Highly crystalline SnO2 is demonstrated to serve as a stable and robust electron‐transporting layer for high‐performance perovskite solar cells. Benefiting from its high crystallinity, the relatively ...thick SnO2 electron‐transporting layer (≈120 nm) provides a respectable electron‐transporting property to yield a promising power conversion efficiency (PCE)(18.8%) Over 90% of the initial PCE can be retained after 30 d storage in ambient with ≈70% relative humidity.
A low‐bandgap (1.33 eV) Sn‐based MA0.5FA0.5Pb0.75Sn0.25I3 perovskite is developed via combined compositional, process, and interfacial engineering. It can deliver a high power conversion efficiency ...(PCE) of 14.19%. Finally, a four‐terminal all‐perovskite tandem solar cell is demonstrated by combining this low‐bandgap cell with a semitransparent MAPbI3 cell to achieve a high efficiency of 19.08%.
This paper presents a simple yet effective supervised deep hash approach that constructs binary hash codes from labeled data for large-scale image search. We assume that the semantic labels are ...governed by several latent attributes with each attribute on or off, and classification relies on these attributes. Based on this assumption, our approach, dubbed supervised semantics-preserving deep hashing (SSDH), constructs hash functions as a latent layer in a deep network and the binary codes are learned by minimizing an objective function defined over classification error and other desirable hash codes properties. With this design, SSDH has a nice characteristic that classification and retrieval are unified in a single learning model. Moreover, SSDH performs joint learning of image representations, hash codes, and classification in a point-wised manner, and thus is scalable to large-scale datasets. SSDH is simple and can be realized by a slight enhancement of an existing deep architecture for classification; yet it is effective and outperforms other hashing approaches on several benchmarks and large datasets. Compared with state-of-the-art approaches, SSDH achieves higher retrieval accuracy, while the classification performance is not sacrificed.
•The generation of MSW is related to various features of urbanization.•The MSW composition was found to be closely related to the household population.•The volume of food waste generated was also ...related to the industrialization indicator.•MSW disposal fees should reflect not only household population but also tap water penetration.
The generation of municipal solid waste (MSW) is related to various features of urbanization. In this study, a linear regression model was used to evaluate the effects of several urbanization indicators on the composition of MSW. Household population (P), area of urban planning (L), tap water penetration (W), electricity sold (El), number of operating factories (I), car density (T), education level (Ed), and annual revenue (R) were chosen as important indicators of urbanization. The five major categories of MSW—paper, food waste, plastic, metal, and glass—were also chosen for specific analysis, and MSW composition was found to be closely related to household population (P) (r2 > 0.8). The volume of one category of waste, food waste, was related to the industrialization indicator (r2 > 0.9). The total volume of MSW and the total volume of metal waste were linked with household population divided by tap water penetration (P/W) (r2 = 0.9903), and with annual revenue divided by tap water penetration (R/W) (r2 = 0.9364). The volume of plastic waste and glass waste generated, respectively, was related to annual revenue divided by education level (R/Ed) (r2 = 0.9814 vs. r2 = 0.9371). In addition, a case study of Taipei City indicated that MSW disposal fees should reflect not only household population (P) but also tap water penetration (W). This study provides valuable findings quantifying the effects of urbanization on MSW composition. The results will help governments and enterprises to efficiently evaluate and predict variation in MSW composition with reference to indicators of urbanization, thereby improving the management of waste.
All-inorganic perovskite solar cells (PVSCs) have drawn increasing attention because of their outstanding thermal stability. However, their performance is still inferior than the typical ...organic-inorganic counterparts, especially for the devices with p-i-n configuration. Herein, we successfully employ a Lewis base small molecule to passivate the inorganic perovskite film, and its derived PVSCs achieved a champion efficiency of 16.1% and a certificated efficiency of 15.6% with improved photostability, representing the most efficient inverted all-inorganic PVSCs to date. Our studies reveal that the nitrile (C-N) groups on the small molecule effectively reduce the trap density of the perovskite film and thus significantly suppresses the non-radiative recombination in the derived PVSC by passivating the Pb-exposed surface, resulting in an improved open-circuit voltage from 1.10 V to 1.16 V after passivation. This work provides an insight in the design of functional interlayers for improving efficiencies and stability of all-inorganic PVSCs.
Marangoni‐effect‐driven actuators (MDAs) have the advantages of direct light‐to‐work conversion and convenient operation, which makes it widely researched in the cutting‐edge fields including robots, ...micromachines, and intelligent systems. However, the MDA relies on the surface tension difference and it only works on the 2D liquid–air interface. Besides, the MDAs are normally pure black due to the light‐absorption material limitation. Herein, a transparent light‐driven 3D movable actuator (LTMA) and a 3D manipulation strategy are proposed. The LTMA is composed of photothermal nanoparticles‐doped temperature‐responsive hydrogel, whose surface energy changes as the nanoparticles absorb light energy. The 3D manipulation strategy combines Marangoni effect with photothermal buoyancy flow for realizing complex self‐propellant and floating/sinking motions. The LTMA can perform more advanced tasks such as 3D obstacle avoidance and 3D sampling. Benefiting from the porous structure of hydrogel, LTMA can naturally absorb the chemical molecules for remote sampling and automated drug delivery. The light‐driven, transparent, three‐dimensionally movable, and programmable actuator has promising prospects in the field of micromachines and intelligent systems.
