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Noncontact fatigue crack detection using non-linear frequency mixing of surface acoustic waves
No full textThe presence of fatigue cracks poses a significant challenge to the early detection of structural defects, prior to the formation of macro-cracks. This study investigates the feasibility of using acoustic nonlinearity parameters for the early evaluation and localization of fatigue damage in aluminum, employing a fully non-contact method for both excitation and sensing. The method is based on the sample excitation of two narrowband surface acoustic waves (SAWs) by two laser beams at two frequencies f(a) and f(b)(f(a) > f(b)). A laser-based surface acoustic wave (SAW) technique, utilizing micro-lens arrays, was used to generate two distinct, counter-propagating narrowband SAWs with wavelengths of 300 mu m and 500 mu m, corresponding to frequencies of 9.84 MHz and 5.86 MHz, respectively. The nonlinear interaction of these collinearly propagating counter-directed waves was monitored using a Laser Doppler Vibrometer across various fatigue levels. Subsequently, the interaction of these collinearly counter-propagating SAWs was employed to assess fatigue cracks at various damage levels. The presence of micro-cracks significantly increased material nonlinearity, leading to higher amplitudes of the quadratic components (eg., 2f(a), 2f(b), f(a) +/- f(a)) observed in the mixed acoustic signal. The results of this study demonstrate the feasibility of an early fatigue crack detection and achieving high spatial resolution for crack localization.
Evaluation of combustion models and reaction mechanisms to predict NOx and CO emissions from densely distributed lean-premixed multinozzle CH4/H2/air flames
No full textThis work explores the importance of reaction mechanisms and combustion models on the flame length and emission characteristic prediction by computational fluid dynamics (CFD) simulations of a complex multinozzle combustor configuration, operating under CH4/H2 blend variations. For the study, both RANS and LES turbulence models are explored. Test data used for the analysis is taken from work published by KAIST University, on the investigation of combustion dynamics and NOx/CO emissions from lean-premixed multinozzle CH4/H2 blended flames. The combustion domain consists of densely distributed small-scale multitube injectors called Micromixer nozzles. This setup provides insights into the collective behavior of small-scale multinozzle flames and resultant emission rates. Test data for different inlet compositions, keeping a thermal power condition of 78 kW, are considered for evaluation. Results from simulations for OH*chemiluminescence, OH concentrations, NOx, and CO emissions are compared against the test data. Reduce model fuel library (MFL) mechanism with relevant NOx pathways along with flamelet generated manifold (FGM) model found to predict the trend of flame length and emissions concentration with change in fuel composition reasonably well, compared to detailed chemistry combustion model, as well as test data. However, for capturing the impact of local nonunity Lewis number effects, the detailed chemistry model is found to be better for the low turbulent flow conditions, as considered in the referred experimental data.
Bias-controlled catalytic selectivity via metal-semiconductor schottky nanodiodes
No full textThe selective oxidation of methanol serves as a model reaction for probing the fundamental principles of heterogeneous catalysis, where control over product distribution remains a central challenge. Here, we report a catalytic nanodiode platform based on a Pt/n-type TiO2 Schottky junction that enables active modulation of reaction selectivity via applied electrical bias. By systematically varying the bias direction and magnitude during methanol oxidation under oxygen-rich conditions, we demonstrate that accumulation of negative charge on the Pt surface under reverse bias leads to a consistent decrease in methyl formate selectivity, indicating a shift toward full oxidation pathways. Electrical measurements confirm the suppression of current under reverse bias, supporting the formation of an electron-rich catalytic interface. These results provide direct experimental evidence that external control of interfacial charge can influence reaction selectivity, establishing catalytic nano-diodes as a promising platform for electronically tunable heterogeneous catalysis.
