Synthesis of low-cost multi-element Pt-based alloy nanoparticles as catalysts for the oxygen reduction reaction.

Due to their high catalytic activity, stability, and economic benefits, Pt-based multi-element alloyed nanoparticles (NPs) are considered promising electrodes for oxygen reduction reactions. However, a synthesis method capable of controlling the reduction reaction of elements with different redox potentials to synthesize multimetallic alloy NPs is yet to be developed. In this study, monodisperse NiPtPd alloy NPs with varying compositions were synthesized using 1-heptanol as a reducing solvent. The selection of low-reducing noble metal precursors and complexing agents is done strategically to adjust the reduction time of metal ions. The spectroscopic results confirmed that olelylamine (OAm) preferentially coordinates with Pt ions, while trioctylphosphine (TOP) preferentially coordinates with Pd ions. Consequently, control of the elemental distribution within the particle is successfully achieved by adjusting the OAm/Pt and TOP/Pd molar ratios. Subsequently, Ni78Pt11Pd11 alloy NPs were designed, and their catalytic properties as electrodes in the oxygen reduction reaction (ORR) were examined. Despite a low noble metal content of 22%, the catalytic performance and stability were superior to and comparable to those of commercial Pt NPs, respectively.

Adaptive estimation of the Gutenberg-Richter b value using a state space model and particle filtering.

Earthquakes follow an exponential distribution referred to as the Gutenberg-Richter law, which is characterized by the b value that represents a ratio of the number of large earthquakes to that of small earthquakes. Spatial and temporal variation in the b value is important for assessing the probability of a larger earthquake. Conventionally, the b value is obtained by a maximum-likelihood estimation based on past earthquakes with a certain sample size. To properly assess the occurrence of earthquakes and understand their dynamics, determining this parameter with a statistically optimal method is important. Here, we discuss a method that uses a state space model and a particle filter, as a framework for time-series data, to estimate temporal variation in the b value. We then compared our output with that of a conventional method using data of earthquakes that occurred in Tohoku and Kumamoto regions in Japan. Our results indicate that the proposed method has the advantage of estimating temporal variation of the b value and forecasting magnitude. Moreover, our research suggests no heightened probability of a large earthquake in the Tohoku region, in contrast to previous studies. Simultaneously, there is the potential of a large earthquake in the Kumamoto region, emphasizing the need for enhanced monitoring.

Preseismic atmospheric radon anomaly associated with 2018 Northern Osaka earthquake.

Despite the challenges in identifying earthquake precursors in intraplate (inland) earthquakes, various hydrological and geochemical measurements have been conducted to establish a possible link to seismic activities. Anomalous increases in radon (222Rn) concentration in soil, groundwater, and atmosphere have been reported prior to large earthquakes. Although the radon concentration in the atmosphere is lower than that in groundwater and soils, a recent statistical analysis has suggested that the average atmospheric concentration over a relatively wide area reflects crustal deformation. However, no study has sought to determine the underlying physico-chemical relationships between crustal deformation and anomalous atmospheric radon concentrations. Here, we show a significant decrease in the atmospheric radon concentration temporally linked to the seismic quiescence before the 2018 Northern Osaka earthquake occurring at a hidden fault with complex rupture dynamics. During seismic quiescence, deep-seated sedimentary layers in Osaka Basin, which might be the main sources of radon, become less damaged and fractured. The reduction in damage leads to a decrease in radon exhalation to the atmosphere near the fault, causing the preseismic radon decrease in the atmosphere. Herein, we highlight the necessity of continuous monitoring of the atmospheric radon concentration, combined with statistical anomaly detection method, to evaluate future seismic risks.

Non-parametric detection of atmospheric radon concentration anomalies related to earthquakes.

Anomalous phenomena related to earthquakes have been studied to aid in the forecasting of large earthquakes. Radon (222Rn) concentration changes are known to be one of those phenomena. Many studies have quantified radon anomalies to identify physical aspects of radon emanations related to earthquakes. Here, we apply singular spectrum transformation, non-parametric analysis to estimate change points in time series, to atmospheric radon concentration. From 10 years of data from continuous observation of the atmospheric radon concentration over northeastern Japan and Hokkaido, we identify anomalies in the atmospheric radon concentration related to the moment releases of large earthquakes. Compared with a conventional model-based method, the singular spectrum transformation method identifies more anomalies. Moreover, we also find that change points in the atmospheric radon concentration prior to the 2011 Tohoku-Oki earthquake (Mw 9.0; 11 Mar. 2011, N38.1°, E142.9°) coincided with periods of other anomalous precursory phenomena. Our results indicate that singular spectrum transformation can be used to detect anomalies in atmospheric radon concentration related to the occurrences of large earthquakes.