During many life processes such as replication, transcription, double-strand breaks repair and so on, double-stranded DNA will temporarily unwind and form single strand DNA (ssDNA). ssDNA may affect genomic stability and may also participate in the formation of non-B DNA structure, which in turn regulates and influences many key cellular processes. This review briefly describes the causes of the formation of single-stranded DNA, the structures containing single-stranded DNA and their possible functions in cells, and summarizes some high-throughput analysis techniques of single-stranded DNA, which provides the method inspiration for the subsequent ssDNA research and promotes the further development of ssDNA analysis techniques and methods.

In recent years, electrocatalytic nitrate reduction (ENitRR) has attracted considerable attention in the synthesis of ammonia at ambient conditions. Compared to the traditional Haber-Bosch process for ammonia synthesis, ENitRR offers lower energy consumption and milder reaction conditions. The design and optimization of ENitRR electrocatalysts are crucial for nitrate deoxygenation and hydrogenation. Copper-based catalytic materials have been widely studied due to their unique structure, low cost, and excellent performance, making them highly promising electrocatalysts through various morphology and electronic structure modulation strategies. This article summarizes various effective design strategies using copper-based electrocatalysts as a typical example to enhance the ammonia production rate and conversion efficiency in ENitRR. It also introduces the reaction mechanism and the relationship between structural changes in Cu-based electrocatalysts and their performance. These strategies include morphology modulation, alloy engineering, lattice phase tuning, single-atom structures, as well as copper compound construction and composites with other materials. Finally, challenges faced by copper-based electrocatalysts are discussed along with future research directions that should be focused on in order to provide reference for researchers engaged in nitrate treatment in aqueous systems.

Layered transition metal oxides (LiTMO₂) are candidate cathode materials for high-energy-density lithium-ion batteries, primarily owing to their high theoretical specific capacity. Nevertheless, the persistent challenge of chemical-mechanical failure during charge-discharge cycling has impeded its progressive development. In numerous prior investigations, researchers have diligently explored the cycling failure of this material family, presenting a spectrum of modification strategies aimed at addressing this issue including doping, coating, surface or grain boundary modification. Given the impact of lattice defects and heterogeneous structures introduced throughout the synthesis process cannot be overlooked, a comprehensive comprehension of the influence exerted by various controlling factors on the structural formation of materials is imperative. This review aims to elucidate the ramifications of control factors, including precursor, lithium salt, sintering temperature, holding time, and sintering atmosphere, on the material structure during the synthesis process. The objective is to provide the battery community with valuable insights on strategies to synthesize high-performance LiTMO₂ materials.

In recent years, there has been significant progress in non-fullerene organic solar cells (NF-OSCs) due to the rapid development of narrow-bandgap small-molecule acceptor materials and the high-performance polymer donor materials, with the power conversion efficiency (PCE) approaching 20%. However, as the design of alternating D-A copolymer materials reaches saturation, there is an urgent need to develop more efficient conjugated polymer materials. The ternary random strategy has emerged to address this challenge. The advantages of the ternary random copolymerization, including easy energy level tuning, broad and strong absorption, and high molar absorptivity, which have attracted considerable attention in the field of organic solar cells. In this review, firstly, the advantages of the ternary random copolymerization strategy in modulating polymer properties and device performance are discussed. Through this strategy, the active layer morphology can be effectively regulated and optimized, and thus the charge transfer efficiency can be improved leading to the improved PCE. Furthermore, the application of the ternary random copolymerization into NF-OSCs is summarized from the perspectives of random polymer donors and acceptors. Finally, a summary and outlook of the further development of random polymers are presented. As expected, to understand the design concept and advantages of ternary random strategy would be beneficial for the development of organic solar cells.

MXene is a two-dimensional transition metal carbon/nitrogen compound or carbon-nitrogen compound obtained from MAX phase materials by chemical etching followed by ultrasonic or intercalation treatment. It has the properties of two-dimensional atomic layer structure, abundant components, metallic conductivity, large specific surface area and active surface, etc. It has distinct infrared absorption in the near-infrared and mid\far-infrared bands, and has attracted extensive attention from researchers in recent years in a number of infrared applications, such as infrared camouflage, photothermal conversion, and photovoltaic effect. In this paper, the properties of MXene materials in the infrared band are reviewed in detail, including the high absorbance and localized surface plasmon resonance effect in the near-infrared band and the infrared low-emission properties in the mid/far-infrared band. Further based on its infrared properties, the research progress of its applications in popular fields such as infrared camouflage, broadband absorber, passive radiant heating, photothermal conversion and photovoltaic effect is summarized. Finally, the main problems of the current research on MXene materials in the infrared field and the future development direction are prospected.