A Kronecker congruence relation for modular functions of higher level and genus
No full textLet j be the elliptic modular function, a weakly holomorphic modular function for SL2(Z). Weber showed that for each prime p the modular polynomial 'T'p(x, y) of j satisfies what is known as the Kronecker congruence relation 'T'p(x, y) equivalent to (xp-y)(x-yp) (mod pZ[x, y]). We give a generalization of this congruence applicable to certain weakly holomorphic modular functions of higher level in terms of integrality over Z[j]. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Interfacial spin-state engineering through lattice-distorted transition metal oxides heterostructure enables low-voltage and durable anion-exchange-membrane water electrolysis
No full textTransition metal oxides (TMOs) exhibit electrocatalytic activity intrinsically tied to their electron spin states, yet precise spin-state regulation without sacrificing structural integrity presents a persistent challenge. Here we introduce a hetero-lattice engineering approach to achieve spin-state modulation in TMOs through lattice distortion. We demonstrate a lattice-distorted Co3O4/MoO3 heterostructure (Co-O-Mo|H) that effectively converts low-spin Co3 + [e(g)(0)t(2)(g)(6)] to high-spin Co3+ [e(g)(2)t(2)(g)(4)]. This electronic reconfiguration enables strengthened *OH adsorption while promoting efficient *OOH desorption, resulting in exceptional oxygen evolution reaction performance with a low overpotential of 211 mV at 10 mA cm(-2), outperforming benchmark RuO2 (321 mV). Simultaneously, the engineered Co-O-Mo interface creates highly active hydrogen evolution sites, delivering ultralow overpotentials of 40/151 mV at current densities of 10/100 mA cm(-2), respectively, surpassing commercial Pt/C (52/170 mV). Integrated into an anion-exchange membrane electrolyzer, the Co-O-Mo|H-based system demonstrates exceptional durability (>200 h at 10 mA cm(-2)) and superior performance, achieving low cell voltages of 1.48/1.57 V at 10/100 mA cm(-2), significantly lower than the 1.58 V and 1.68 V required by RuO2 & Vert;20 % Pt/C. These findings establish a new paradigm for spin-state engineering through lattice distortion in transition metal oxides, offering a strategic pathway toward developing economically viable and robust hydrogen production technologies.
Buffering effects of green space on residents' mental wellbeing: A regression discontinuity analysis during COVID containment policy shift
No full textDuring the COVID-19 pandemic, access to green space was crucial for mental wellbeing, particularly in urban areas under lockdown. However, studies on the transition from strict containment measures to reopening are limited. This transition, while relaxing mobility and enabling free access to green spaces, also increases infection risks. Our study used a regression discontinuity design (RDD) with a unique dataset (N = 2545) from two major Chinese cities, Beijing and Shanghai, to examine the effects of the COVID containment policy shift on mental wellbeing and green space exposure. We compared participants by different green exposure categories to investigate variations in mental wellbeing during this transitional phase. The findings confirm that the policy does not promote short-term mental wellbeing, as measured by CES-D scores, self-rated health, happiness, and frequency of negative feelings. Residing 400-1200 m from a park, but not extremely close (within 400 m), confers mental health benefits. Visual exposure to greenery from windows bolsters mental wellbeing compared to limited greenery views, although the magnitude of this effect is modest. This study underscores the importance of urban green spaces in buffering mental wellbeing impacts of major policy changes during pandemic, highlighting their importance in urban planning and public health strategies.
Exploring the relationship between air quality and happiness in South Korea using artificial neural networks
No full textThis study investigates the relationship between air quality and subjective happiness across South Korean districts using artificial neural network (ANN)-based modeling. By aggregating the Korean National Assembly Futures Institute's happiness survey (2020-2021) data with the Korean Ministry of Environment's air quality data, among others, six major air pollutants were examined for their potential associations with the happiness ladder at the minuscule city level throughout South Korea. Complex non-linear patterns were observed. Among the pollutants, PM2.5 exhibited the most consistent negative association with the happiness ladder. The robust modeling and training strategies provide insights into the intricate relationships between air quality factors and the individual happiness ladder. The analysis effectively captures subtle relationships under fixed socioeconomic and happiness-related conditions, highlighting varying confidence intervals across multiple scenarios. These findings underscore the potential of ANN-based modeling in assessing the environmental factors of subjective happiness. Despite limitations related to the spatiotemporal scale of the annual happiness survey, this study contributes to the methods by applying deep learning techniques to infer the relationship between air quality and happiness, providing evidence that may inform environmental policymaking and urban sustainability strategies.
