The synthesis of photocatalysts with both broad light absorption and efficient charge separation is significant for a high solar energy conversion, which still remains to be challenge. Herein, narrow-bandgap Y2Ti2O5S2 (YTOS) oxysulfide nanosheet coexposed defined {101} {001} facets synthesized by flux-assisted solid-state reaction was revealed display the character an anisotropic migration. selective photodeposition cocatalysts demonstrated that surfaces YTOS nanosheets were reduction...

Emergence and causality are two fundamental concepts for understanding complex systems. They interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed cause of individual properties. other can exhibit emergence, meaning that new causal laws may arise as we increase level abstraction. Causal (CE) theory aims bridge these even employs measures quantify emergence. This paper provides a comprehensive review recent advancements in...

The limitations imposed by the high carrier recombination rate in current photocatalytic H2O2 production system substantially restrict of generation. Herein, we successfully prepared an In2S3/HTCC dense heterojunction bridged In–S–C bonds through situ polymerization glucose on In2S3. This interfacial bond provides a fast transfer channel for electrons at interface to achieve highly efficient charge efficiency, leading formation enhanced built-in electric field between In2S3 and HTCC, thus...

Solar water splitting from a p–n-conjugated photoelectrochemical (PEC) system is promising way to produce hydrogen sustainably. At present, finding compatible p-type photocathode material for the p–n remains great challenge in consideration of photocurrent and stability. This paper highlighted candidate, Rh/BaTiO3, by switching BaTiO3 an n-type photoanode upon Rh doping. The dopant activated visible light absorption up 550 nm onset potential as high 1.0 V (vs RHE). Using surface photovoltage...

ABSTRACT Quantifying emergence and modeling emergent dynamics in a data-driven manner for complex dynamical systems is challenging due to the fact that behaviors cannot be directly captured by micro-level observational data. Thus, it crucial develop framework identify phenomena capture at macro-level using available Inspired theory of causal (CE), this paper introduces machine learning learn macro-dynamics an latent space quantify degree CE. The maximizes effective information, resulting...

Causal emergence (CE) based on effective information (EI) shows that macro-states can exhibit stronger causal effects than micro-states in dynamics. However, the identification of CE and maximization EI both rely coarse-graining strategies, which is a key challenge. A recently proposed framework approximate dynamical reversibility utilizing singular value decomposition (SVD) independent but limited to transition probability matrices (TPM) discrete states. To address this problem, article...

We employ a selectively pumped solid-state laser with stimulated Raman scattering and second-harmonic generation to generate frequency-doubled lasing modes (FDLMs) at 588 nm. The FDLMs are transformed by using an external cylindrical mode converter various structured beams multiple optical vortices. Theoretical analyses clearly reveal the relationship between components in emission transverse displacement of off-center pumping. further verify that experimental results for can be numerically...

Photoelectrochemical (PEC) performance of WO3 photoanodes for water splitting is heavily influenced by the orientation crystal facets. In this work, mono-particle-layer electrodes, assembled particulate square plates with highly uniform alignment along (002) facet, improved PEC oxidation kinetics and stability. Photo-deposition Au cracks formed on surface plates, which are edges {110} facets, was found to further enhance electron collection efficiency. Combination these two strategies...

Conventional studies of causal emergence have revealed that stronger causality can be obtained on the macro-level than micro-level same Markovian dynamical systems if an appropriate coarse-graining strategy has been conducted micro-states. However, identifying this emergent from data is still a difficult problem not solved because found easily. This paper proposes general machine learning framework called Neural Information Squeezer to automatically extract effective and dynamics, as well...

Building a sustainable human habitat on the Moon requires advances in excavation, paving, and additive manufacturing to construct landing pads, surface transportation arteries, resilient shelters, scientific outposts. Construction of infrastructure elements lunar necessitates exploration interfacial reactivity locally sourced regolith adaptation Earth-based construction techniques. Various crosslinking frameworks sintering methods have been proposed as means consolidating into load-bearing...