The rapid development of infrared detection equipment has caused a huge threat to military equipment. And infrared stealth technology is an important way to improve the survival, strike and breakthrough capabilities of military equipment, and plays a vital role in the development of the national defense industry. However, the battlefield environment is complex and changeable, and materials with only infrared stealth performance are difficult to meet the actual needs when facing radar detection, rainforest, mountain, ocean, desert and other environments. Therefore, it is imperative to develop multifunctional infrared stealth materials. In this paper, the latest research progress of different infrared stealth materials is reviewed from the perspective of the mechanism of infrared stealth materials, such as low emissivity materials, temperature control materials, variable emissivity materials and cooperative working mode materials, and the control methods of different infrared stealth materials are discussed. Secondly, the multi-functional infrared stealth materials suitable for different application scenarios, such as multi-band stealth, electromagnetic shielding, antibacterial and waterproof, high temperature resistance, anti-corrosion and flame retardant infrared stealth materials, and their design mechanisms are discussed. Finally, the future development of multifunctional infrared stealth materials is summarized and prospected.

Pharmaceuticals and personal care products (PPCPs) are a large category of emerging pollutants that have been highly concern in recent years. The huge production and rapid consumption demand of PPCPs make them widely enter and highly exist in various environmental mediums. Due to migration, transformation and bioaccumulation, PPCPs enter the ecological environment, causing different degrees of negative impact on organisms and human bodies, thus bringing serious threats to the ecological environment and human health. In this review, we summarize the exposure sources, pathways and characteristics of current PPCPs in the environment, conclude the degradation method and pathway of PPCPs in the environment, review the main biotoxicity of PPCPs, overview the exposure concentrations and the health influences on the human body, and finally have some outlooks on the research field of ecotoxicity of PPCPs.

With the continuous development of flexible electronic devices in recent years, flexible wearable sensors show great potential for development in the fields of human health monitoring, electronic skin, and intelligent machines. Biomass materials, as a kind of renewable resource derived from living organisms with excellent characteristics such as inexpensive, green and, eco-friendly, skin-friendly and breathable, and good biocompatibility, have been heavily studied as the matrix of wearable, flexible sensors. Biomass-based sensors can be ideal for use in the field of human health monitoring because they combine the excellent properties of biomass materials with sensing elements. This paper first reviews the structure, composition and working principle of common flexible sensors (strain, pressure, temperature, biological). And then, the characteristics of different biomass-based sensors and their applications are described in detail. The biomass materials involved mainly include collagen, gelatine, cellulose, chitosan, sodium alginate, and silk protein. In addition, the applications of biomass-based sensors in human health monitoring (including physical signals, chemical signals, bioelectrical signals and thermal signals monitoring) are summarised. Finally, the challenges and future directions of biomass-based sensors and their applications in the field of human health monitoring are pointed out in light of the current status of the applications they are currently facing.

Interfering with bacterial iron metabolism is a non-antibiotic antibacterial strategy that is not easy to cause bacterial resistance. In this review, firstly, an iron-blocking antibacterial therapy which can kill drug-resistant bacteria but not easily cause drug resistance is introduced. Then, the mechanism of iron-blocking antibacterial therapy is explained from the iron uptake pathway and heme uptake pathway of bacteria. In addition, the types, in vitro antibacterial properties, and in vivo therapeutic effects of the iron blocking antimicrobials based on gallium salts and gallium porphyrins are reviewed in detail. Finally, the future development and practical application of the antimicrobials based on iron-blocking mechanism are prospected.

Atmospheric deposition of desert dust aerosol is a major source of key nutrients for surface seawater in open oceans, significantly impacting marine biogeochemistry and primary productivity. As a tracer for desert dust aerosol, aluminum (Al) is widely used to estimate deposition fluxes of desert dust aerosol into the oceans, and dissolved Al concentrations in surface seawater and aerosol particles are key parameters for using this method to estimate desert dust deposition fluxes into the oceans. In this paper, we first review separation, extraction and detection methods used to measure dissolved Al in seawater and aerosol samples, and discuss their principles, advantages, limitations and applicability. After advances in aerosol Al solubility are systematically reviewed, we point out that the uncertainties in aerosol Al solubility are the bottleneck which currently limits accurate estimations of desert dust deposition fluxes into the oceans, and further analyze the sources of these uncertainties. In the final, we also outline research directions for dissolved Al analysis and aerosol Al solubility research.

The risk of algal blooms has significantly increased in eutrophic lakes and reservoirs due to the global climate change and anthropogenic pollution, which has a significant impact on the safety and stability of municipal water supplies. To protect source water, it is necessary to construct a mathematical model and alert system to predict algae concentration in lakes and reservoirs. This paper reviews the main environmental factors (physical, chemical, and biological) that affect the algae growth, and summarizes the principles and application scenarios of existing models. Prediction models can generally be divided into two categories: process-based models (PB models) and data-driven models (DD models). PB models are based on natural processes, which enhances their interpretability and generality. However, they require a high level of research and testing, which can be costly. DD models rely on artificial intelligence methods such as machine learning, which offer flexible and diverse modeling approaches. However, they depend on data quality, lack mechanism support, and are location-specific. Both models have been extensively studied in the past decades and have been applied in some lakes and reservoirs. To further improve model performance, future research should improve the frequency and quality of data monitoring and combine natural process mechanisms with artificial intelligence methods.