.252, which are prominently blue-shifted from bulk counterparts and previously reported Ge_1-x Sn _x QDs. PL spectra of Ge_1-x-y Si _y Sn _x QDs exhibit nanosecond-scale emission from 1.84 - 1.88 eV for y ≤ 0.134 and 2.32 - 2.43 eV for y ≥ 0.177 compositions, displaying similarly pronounced blueshifts from comparable Ge_1-x Sn _x QDs. This correlated absorption/PL tunability expands upon that demonstrated by Ge and Ge_1-x Sn _x counterparts widens the optical window of Group IV semiconductor nanostructures, making them attractive for visible-to-near-IR optoelectronic studies.

IrO₂ is one of the most widely investigated electrocatalysts for oxygen evolution reaction in an acidic environment. Increasing the mass activity is an effective way of decreasing the loading of Ir, to ultimately reduce costs. Here, we demonstrate the crystal-phase engineering of two different potassium iridate polymorphs obtained by designing a selective solid-state synthesis of either one-dimensional K_0.25IrO₂ nanowires with a hollandite crystal structure or two-dimensional KIrO₂ hexagonal platelets. Both structures present increased specific and mass electrocatalytic activities for the water oxidation reaction in acidic media compared to commercial rutile IrO₂ of up to 40%, with the 1D nanowires outperforming the 2D platelets. XANES, extended X-ray absorption fine structure, and X-ray diffraction investigations prove the structural stability of these two different allotropes of KxIrO₂ compounds upon electrocatalytic testing. These low-dimensional nanostructured 1D and 2D KxIrO₂ compounds with superior mass activity to commercial IrO₂ can pave the way toward the design of new electrocatalyst architectures with reduced Ir loading content for proton exchange membrane water electrolyzer (PEMWE) anodes.

This study aimed to develop a bifunctional nanomaterial that could simultaneously adsorb zoledronic acid (ZA) and release geranylgeraniol (GGOH) to reverse ZA-induced cytotoxicity. The synthesized aluminum-doped mesoporous silica nanomaterial (AM) was subsequently amine-functionalized by 3-aminopropyltriethoxysilane, generating both amine- and aluminum-containing nanomaterial (NAM), to enhance the ability of nanoparticles to adsorb GGOH. The comprehensive characterization results confirmed the successful aluminum-doping and amine-functionalization of the nanoparticles. The results acquired from both thermogravimetric analysis and high-performance liquid chromatography demonstrated that NAM, rather than AM, served as a good nanocarrier for GGOH loading and controlled-releasing. NAM exhibited up to 12.48% GGOH loading efficiency and GGOH sustained release for over 10 days with a release profile best fitted by the Higuchi model (R ² = 0.9868), indicating a diffusion-controlled mechanism. Although AM demonstrated much higher ZA adsorption (>95%), NAM still retained moderate ZA adsorption (∼30%). In vitro assays using RAW 264.7 murine cells revealed that GGOH-loaded NAM was noncytotoxic and completely reversed ZA-induced cytotoxicity and metabolic impairment. Furthermore, it displayed negligible hemolytic activity (<0.5%). The combination of targeted drug delivery and bisphosphonate sequestration via nanostructured silica nanocarriers presents a promising therapeutic approach with translational potential in the prevention of medication-related osteonecrosis of the jaw. The promising cellular results, serving as a preclinical foundation, provide a stepping stone toward in vivo applications.

Calcium carbonate vaterite crystals have attracted increasing attention as sacrificial templates for forming polymer microgels. Vaterite's porous structure, biocompatibility, and eco-friendly synthesis make it ideal for biomedical applications. In this study, vaterite is grown on the surface, and surface-supported (ss)-microgels are formed by coating it with alternating layers of polyelectrolytes, sodium alginate (ALG), and poly-l-lysine (PLL), followed by core dissolution. Pre-loading (during vaterite synthesis) and post-loading (after microgel formation) of macromolecules are compared using dextran and its charged derivatives. Pre-loading proved to be more efficient, achieving up to 9% w/w encapsulation. Dextran adsorption follows the Langmuir model (ΔG = - 31.0 kJ/mol), while its derivatives follow the Freundlich model (1/n = 0.7-0.8), indicating intermolecular repulsion. Post-loading resulted in encapsulation levels below 1% w/w and exhibited pH-independent behavior. The microgels remained stable in acidic environments, but PLL degradation via trypsin enabled the sustained release of dextran. These findings clarify the mechanisms of macromolecular adsorption on ss-vaterite, highlight the importance of considering the loading strategy when designing microgels for specific applications, and support the use of ss-microgels for therapeutic delivery.

