High-entropy effect with hollow (ZnCdFeMnCu)xS nanocubes for photoelectrochemical immunoassay

A novel ratiometric electrochemical aptasensor based on graphene quantum dots/Cu-MOF nanocomposite for the on-site determination of Staphylococcus aureus

The sensitive detection of Staphylococcus aureus (S. aureus) holds great practical importance for ensuring public health and food safety. In this study, a sensitivity and stability ratiometric electrochemical aptasensor using graphene quantum dots/[Cu2.5 (benzotriazole-5-COO)1.5 (benzotriazole-5-COOH)0.5 (μ-Cl)0.5 (μ3-OH)-(H2O)]·3 H2O nanocomposite (GQDs/Cu-MOF) was constructed for S. aureus detection. The GQDs enhanced the sensitivity of the electrochemical aptasensor due to their excellent conductivity and provided stability through their abundant carboxyl groups. The Cu-MOF, possessing electrical activity, not only enhanced the performance of the electrochemical aptasensor but also served as a signal label. The single-stranded DNA1 (S1) was immobilized on the surface of a GQDs/Cu-MOF/screen-printed carbon electrode (S1/GQDs/Cu-MOF/SPCE) as the sensing interface. Subsequently, the S1/GQDs/Cu-MOF/SPCE was hybridized with the probe DNA-ferrocene (S2-Fc), resulting in the generation of electrochemical signals from Cu-MOF (ICu-MOF) and S2-ferrocene (IS2-FC) within the system. However, the electron transfer performance of DNA at the sensing interface was compromised, leading to a reduction in the ICu-MOF. When S. aureus was present in the system, S2-Fc reacted with it and detached from the sensing surface, resulting in a gradual decrease in IS2-FC and an increase in ICu-MOF. Then a ratiometric electrochemical aptasensor was established for S. aureus detection with remarkable sensitivity (0.97 CFU·mL-1), excellent stability, and a broad linear range. Furthermore, the aptasensor was successfully applied to detect S. aureus in tap water, milk, Lonicera japonica, urine, and Zhangjiang River. Additionally, this aptasensor design can be adapted for the detection of other foodborne pathogens, which indicates that the design scheme of the aptasensor has good universality.

Synthesis Strategies for High Entropy Nanoparticles

Nanoparticles (NPs) of high entropy materials (HEMs) have attracted significant attention due to their versatility and wide range of applications. HEM NPs can be synthesized by fragmenting bulk HEMs or disintegrating and recrystallizing them. Alternatively, directly producing HEMs in NP form from atomic/ionic/molecular precursors presents a significant challenge. A widely adopted strategy involves thermodynamically driving HEM NP formation by leveraging the entropic contribution but incorporating strategies to limit NP growth at the elevated temperatures used for maximizing entropy. A second approach is to kinetically drive HEM NP formation by promoting rapid reactions of homogeneous reactant mixtures or using highly diluted precursor dissolutions. Additionally, experimental evidence suggests that enthalpy plays a significant role in driving HEM NP formation processes at moderate temperatures, with the high energy cost of generating additional surfaces and interfaces at the nanoscale stabilizing the HEM phase. This review critically assesses the various synthesis strategies developed for HEM NP preparation, highlighting key illustrative examples and offering insights into the underlying formation mechanisms. Such insights are critical for fine-tuning experimental conditions to achieve specific outcomes, ultimately enabling the effective synthesis of optimized generations of these advanced materials for both current and emerging applications across various scientific and technological fields.

High-Entropy Materials for Prospective Biomedical Applications: Challenges and Opportunities

With their unique structural characteristics, customizable chemical composition, and adjustable functional characteristics, high-entropy materials (HEMs) have triggered a wide range of interdisciplinary research, especially in the biomedical field. In this paper, the basic concept, core properties, and preparation methods of HEMs are first summarized, and then the application and development of HEMs in the field of biomedical are briefly described. Subsequently, based on the diverse and comprehensive properties of HEMs and a few reported cases, the possible application scenarios of HEMs in biological fields such as biosensors, antibacterial materials, therapeutics, bioimaging, and tissue engineering are prospectively predicted and discussed. Finally, their potential advantages and major challenges is summarized, which may provide useful guidance and principles for researchers to develop and optimize novel HEMs.