The built-in potential in the space charge layer dominates migration of carriers a traditional photoelectrode model. In this work, through particle engineering and surface reconstruction, Rh-doped rutile TiO2 (Rh-TiO2) is fabricated, which Rh concentration decreased gradiently directed from conductive substrate to solution. Since dopants involve intragap states above valence band TiO2, it shapes that orients photoexcited holes toward repels electrons solution side, change Rh-TiO2 electrode...

After coarse-graining a complex system, the dynamics of its macro-state may exhibit more pronounced causal effects than those micro-state. This phenomenon, known as emergence, is quantified by indicator effective information. However, two challenges confront this theory: absence well-developed frameworks in continuous stochastic dynamical systems and reliance on methodologies. In study, we introduce an exact theoretic framework for emergence within linear iteration featuring state spaces...

Developing an efficient and stable photocathode material for photoelectrochemical solar water splitting remains challenging. Herein, we demonstrate the potential of rutile TiO2 as a by Rh doping with visible light absorption up to 640 nm onset 0.9 V versus reversible hydrogen electrode. The dopant transforms host from n-type semiconductor p-type one, confirmed Mott–Schottky curve kelvin probe force microscopy. Physical analyses further suggest that mechanism is dependent on concentration....

Semi-artificial Z-scheme systems offer promising potential toward efficient solar-to-chemical conversion, yet sustainable and stable designs are currently lacking. Here, we developed a hybrid system capable for visible light–driven overall water splitting by integrating the durability of inorganic photocatalysts with interfacial adhesion regenerative property bacterial biofilms. The configuration is fabricated drop casting mixture onto glass plate, followed growth biofilms conformal...

The interaction of surfactants with lipid membranes can result in composition change, area expansion, solubilization, or the formation protrusion features membranes. Amphipathic surfactant molecules are simplified analogues to membrane-active drugs and peptides which known for inserting into bilayers; however, effect these amphipathic on supported is not well characterized. In this paper we explore use microcantilever sensors quantify surfactants' effects We microcantilevers coated probe...

Aiming at the current software cost model and optimal release research, which does not fully consider actual faults in testing phase, a cost-reliability SRGM evaluation selection algorithm SESABCRC is proposed. From perspective of incomplete debugging, introducing new faults, considering effort, imperfect debugging established. The proposed can be used to describe process through failure data set verification, superior other models. Based on SRGM, corresponding function given, explicitly...

We report the use of lipid membrane-coated microcantilevers to probe interactions between phospholipid membranes and membrane-active peptides. This sensing method integrates two well-developed techniques: solid-supported bilayers (SLBs) microcantilever sensors. SLBs are prepared on silicon dioxide surface using a vesicle fusion method. As molecules adsorb onto microcantilever, bends due induced compressive or tensile stresses, which result from free energy change. Real-time stress changes in...

This article studies the E-Bayesian estimation of unknown parameter Lomax distribution based on generalized Type-I hybrid censoring. Under square error loss and LINEX functions, we get compare its effectiveness with Bayesian estimation. To measure estimation, expectation mean (E-MSE) is introduced. With Markov chain Monte Carlo technology, estimations are computed. Metropolis–Hastings algorithm applied within process. Similarly, credible interval for calculated. Then, can MSE E-MSE to...

For the purpose of improving statistical efficiency estimators in life-testing experiments, generalized Type-I hybrid censoring has lately been implemented by guaranteeing that experiments only terminate after a certain number failures appear. With wide applications bathtub-shaped distribution engineering areas and recently introduced scheme, considering there is no work coalescing this type model with distribution, we consider parameter inference under censoring. First, estimations unknown...

After coarse-graining a complex system, the dynamics of its macro-state may exhibit more pronounced causal effects than those micro-state. This phenomenon, known as emergence, is quantified by indicator effective information. However, two challenges confront this theory: absence well-developed frameworks in continuous stochastic dynamical systems and reliance on methodologies. In study, we introduce an exact theoretic framework for emergence within linear iteration featuring state spaces...

Predicting company growth is crucial for strategic adjustment, operational decision-making, risk assessment, and loan eligibility reviews. Traditional models often focus too much on theory, overlooking practical forecasting, or they rely solely time series forecasting techniques, ignoring interpretability the inherent mechanisms of growth. In this paper, we propose a machine learning-based prediction framework that incorporates an econophysics model Our captures both intrinsic companies led...