variational principle for weighted amenable topological pressure

Following the approach of Tsukamoto[\emph{Ergodic Theory Dynam. Syst.} \textbf{43} (2023), 1004-1034.], we introduce the notion of weighted amenable topological pressure for factor maps between dynamical systems of amenable group actions, and established a variational principle for it

Exceptionally Long-Lived Charge Separated State in Zeolitic Imidazolate Framework: Implication for Photocatalytic Applications

Zeolitic imidazolate frameworks (ZIFs) have emerged as a novel class of porous metal–organic frameworks (MOFs) for catalysis application because of their exceptional thermal and chemical stability. Inspired by the broad absorption of ZIF-67 in UV–vis-near IR region, we explored its excited state and charge separation dynamics, properties essential for photocatalytic applications, using optical (OTA) and X-ray transient absorption (XTA) spectroscopy. OTA results show that an exceptionally long-lived excited state is formed after photoexcitation. This long-lived excited state was confirmed to be the charge-separated (CS) state with ligand-to-metal charge-transfer character using XTA. The surprisingly long-lived CS state, together with its intrinsic hybrid nature, all point to its potential application in heterogeneous photocatalysis and energy conversion

Unravelling the Correlation of Electronic Structure and Carrier Dynamics in CuInS\u3csub\u3e2\u3c/sub\u3e Nanoparticles

In this work, we report the direct correlation of photoinduced carrier dynamics and electronic structure of CuInS2 (CIS) nanoparticles (NPs) using the combination of multiple spectroscopic techniques including steady-state X-ray absorption spectroscopy (XAS), optical transient absorption (OTA), and X-ray transient (XTA) absorption spectroscopy. XAS results show that CIS NPs contain a large amount of surface Cu atoms with ≪four-coordination, which is more severe in CIS NPs with shorter nucleation times, indicating the presence of more Cu defect states in CIS NPs with smaller size particles. Using the combination of OTA and XTA spectroscopy, we show that electrons are trapped at states with mainly In or S nature while holes are trapped in sites characteristic of Cu. While there is no direct correlation of ultrafast trapping dynamics with NP nucleation time, charge recombination is significantly inhibited in CIS NPs with larger particles. These results suggest the key roles that Cu defect sites play in carrier dynamics and imply the possibility to control the carrier dynamics by controlling the surface structure at the Cu site in CIS NPs

Unravelling the Correlation of Electronic Structure and Carrier Dynamics in CuInS2 Nanoparticles

In this work, we report the direct correlation of photoinduced carrier dynamics and electronic structure of CuInS2 (CIS) nanoparticles (NPs) using the combination of multiple spectroscopic techniques including steady-state X-ray absorption spectroscopy (XAS), optical transient absorption (OTA), and X-ray transient (XTA) absorption spectroscopy. XAS results show that CIS NPs contain a large amount of surface Cu atoms with ≪four-coordination, which is more severe in CIS NPs with shorter nucleation times, indicating the presence of more Cu defect states in CIS NPs with smaller size particles. Using the combination of OTA and XTA spectroscopy, we show that electrons are trapped at states with mainly In or S nature while holes are trapped in sites characteristic of Cu. While there is no direct correlation of ultrafast trapping dynamics with NP nucleation time, charge recombination is significantly inhibited in CIS NPs with larger particles. These results suggest the key roles that Cu defect sites play in carrier dynamics and imply the possibility to control the carrier dynamics by controlling the surface structure at the Cu site in CIS NPs

Identifying Chinese Leading Venture Capital Firms Based on Graph Convolutional Neural Networks

It is a meaningful challenge to identify leading venture capital firms (VCs) in the analysis of the Chinese investment market. Identifying leading VCs is equal to determine influential nodes in the field of complex network analysis. Many studies have applied centrality measures to determine influence nodes. However, only a few studies have explored more efficient and flexible ways to accomplish this task. In this work, we propose a new approach which using graph convolutional neural networks to identify influential nodes in the network, so as to determine leading VCs. We build an undirected graph based on co-investment of VCs, then learn a VCs Graph Convolutional Neural Network (vcGCNN) for nodes classification. Our vcGCNN is labeled with ‘1’ and ‘0’ for ‘is leading VCs’ and ‘is not leading VCs’. The experiment results on VCs dataset demonstrate that vcGCNN outperforms multiple centrality measures and some typical spectral-based GNN methods for leading venture capital firms identification

Direct Observation of Node-to-Node Communication in Zeolitic Imidazolate Frameworks

Zeolitic imidazolate frameworks (ZIFs) with open-shell transition metal nodes represent a promising class of highly ordered light harvesting antennas for photoenergy applications. However, their charge transport properties within the framework, the key criterion to achieve efficient photoenergy conversion, are not yet explored. Herein, we report the first direct evidence of a charge transport pathway through node-to-node communication in both ground state and excited state ZIFs using the combination of paramagnetic susceptibility measurements and time-resolved optical and X-ray absorption spectroscopy. These findings provide unprecedented new insights into the photoactivity and charge transport nature of ZIF frameworks, paving the way for their novel application as light harvesting arrays in diverse photoenergy conversion devices