Materials Containing Single-, Di-, Tri-, and Multi-Metal Atoms Bonded to C, N, S, P, B, and O Species as Advanced Catalysts for Energy, Sensor, and Biomedical Applications

Modifying the coordination or local environments of single-, di-, tri-, and multi-metal atom (SMA/DMA/TMA/MMA)-based materials is one of the best strategies for increasing the catalytic activities, selectivity, and long-term durability of these materials. Advanced sheet materials supported by metal atom-based materials have become a critical topic in the fields of renewable energy conversion systems, storage devices, sensors, and biomedicine owing to the maximum atom utilization efficiency, precisely located metal centers, specific electron configurations, unique reactivity, and precise chemical tunability. Several sheet materials offer excellent support for metal atom-based materials and are attractive for applications in energy, sensors, and medical research, such as in oxygen reduction, oxygen production, hydrogen generation, fuel production, selective chemical detection, and enzymatic reactions. The strong metal-metal and metal-carbon with metal-heteroatom (i.e., N, S, P, B, and O) bonds stabilize and optimize the electronic structures of the metal atoms due to strong interfacial interactions, yielding excellent catalytic activities. These materials provide excellent models for understanding the fundamental problems with multistep chemical reactions. This review summarizes the substrate structure-activity relationship of metal atom-based materials with different active sites based on experimental and theoretical data. Additionally, the new synthesis procedures, physicochemical characterizations, and energy and biomedical applications are discussed. Finally, the remaining challenges in developing efficient SMA/DMA/TMA/MMA-based materials are presented.

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand

Exploring the potential of new models for mapping groundwater quality presents a major challenge in water resource management, particularly in Kanchanaburi Province, Thailand, where groundwater faces contamination risks. This study aimed to explore the applicability of random forest (RF) and artificial neural networks (ANN) models to predict groundwater quality. Particularly, these two models were integrated into cross-validation (CV) and bootstrapping (B) techniques to build predictive models, including RF-CV, RF-B, ANN-CV, and ANN-B. Entropy groundwater quality index (EWQI) was converted to normalized EWQI which was then classified into five levels from very poor to very good. A total of twelve physicochemical parameters from 180 groundwater wells, including potassium, sodium, calcium, magnesium, chloride, sulfate, bicarbonate, nitrate, pH, electrical conductivity, total dissolved solids, and total hardness, were investigated to decipher groundwater quality in the eastern part of Kanchanaburi Province, Thailand. Our results indicated that groundwater quality in the study area was primarily polluted by calcium, magnesium, and bicarbonate and that the RF-CV model (RMSE = 0.06, R2 = 0.87, MAE = 0.04) outperformed the RF-B (RMSE = 0.07, R2 = 0.80, MAE = 0.04), ANN-CV (RMSE = 0.09, R2 = 0.70, MAE = 0.06), and ANN-B (RMSE = 0.10, R2 = 0.67, MAE = 0.06). Our findings highlight the superiority of the RF models over the ANN models based on the CV and B techniques. In addition, the role of groundwater parameters to the normalized EWQI in various machine learning models was found. The groundwater quality map created by the RF-CV model can be applied to orient groundwater use.

Dendritic quinary PtRhMoCoFe high-entropy alloy as a robust immunosensing nanoplatform for ultrasensitive detection of biomarker

Recently, high-entropy alloys have superior physicochemical properties as compared to conventional alloys for their glamorous "cocktail effect". Nevertheless, they are scarcely applied to electrochemical immunoassays until now. Herein, uniform PtRhMoCoFe high-entropy alloyed nanodendrites (HEANDs) were synthesized by a wet-chemical co-reduction method, where glucose and oleylamine behaved as the co-reducing agents. Then, a series of characterizations were conducted to illustrate the synergistic effect among multiple metals and fascinating structural characteristics of PtRhMoCoFe HEANDs. The obtained high-entropy alloy was adopted to build a electrochemical label-free biosensor for ultrasensitive bioassay of biomarker cTnI. In the optimized analytical system, the resultant sensor exhibited a dynamic linear range of 0.0001-200 ng mL-1 and a low detection limit of 0.0095 pg mL-1 (S/N = 3). Eventually, this sensing platform was further explored in serum samples with satisfied recovery (102.0 %). This research renders some constructive insights for synthesis of high-entropy alloys and their expanded applications in bioassays and bio-devices.

Self-assembled p-n Ag2O@Bi2O2S nanoflower heterojunctions for sensitive photoelectrochemical immunoassay

A new photoelectrochemical immunoassay based on self-assembled p-n Ag2O@Bi2O2S nanoflower heterojunction was designed and developed for quantitative monitoring of prostate-specific antigen (PSA) in biological fluids. Primarily, self-assembled p-n Ag2O@Bi2O2S nanoflower heterojunctions were served as the photoactive materials and coated onto the surface of electrodes. Subsequently, the glucose oxidase (GOx) was bound to the detection antibody (mAb2) labeled gold nanoparticles (Au NPs) and then were employed to accomplish a sandwich-like immunoreaction to generate H2O2 on a microplate incubated with monoclonal anti-PSA antibodies. In the presence of PSA, the product (H2O2) was catalyzed by the substrate, which was used as an electron sacrificial agent to improve signal conversion and capture of photogenerated electrons. Under optimum conditions, a wide linear range of 0.01-50 ng mL-1 and a low detection limit of 5.3 pg mL-1 were accomplished with the sensor, exhibiting an excellent photocurrent response. Moreover, the proposed sensor revealed satisfactory reproducibility, high selectivity, and acceptable accuracy for the real sample testing. Importantly, our work provides a novel strategy for high sensitivity detection of disease-associated biomarkers for the early diagnosis of cancers.