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Die Metathese von Ethen mit 2‐Butenen zu Propen ist ein etablierter großtechnischer Prozess. Allerdings sind die Grundlagen der In situ‐Umwandlung von geträgerten WOx‐, MoOx‐ oder ReOx‐Spezies in katalytisch aktive Metallcarbene und deren intrinsische Aktivität sowie die Rolle metatheseinaktiver Cokatalysatoren noch ungeklärt, was sich nachteilig auf die Katalysatorentwicklung und Prozessoptimierung auswirkt. Die Studie liefert die erforderlichen Grundlagen basierend auf steady‐state isotopic transient kinetic analysis. Zum ersten Mal wurden die stationäre Konzentration, die Lebensdauer und die intrinsische Reaktivität von Metallcarbenen bestimmt. Die erhaltenen Ergebnisse können direkt für das Design und die Herstellung von Katalysatoren für die Metathese‐Reaktion und Cokatalysatoren verwendet werden, was die Möglichkeit zur Optimierung der Propenproduktivität eröffnet. [ABSTRACT FROM AUTHOR]

The metathesis of ethylene with 2‐butenes to propene is an established large‐scale process. However, the fundamentals behind in situ transformation of supported WOx, MoOx, or ReOx species into catalytically active metal‐carbenes and the intrinsic activity of the latter as well as the role of metathesis‐inactive cocatalysts are still unsolved. This is detrimental for catalyst development and process optimization. In this study, we provide the required essentials derived from steady‐state isotopic transient kinetic analysis. For the first time, the steady‐state concentration, the lifetime, and the intrinsic reactivity of metal carbenes were determined. The obtained results can be directly used for the design and the preparation of metathesis‐active catalysts and cocatalysts, thereby opening up possibilities for optimizing propene productivity. [ABSTRACT FROM AUTHOR]

The broad application of ultraviolet (UV) photodetectors in civil, astronomical, and military fields has sparked significant research interest. Recently, two-dimensional layered transition metal dichalcogenides have emerged as an ideal platform for developing high-performance and versatile photodetectors due to their abundant intriguing optoelectronic properties. Here, we constructed a photodetector utilizing dual heterojunctions based on rhenium disulfide (ReS2) nanosheet/tungsten disulfide (WS2) nanosheet/p-type gallium nitride (p-GaN) substrate, which incorporate dual built-in electric fields. The built-in electric field at the WS2–p-GaN interface accelerates the separation of photogenerated electrons, enabling a fast photoresponse. Simultaneously, the built-in electric field at the ReS2–WS2 interface not only suppresses dark current but also confines photoexcited holes within the ReS2 layer, ultimately extending the lifetime of photocarriers. Consequently, a photogating effect with high photoconductive gain is achieved. Exploiting these advantages, the ReS2/WS2/p-GaN device exhibits a high responsivity of 3.78 A/W, an outstanding detectivity of 2.1 × 1012 Jones, and a fast rise/decay time of 259/374 μs under 365 nm light with a power density of 0.069 mW/cm2. Furthermore, the device demonstrates its potential for high-resolution UV imaging by functioning as a single pixel, showcasing its capabilities for advanced UV detection and imaging applications. [ABSTRACT FROM AUTHOR]

In the generation process of reinforcement learning decision model, due to the complex environment and incomplete observation of state information, the classical proximal policy optimization algorithm faces problems such as low exploration and utilization efficiency and poor effect of generated strategies, this paper proposes an MNAEK-PPO (proximal policy optimization based on maximum number of arrival & expert knowledge algorithm) based on curiosity mechanism. Focusing on the difficult problem of exploring the strategy space, by constructing the exploration frequency matrix of the agent in the training process, the exploration frequency is treated as an internal reward to participate in the agent's reinforcement learning and training process. In addition, expert knowledge is added to assist the agent in making decisions. Through experiments in the intelligent battlefield simulation environment, the best construction method of internal rewards in MNAEK-PPO is determined, and a series of comparative experiments are carried out. The experimental results show that MNAEK-PPO greatly improves the exploration efficiency of decision space, and the convergence speed and game score are significantly improved, which provides a new solution for promoting the application and development of deep reinforcement learning in the generation of intelligent tactical strategies. [ABSTRACT FROM AUTHOR]

Systematic reviews are vital instruments for researchers to understand broad trends in a field and synthesize evidence on the effectiveness of interventions in addressing specific issues. The quality of a systematic review depends critically on having comprehensively surveyed all relevant literature on the review topic. In addition to database searching, handsearching is an important supplementary technique that helps increase the likelihood of identifying all relevant studies in a literature search. Traditional handsearching requires reviewers to manually browse through a curated list of field‐specific journals and conference proceedings to find articles relevant to the review topic. This manual process is not only time‐consuming, laborious, costly, and error‐prone due to human fatigue, but it also lacks replicability due to its cumbersome manual nature. To address these issues, this paper presents a free and open‐source Python package and an accompanying web‐app, Paperfetcher, to automate the retrieval of article metadata for handsearching. With Paperfetcher's assistance, researchers can retrieve article metadata from designated journals within a specified time frame in just a few clicks. In addition to handsearching, it also incorporates a beta version of citation searching in both forward and backward directions. Paperfetcher has an easy‐to‐use interface, which allows researchers to download the metadata of retrieved studies as a list of DOIs or as an RIS file to facilitate seamless import into systematic review screening software. To the best of our knowledge, Paperfetcher is the first tool to automate handsearching with high usability and a multi‐disciplinary focus. [ABSTRACT FROM AUTHOR]