A transparent light‐driven 3D actuator (LTMA) is prepared using hydrogel and photothermal nanoparticles. The LTMA can not only realize the propulsion movements on the liquid‐air interface based on Marangoni effect but also can realize the floating/sinking motions based on the photo‐thermal buoyancy flow. The LTMA with programmable controllability has promising prospects in the field of micromachines and intelligent systems.
A one‐step core/shell electrospinning technique is exploited to fabricate uniform luminous perovskite‐based nanofibers, wherein the perovskite and the polymer are respectively employed in the core ...and the outer shell. Such a coaxial electrospinning technique enables the in situ formation of perovskite nanocrystals, exempting the needs of presynthesis of perovskite quantum dots or post‐treatments. It is demonstrated that not only the luminous electrospun nanofibers can possess color‐tunability by simply tuning the perovskite composition, but also the grain size of the formed perovskite nanocrystals is largely affected by the perovskite precursor stoichiometry and the polymer solution concentration. Consequently, the optimized perovskite electrospun nanofiber yields a high photoluminescence quantum yield of 30.9%, significantly surpassing the value of its thin‐film counterpart. Moreover, owing to the hydrophobic characteristic of shell polymer, the prepared perovskite nanofiber is endowed with a high resistance to air and water. Its photoluminescence intensity remains constant while stored under ambient environment with a relative humidity of 85% over a month and retains intensity higher than 50% of its initial intensity while immersed in water for 48 h. More intriguingly, a white light‐emitting perovskite‐based nanofiber is successfully fabricated by pairing the orange light‐emitting compositional perovskite with a blue light‐emitting conjugated polymer.
Uniform luminous perovskite nanofibers prepared by a one‐step core/shell electrospinning technique are demonstrated herein. The optimized perovskite electrospun nanofiber yields a high photoluminescence quantum yield with improved stability. Finally, a white light‐emitting perovskite‐based nanofiber is also successfully fabricated by pairing the orange light‐emitting compositional perovskite with a blue light‐emitting conjugated polymer.
Low‐temperature, solution‐processable Cu‐doped NiOX (Cu:NiOx), prepared via combustion chemistry, is demonstrated as an excellent hole‐transporting layer (HTL) for thin‐film perovskite solar cells ...(PVSCs). Its good crystallinity, conductivity, and hole‐extraction properties enable the derived PVSC to have a high power conversion efficiency (PCE) of 17.74%. Its general applicability for various elecrode materials is also revealed.
Southeastern South America (SESA) is a highly productive agricultural region and a hot spot for land‐atmosphere interactions. To evaluate the impact of dry soil moisture anomalies (SMAs) on SESA ...climate and the sensitivity of the regional climate response to the location of SMAs, we perform three experimental simulations using the Community Earth System Model (CESM) with prescribed dry SMAs over (a) SESA, (b) western SESA, and (c) eastern SESA. The dry SESA and eastern SESA simulations show widespread negative precipitation anomalies. In contrast, the dry western SESA simulation shows positive precipitation anomalies over northeastern Argentina, which are associated with the enhanced southward moisture flux co‐located with the South American low‐level jet exit region. A composite analysis of extremely dry cases over western SESA using reanalysis data agrees with the findings from our CESM experiment. These findings have potential implications for subseasonal forecasting in this region.
Plain Language Summary
Large‐scale soil moisture anomalies evolve slowly and can provide an opportunity for better weather forecasting at timescales longer than 2 weeks. Therefore, it is critical to understand the causal physical mechanism and evaluate whether the regional climate response is sensitive to the location of soil moisture anomalies, especially in a productive agricultural region like southeastern South America (SESA). Using a numerical climate model, we simulate the impacts of dry soil over (a) SESA, (b) western SESA, and (c) eastern SESA. The simulations show that dry soil over western SESA can alter regional atmospheric circulation in the proximity of the existing corridor of poleward moisture transport, hence enhancing rainfall over northeastern Argentina. Conversely, dry soil over eastern SESA or the entire SESA region results in less precipitation because enhanced northerly transport is not co‐located with the low‐level wind corridor. Analysis of a dataset that incorporates observations supports our findings from numerical simulations.
Key Points
The impact of dry soil moisture anomalies (SMAs) on southeastern South America (SESA) regional climate is sensitive to the location of SMAs
This study provides a causal mechanism linking soil moisture to precipitation via atmospheric circulation
When western SESA has dry soil, it generates anomalous geostrophic wind, which is co‐located with the low‐level jet exit region
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