Two-dimensional (2D) perovskites have emerged as promising optoelectronic materials. However, their practical and rational design is hindered by poor understanding of the relationship between the screening environment and excitonic properties. In a new study, researchers developed a new method to isolate the effects of the screening environment, offering a new predictive model for excitonic properties of 2D perovskites. This will contribute to more stable and tunable optoelectronic technologies.

Researchers at the Karlsruhe Institute of Technology (KIT) have found out how plant cells respond to stress. If their energy supply is disrupted by heat, drought, or saline soils, chloroplasts – the cells’ powerhouses – send an intracellular distress signal by forming tiny, finger-like projections. This signal specifically activates protection programs, which help to limit damage. The results of the study clearly show for the first time what the function of these previously mysterious structures is, and present an approach for making crops more resilient to climate stress.Researchers at the Karlsruhe Institute of Technology (KIT) have found out how plant cells respond to stress. If their energy supply is disrupted by heat, drought, or saline soils, chloroplasts – the cells’ powerhouses – send an intracellular distress signal by forming tiny, finger-like projections. This signal specifically activates protection programs, which help to limit damage. The results of the study clearly show for the first time what the function of these previously mysterious structures is, and present an approach for making crops more resilient to climate stress.

Osaka Metropolitan University researchers developed a silica capsule–based technology that enables easy separation and reuse of colorants from plastics, overcoming limitations of conventional recycling. This approach allows repeated upcycling into high-quality, vividly colored materials with significantly lower energy consumption.

The ongoing evolution of software defect detection methodologies leveraging large language models is rapid; however, the current research landscape has not been adequately investigated. Existing reviews inclusively categorize smaller language models as LLMs, failing to concentrate specifically on the domain of software defect detection and omitting recent advancements in the field. This highlights a gap in the detailed analysis and assessment of cutting-edge applications of large language models in detecting software flaws.

The quality control issue has always been the focus of Crowdsourcing research. However, existing surveys predominantly concentrate on quality control in Boolean tasks, which are generally formulated as simple label classification, ranking, or numerical prediction. Ubiquitous open-ended tasks like question-answering, translation, and semantic segmentation have not been sufficiently discussed due to several challenges, like large to infinite answer spaces, complex task structure, dynamic and multidimensional worker abilities and non-unique acceptable answers.