Water splitting, the process of converting water into hydrogen and oxygen gases, has garnered significant attention as a promising avenue for sustainable energy production. One area of focus has been the development of efficient and cost-effective catalysts for water splitting. Researchers have explored catalysts based on abundant and inexpensive materials such as nickel, iron, and cobalt, which have demonstrated improved performance and stability. These catalysts show promise for large-scale implementation and offer potential for reducing the reliance on expensive and scarce materials. Another avenue of research involves photoelectrochemical (PEC) cells, which utilize solar energy to drive the water-splitting reaction. Scientists have been working on designing novel materials, including metal oxides and semiconductors, to enhance light absorption and charge separation properties. These advancements in PEC technology aim to maximize the conversion of sunlight into chemical energy. Inspired by natural photosynthesis, artificial photosynthesis approaches have also gained traction. By integrating light-absorbing materials, catalysts, and membranes, these systems aim to mimic the complex processes of natural photosynthesis and produce hydrogen fuel from water. The development of efficient and stable artificial photosynthesis systems holds promise for sustainable and clean energy production. Tandem cells, which combine multiple light-absorbing materials with different bandgaps, have emerged as a strategy to enhance the efficiency of water-splitting systems. By capturing a broader range of the solar spectrum, tandem cells optimize light absorption and improve overall system performance. Lastly, advancements in electrocatalysis have played a critical role in water splitting. Researchers have focused on developing advanced electrocatalysts with high activity, selectivity, and stability for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). These electrocatalysts contribute to overall water-splitting efficiency and pave the way for practical implementation.

Cobalt-ion batteries are considered a promising battery chemistry for renewable energy storage. However, there are indeed challenges associated with co-ion batteries that demonstrate undesirable side reactions due to hydrogen gas production. This study demonstrates the use of a nanocomposite electrolyte that provides stable performance cycling and high Co²⁺ conductivity (approximately 24 mS cm⁻¹). The desirable properties of the nanocomposite material can be attributed to its mechanical strength, which remains at nearly 68 MPa, and its ability to form bonds with H₂O. These findings offer potential solutions to address the challenges of co-dendrite, contributing to the advancement of co-ion batteries as a promising battery chemistry. The exceptional cycling stability of the co-metal anode, even at ultra-high rates, is a significant achievement demonstrated in the study using the nanocomposite electrolyte. The co-metal anode has a 3500-cycle current density of 80 mA cm⁻², which indicates excellent stability and durability. Moreover, the cumulative capacity of 15.6 Ah cm⁻² at a current density of 40 mA cm⁻² highlights the better energy storage capability. This performance is particularly noteworthy for energy storage applications where high capacity and long cycle life are crucial. The H₂O bonding capacity of the component in the nanocomposite electrolyte plays a vital role in reducing surface passivation and hydrogen evolution reactions. By forming strong bonds with H₂O molecules, the polyethyne helps prevent unwanted reactions that can deteriorate battery performance and efficiency. This mitigates issues typically associated with excess H₂O and ion presence in aqueous Co-ion batteries. Furthermore, the high-rate performance with excellent stability and cycling stability performance (>500 cycles at 8 C) of full Co||MnO₂ batteries fabricated with this electrolyte further validates its effectiveness in practical battery configurations. These results indicate the potential of the nanocomposite electrolyte as a valuable and sustainable option, simplifying the development of reliable and efficient energy storage systems and renewable energy applications.

The management of Mediterranean mountains need to know whether or not the flora is adapted to respond to fire and, if so, through what mechanisms. Serpentine outcrops constitute particular ecosystems in the Mediterranean Basin, and plants need to make an additional adaptive effort. The objective of this study is to know the response to fire of the main members of the group of serpentine plants, which habit the Spanish Mediterranean ultramafic mountain, to help in their management. For this purpose, monitoring plots were established on a burned ultramafic outcrop, which was affected by fire in August 2012.They were located in the Mediterranean south of the Iberian Peninsula, Andalusia region. The dominant vegetation of this serpentine ecosystem had been studied previously to fire; it was a shrubland composed of endemic serpentinophytes (small shrubs and perennial herbs) included in Digitali laciniatae-Halimietum atriplicifolii plant association (Cisto-Lavanduletea class) in an opened pine forest. The post-fire response of the plants was studied in the stablished burned plots by field works through permanent 200 x 10 m transect methods, consisting on checking whether they were resprouters, seeders, both of them or if they showed no survival response. Additional information about fire related functional traits is provided for the studied taxa from other studies. Of the total of plants studied (23 taxa), 74% acted as resprouters, 30% as seeders, some of which also had the capacity to resprout (13%), and only 9% of the plants did not show any survival strategy. The presence of a resprouting burl was not high (17%), although serpentine small shrubs such as Bupleurum acutifolium and the generalist Teucrium haenseleri had this kind of organ. The herbaceous taxa Sanguisorba verrucosa, Galium boissieranum and Linum carratracense were seen to be resprouters and seeders. The serpentine obligated Ni-accumulator, Alyssum serpyllifolium subsp. malacitanum, did not show any survival strategy in the face of fire and therefore their populations need monitoring after fires. In the studied ecosystems no species had traits that would protect the aerial part of the plant against fire, although most of the species are capable of post-fire generation by below ground buds. Our results show that the ecosystem studied, composed of taxa with a high degree of endemism and some of them threatened, is predominantly adapted to survival after a fire, although their response capacity may be decreased by environmental factors.

Lead sulfide (PbS) is an important IV-VI semiconductor material with narrow bandwidth and wide wave width, which attracts people's attention. Nano-level PbS has many novel optoelectronic properties and has a wide range of applications in the field of optoelectronics, such as infrared optoelectronic devices, photovoltaic devices, light-emitting devices and display devices. In this paper, Pbs is produced by solvent thermal method by using lead acetate as lead source, sulfur power as sulfur source, ethylene glycol as solvent, and acetic acid to provide acidic environment. The reaction acidity, type of lead source, amount of sulfur source and other aspects will be explored. The products obtained under different conditions were characterized by X-ray diffraction (XRD), optical microscopy and scanning electron microscopy (SEM). The results showed that PbS produced at 140°C for 24 hours, using 14mL ethylene glycol and 1.2mL acetic acid has the best morphology. It has a non-planar six-arm symmetrical structure. Finally, we prepare the lead sulfide composite Ni/PbS, and characterized it.

In this paper, we will provide an extensive analysis of how Generative Artificial Intelligence (GenAI) could be applied when handling Supply Chain Management (SCM). The paper focuses on how GenAI is more relevant in industries, and for instance, SCM where it is employed in tasks such as predicting when machines are due for a check-up, man-robot collaboration, and responsiveness. The study aims to answer two main questions: (1) What prospects can be identified when the tools of GenAI are applied in SCM? Secondly, it aims to examine the following question: (2) what difficulties may be encountered when implementing GenAI in SCM? This paper assesses studies published in academic databases and applies a structured analytical framework to explore GenAI technology in SCM. It looks at how GenAI is deployed within SCM and the challenges that have been encountered, in addition to the ethics. Moreover, this paper also discusses the problems that AI can pose once used in SCM, for instance, the quality of data used, and the ethical concerns that come with, the use of AI in SCM. A grasp of the specifics of how GenAI operates as well as how to implement it successfully in the supply chain is essential in assessing the performance of this relatively new technology as well as prognosticating the future of generation AI in supply chain planning.