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Abstract Identifying and understanding various causal relations are fundamental to climate dynamics for improving the predictive capacity of Earth system modeling. In particular, causality in Earth systems has manifest temporal periodicities, like physical climate variabilities. To unravel the characteristic frequency of causality in climate dynamics, we develop a data‐analytic framework based on a combination of causality detection and Hilbert spectral analysis, using a long‐term temperature and precipitation dataset in the contiguous United States. Using the Huang–Hilbert transform, we identify the intrinsic frequencies of cross‐regional causality for precipitation and temperature, ranging from interannual to interdecadal time scales. In addition, we analyze the spectra of the physical climate variabilities, including El Niño‐Southern Oscillation and Pacific Decadal Oscillation. It is found that the intrinsic causal frequencies are positively associated with the physics of the oscillations in the global climate system. The proposed methodology provides fresh insights into the causal connectivity in Earth's hydroclimatic system and its underlying mechanism as regulated by the characteristic low‐frequency variability associated with various climatic dynamics. 

The Atlantic Meridional Overturning Circulation (AMOC) is a significant component of the global ocean system, which has so far ensured a relatively warm climate for the North Atlantic and mild conditions in regions, such as Western Europe. The AMOC is also critical for the global climate. The complexity of the dynamical system underlying the AMOC is so vast that a long-term assessment of the potential risk of AMOC collapse is extremely challenging. However, short-term prediction can lead to accurate estimates of the dynamical state of the AMOC and possibly to early warning signals for guiding policy making and control strategies toward preventing AMOC collapse in the long term. We develop a model-free, machine-learning framework to predict the AMOC dynamical state in the short term by employing five datasets: MOVE and RAPID (observational), AMOC fingerprint (proxy records), and AMOC simulated fingerprint and CESM AMOC (synthetic). We demonstrate the power of our framework in predicting the variability of the AMOC within the maximum prediction horizon of 12 or 24 months. A number of issues affecting the prediction performance are investigated. 

Emerging wearable devices would benefit from integrating ductile photovoltaic light-harvesting power sources. In this work, we report a small-molecule acceptor (SMA), also known as a non–fullerene acceptor (NFA), designed for stretchable organic solar cell (s-OSC) blends with large mechanical compliance and performance. Blends of the organosilane-functionalized SMA BTP-Si4 with the polymer donor PNTB6-Cl achieved a power conversion efficiency (PCE) of >16% and ultimate strain (ε_u) of >95%. Typical SMAs suppress OSC blend ductility, but the addition of BTP-Si4 enhances it. Although BTP-Si4 is less crystalline than other SMAs, it retains considerable electron mobility and is highly miscible with PNTB6-Cl and is essential for enhancing ε_u. Thus,s-OSCs with PCE > 14% and operating normally under various deformations (>80% PCE retention under an 80% strain) were demonstrated. Analysis of several SMA-polymer blends revealed general molecular structure–miscibility–stretchability relationships for designing ductile blends. 

Abstract Global climate changes, especially the rise of global mean temperature due to the increased carbon dioxide (CO₂) concentration, can, in turn, result in higher anthropogenic and biogenic greenhouse gas emissions. This potentially leads to a positive loop of climate–carbon feedback in the Earth’s climate system, which calls for sustainable environmental strategies that can mitigate both heat and carbon emissions, such as urban greening. In this study, we investigate the impact of urban irrigation over green spaces on ambient temperatures and CO₂exchange across major cities in the contiguous United States. Our modeling results indicate that the carbon release from urban ecosystem respiration is reduced by evaporative cooling in humid climate, but promoted in arid/semi-arid regions due to increased soil moisture. The irrigation-induced environmental co-benefit in heat and carbon mitigation is, in general, positively correlated with urban greening fraction and has the potential to help counteract climate–carbon feedback in the built environment. 

In recent decades, more than 100 different mechanophores with a broad range of activation forces have been developed. For various applications of mechanophores in polymer materials, it is crucial to selectively activate the mechanophores with high efficiency, avoiding nonspecific bond scission of the material. In this study, we embedded cyclobutane-based mechanophore cross-linkers (I and II) with varied activation forces (fa) in the first network of the double network hydrogels and quantitively investigated the activation selectivity and efficiency of these mechanophores. Our findings revealed that cross-linker I, with a lower activation force relative to the bonds in the polymer main chain (fa-I/fa-chain = 0.8 nN/3.4 nN), achieved efficient activation with 100% selectivity. Conversely, an increase of the activation force of mechanophore II (fa-II/fa-chain = 2.5 nN/3.4 nN) led to a significant decrease of its activation efficiency, accompanied by a substantial number of nonspecific bond scission events. Furthermore, with the coexistence of two cross-linkers, significantly different activation forces resulted in the almost complete suppression of the higher-force one (i.e., I and III, fa-I/fa-III = 0.8 nN/3.4 nN), while similar activation forces led to simultaneous activations with moderate efficiencies (i.e., I and IV, fa-I/fa-IV = 0.8 nN/1.6 nN). These findings provide insights into the prevention of nonspecific bond rupture during mechanophore activation and enhance our understanding of the damage mechanism within polymer networks when using mechanophores as detectors. Besides, it establishes a principle for combining different mechanophores to design multiple mechanoresponsive functional materials.