Advancing indigenous peoples' sovereignty in international environmental treaties: a call for exception clauses in international trade and investment law
No full textIndigenous peoples face persistent threats from extractive industries and state-led development, often without sufficient legal safeguards. International environmental treaties, while referencing Indigenous rights, typically use non-binding language that enables weak or selective implementation. This paper aims to identify how treaty design can more effectively protect existing domestic Indigenous protections. Drawing on trade and investment law examples-such as New Zealand's Treaty of Waitangi clauses and Colombia's reservation lists-it argues for systematically incorporating explicit carve-out mechanisms into environmental and human rights treaties. Naming Indigenous groups and domestic laws within treaty texts can strengthen legal certainty and shield protections from erosion. The paper concludes with recommendations for negotiators, including legal audits, inter-ministerial coordination, and capacity-building to help states, particularly in the Global South, design carve-outs that reinforce Indigenous sovereignty.
Facilitating C-C bond cleavage toward selective electrocatalytic oxidation of glycerol to formic acid: d-p orbital hybridization and adsorption thermodynamics
No full textFormic acid (FA) is a high-value product in hydrogen energy systems; hence, its selective production via electrochemical glycerol oxidation reaction (GOR) in an alkaline medium has emerged as an energy-efficient approach. However, the process is hindered by sluggish C-C bond cleavage, limited charge transfer, and competitive adsorption between glycerol and OH* species. In this study, we design La-based perovskite electrocatalysts with dual B-site metal incorporation to address the key challenges of alkaline GOR. Among various transition metal combinations (Ni, Fe, and Co), LaNi0.5Co0.5O3 (LNCO) demonstrates the highest GOR performance due to a synergistic effect between Ni and Co, which has been shown to modulate the electronic structure and optimize adsorption thermodynamics. In particular, LNCO exhibits enhanced charge transfer behavior, driven by metal 3d-oxygen 2p orbital hybridization and by a delocalized electronic structure with negligible band gap. Furthermore, glycerol adsorption is thermodynamically more favorable than OH* species, providing balanced adsorption energy conducive to efficient GOR. Consequently, LNCO promotes C-C bond cleavage kinetics and enhances selective FA production. These findings highlight that LNCO is a promising electrocatalytic platform for value-added chemical synthesis via a sustainable electrochemical route.
Self-confined oxidation domains in dual-metal sulfide catalyst enables active sites for selective photoconversion of carbon dioxide to methanol by pure water
No full textThe selective photoreduction of carbon dioxide (CO2) into high-value products, such as methanol, is a highly desirable yet challenging research area. Herein, we report a facile hydro-solvothermal-assisted method (HSM) for constructing dual-metal-site (Sn, In)-based photocatalysts. The resulting composites function as synergistic catalysts, achieving nearly 100 % selectivity for methanol in pure water under an AM1.5 G solar simulator. The formation of a highly stable Sn-C-O-In configuration within the dual-metal-site catalyst (SnIn4S8) facilitates the promotion of key intermediates (*COOH/*CHO) essential for the selective photoreduction of CO2 to methanol following protonation. Additionally, the oxidation domains confined on the SnIn4S8 surface can be self-regulated by adjusting the water to ethylene glycol ratio during the HSM process. Experimental and theoretical results indicate that these oxidation domains not only favor the methanol production pathway but also enhance CO2 adsorption and activation, as well as charge separation and transport. Consequently, the photoreduction efficiency of CO2 is boosted, achieving rates twenty times higher than those of prismatic SnIn4S8. This work provides valuable insights into the role of oxidation domains confined within dual-metal sulfides in CO2 photoreduction, paving the way for higher CO2 reduction efficiency while maintaining the selectivity of the parent catalyst.