Researchers from BI Norwegian Business School and NHH Norwegian School of Economics have developed a new behavioral credit-risk model that integrates credit and debit transactions. The model significantly outperforms state-of-the-art machine learning methods in predicting credit card delinquency and offers clearer insight into the behavioral drivers behind repayment problems.

A research team from Tsinghua University and Tongji University has proposed a “100-Kilometer Coastal Desalination for Short-cut Water Cycle (100K-CDS)” strategy to address China’s growing water scarcity. The authors reposition seawater desalination as a transformative solution, highlighting how the integration of reverse osmosis and renewable energy has cut costs and enabled a 57.5~98.3% reduction in carbon emissions. By industrializing water production along the coast—home to 40% of China's population and over half its GDP—this approach treats freshwater as a manufacturable resource, decoupling water security from natural constraints and offering a scalable model for arid regions worldwide.

Researchers at Peking University share the results of their 30-year investigation in tackling the long-standing mystery of turbulence initiation. Their study identifies soliton-like coherent structures as the key mechanism in driving the transition from laminar to turbulence in shear flows. This discovery provides promising directions for the development of advanced predictive models and technologies for improved control of turbulence.

Abstract

Purpose – This study aims to explore the impacts of U.S. debt ceiling uncertainty on crude oil markets and further reveal the specific influence mechanisms.

Design/methodology/approach – This paper introduces a debt ceiling uncertainty index based on news reports and selects six representative crude oil futures and spot markets to investigate the heterogeneous impacts of U.S. debt ceiling uncertainty on crude oil markets. More specifically, on the one hand, the nonparametric causality-inquantiles test method is used to discuss the asymmetric impacts of debt ceiling uncertainty on the different conditional distributions of crude oil series. On the other hand, the dynamic effects of debt ceiling uncertainty on crude oil markets are analyzed, combining with the time-varying parameter vector autoregressive model.

Findings – The conclusions of this paper are as follows: First, the U.S. debt ceiling uncertainty has obvious nonlinear impacts on each crude oil market, and the effects are greater under the normal condition of crude oil markets rather than under their extreme conditions. Second, the shocks from debt ceiling uncertainty to crude oil markets are mainly illustrated as negative and can be significantly enhanced by important debt-related events. Over time, the reactions of crude oil markets turn to weak positive and gradually dissipate after 6 months. Finally, enterprise production, investor sentiment and government shutdown play important roles as transmission intermediaries for the influence of debt ceiling uncertainty on the crude oil market.

Originality/value – The findings are beneficial for investors to accurately judge oil price trends and prevent investment losses caused by debt risks and also help producers prevent the impacts of crude oil price changes on production and operation activities. Moreover, it is conducive to the management department to maintain the stability of the crude oil market, thus enabling the crude oil financial market to better serve the real economy.

The extensive utilization of fossil fuels has led to a significant increase in carbon dioxide (CO₂) emissions, contributing to global warming and environmental pollution, which pose major threats to human survival. To mitigate these effects, many researchers are actively employing state-of-the-art technologies to convert CO₂ into valuable chemicals and fuels, thereby supporting sustainable development. However, few studies have employed bibliometric methods to systematically analyze research trends in CO₂ reduction reaction (CO₂RR), resulting in limited macroscopic insights into this field. This study aims to conduct a scientometric analysis of academic literature on electrocatalytic, photocatalytic, and thermocatalytic CO₂RR from 2015 to 2023. Utilizing bibliometric analysis tools Citespace, Bibliometrix, and Vosviewer for data visualization, it establishes a knowledge framework for catalytic CO₂RR. The results show that China, the United States, and India are the top three countries with the highest number of published papers in this field, with China and the United States having the highest levels of collaboration. The journal Applied Catalysis B-Environmental published the most articles and received the highest citation count, with 3.4% of the articles in this field appearing in the journal and a total of 62526 citations. Keyword analysis revealed that terms like “CO₂RR,” “CO₂,” “conversion,” and “reduction” are the most frequently occurring, indicating key areas of focus. Additionally, “selectivity” and “heterojunction” emerged as prominent research hotspots. The discussion section highlights the current challenges in the field and proposes potential strategies to address these obstacles, providing valuable insights for research in the field of catalytic CO₂RR.

The utilization of solar energy to address energy and environmental challenges has a seen a significant growth in recent years. Metal halides, which offer unique advantages such as tunable bandgaps, high light absorption efficiencies, favorable product release rates, and low exciton binding energies, have emerged as excellent photocatalysts for energy conversion. This paper reviews the recent advancements in both all-inorganic and organic-inorganic hybrid metal halide photocatalytic materials, including the fundamental mechanisms of photocatalytic CO₂ reduction, various synthesis strategies for metal halide photocatalysts, and their applications in the field of photocatalysis. Finally, it examines the current challenges associated with metal halide materials and explores potential solutions for metal halide materials, along with their future prospects in photocatalysis applications.

Directly correlating the morphology and composition of interfacial water is vital not only for studying water icing under critical conditions but also for understanding the role of protein–water interactions in bio-relevant systems. In this study, we present a model system to study two-dimensional (2D) water layers under ambient conditions by using self-assembled monolayers (SAMs) supporting the physisorption of the Cytochrome C (Cyt C) protein layer. We observed that the 2D island-like water layers were uniformly distributed on the SAMs as characterized by atomic force microscopy, and their composition was confirmed by nano-atomic force microscopy-infrared spectroscopy and Raman spectroscopy. In addition, these 2D flakes could grow under high-humidity conditions or melt upon the introduction of a heat source. The formation of these flakes is attributed to the activation energy for water desorption from the Cyt C being nearly twofold high than that from the SAMs. Our results provide a new and effective method for further understanding the water–protein interactions.