Three-dimensional (3D) covalent organic frameworks (COFs) with high connectivity provide structurally rigid yet finely tunable scaffolds that enable precise enzyme immobilization by offering well-defined binding sites and framework stabilitykey to balancing substrate accessibility with enzyme protection, both critical for efficient biocatalysis. In this work, we investigate the effects of enzyme localizationsurface anchoring versus pore entrapmenton catalytic performance by employing two structurally distinct 3D COFs, TUS-39 and TUS-64, as host matrices. We herein report the designed synthesis of TUS-39, a new (8,3)-connected COF featuring the topology and microporous structure (0.9 nm) through dynamic imine condensation between a D _2h-symmetric tetragonal prism node and a D _3h-symmetric planar triangular linker. This architecture enabled efficient surface anchoring of amano lipase PS, resulting in remarkably high catalytic activity and reusability in the kinetic resolution of racemic (R,S)-1-phenylethanol via transesterification. In contrast, the mesoporous (4.7 nm) COF TUS-64 facilitated encapsulation of the enzyme within its pore channels, affording enhanced stability under harsh chemical and thermal environments. The comparative study reveals that surface immobilization on the tightly connected microporous network of TUS-39 enhances substrate accessibility and catalytic conversion rate, while the internal confinement within the larger mesopores of TUS-64 protects the biocatalyst from denaturation and degradation, albeit with a modest trade-off in catalytic efficiency. These findings underscore the critical interplay between surface characteristics, pore metrics, and enzyme localization in dictating the overall efficiency, resilience, and recyclability of COF-supported biocatalysts.

Over the past century, a growing body of work has demonstrated that cellular behavior is impacted by contact with the materials in the surrounding environment, at length scales from centimeters down to nanometers. Soft matter (such as native extracellular matrices) has historically been challenging to pattern with great precision, so early efforts to understand structured cell-material interactions in the 1990s took advantage of hard interfaces, leveraging fabrication methods developed for the electronics industry throughout the 60s and 70s. Ultimately, as it became clear that cells respond to not only topography and chemistry of their environment, but also mechanical properties, patterning methods have been extended to soft materials, although often with lower structural resolution. Here, we provide a historical overview of the development of structured cell scaffold interfaces, highlighting the potential for additional advances in material patterning translated from hard to soft matter.

The burgeoning field of 4D fabrication holds transformative potential in fabricating dynamic, tubular structures such as artificial vascular grafts, stents, and nerve conduits. These are critical for cardiovascular, respiratory, and neurological applications. Traditional 3D printing, despite its advances, remains constrained by the static nature of its structures, often resulting in challenges such as improper vascular integration, restricted endothelialisation in small-diameter grafts, and complex surgical deployment requirements. This perspective delves into the novel integration of stimuli-responsive smart materials that imbue printed structures with the ability to morph, repair, and adapt to specific environmental stimuli, facilitating a more biocompatible and physiologically relevant interface. Highlighting recent breakthroughs in vascular graft fabrication, we discuss the strategic use of multimaterial printing to achieve endothelial compatibility and structural fidelity. Moreover, advancements in bifurcated stents and multichannel nerve conduits underscore the role of self-assembling and self-folding mechanisms in addressing anatomical and biomechanical complexities inherent in regenerative medicine. However, the translational trajectory of 4D bioprinting is impeded by persistent issues like material scalability, stimulus precision control, mechanical stability, and stringent biocompatibility standards. Future research should prioritize the refinement of multifunctional biomaterials and the development of composite, stimuli-responsive scaffolds equipped with biosensor functionalities to better mimic the dynamic biomechanics of native tissues. This review provides an in-depth analysis of these challenges and explores pathways toward the clinical adoption of 4D-printed, biomimetic tubular structures, aiming to bridge the gap between experimental innovation and clinical application.