Carbon-neutral power system enabled e-kerosene production in Brazil in 2050

Rich in renewable resources, extensive acreage, and bioenergy expertise, Brazil, however, has no established strategies for sustainable aviation fuels, particularly e-kerosene. We extend the lens from the often-studied economic feasibility of individual e-kerosene supply chains to a system-wide perspective. Employing energy system analyses, we examine the integration of e-kerosene production into Brazil’s national energy supplies. We introduce PyPSA-Brazil, an open-source energy system optimisation model grounded in public data. This model integrates e-kerosene production and offers granular spatial resolution, enabling federal-level informed decisions on infrastructure locations and enhancing transparency in Brazilian energy supply scenarios. Our findings indicate that incorporating e-kerosene production can bolster system efficiency as Brazil targets a carbon-neutral electricity supply by 2050. The share of e-kerosene in meeting kerosene demand fluctuates between 2.7 and 51.1%, with production costs varying from 113.3 to 227.3 €/MWh. These costs are influenced by factors such as biokerosene costs, carbon pricing, and export aspirations. Our findings are relevant for Brazilian policymakers championing aviation sustainability and offer a framework for other countries envisioning carbon-neutral e-kerosene production and export

Linkages between nitrogen cycling, nitrogen isotopes, and environmental properties in paleo-lake basins

This work was funded by the National Natural Science Foundation of China (no. 41830425). E.E. Stüeken acknowledges funding from a Natural Environment Research Council grant (no. NE/V010824/1).The linkages between nitrogen cycling, nitrogen isotopes, and environmental properties are fundamental for reconstructing nitrogen biogeochemistry. While the impact of ocean redox changes on nitrogen isotopes is relatively well understood, it is poorly known how nitrogen responds to changes in pH and salinity. To fill the knowledge gap, we explore the effects of these environmental parameters using a well-controlled set of samples from Carboniferous−Paleogene lake sediments in China. Our results show that the threshold of 10−12‰ in δ15N works to distinguish alkaline (pH > 9) from circum-neutral conditions. Elevated Mo levels in the alkaline samples support the idea of NH3 volatilization from a reducing water column in an alkaline setting. For non-alkaline lakes, δ15N values tend to be higher (up to +10‰) in more saline, anoxic settings, which is attributed to either the expansion of stagnant anoxic waters spurring water-column denitrification or a shift from plant-based toward more microbially dominated ecosystems or both. Our results imply that salinity-induced redox stratification and basicity can alter nitrogen biogeochemical cycling beyond what is shown by the marine nitrogen isotope record alone. This finding will result in an improved understanding of the dynamic controls of δ15N in sediments and lead to better biogeochemical interpretations of paleo-environmental conditions from unknown environmental settings on Earth and beyond Earth.PostprintPeer reviewe

Scavenging low-speed breeze wind energy using a triboelectric nanogenerator installed inside a square variable diameter channel

Over the recent years, triboelectric nanogenerator (TENG) have received widespread attention as a simple and efficient energy harvesting device. However, how to collect the breeze in daily life is an important issue that need to be solved for wind-powered triboelectric nanogenerator (W-TENG). Here, we propose a method of connecting a square variable diameter channel to the previously studied double-ended fixed W-TENG, which realizes the collection of energy in the breeze. As a result, after adding channels, the starting wind speed of W-TENG is optimized to as low as 0.4 m s−1, with an average output voltage of 6.1 V. This method not only enables W-TENG to start at the ultra-low wind speed, but also improves the output performance. When the external wind velocity is 2.0 m s−1, the output voltage is increased by 10.6 times after adding the channel structure. This work provides a good strategy for collecting the breeze without changing the original structure of the W-TENG, fully demonstrating the advantages of energy harvesting under the low wind velocity.</p

Multi-Effects Coupled Nanogenerators for Simultaneously Harvesting Solar, Thermal, and Mechanical Energies

As a result of the widespread use of small-scale and low-power electronic devices, the demand for micro-energy sources has increased, in particular the potential to harvest the wide variety of energy sources present in their surrounding environment. In this paper, a novel coupled nanogenerator that can realize energy harvesting for multiple energy sources is reported. Based on the unique electrical properties of ferroelectric Bi 0.5Na 0.5TiO 3 (BNT) materials, it is possible to combine a photovoltaic cell, pyroelectric nanogenerator, and triboelectric-piezoelectric nanogenerator in a single element to harvest light, heat, and mechanical energy simultaneously. To evaluate the effectiveness of coupling for different materials, a Yang coupling factor (k C,Q) is defined in terms of transferred charge, where BNT has the largest k C,Q of 1.29 during heating, indicating that BNT has the best coupling enhancement compared to common ferroelectric materials. This new criterion and novel device structure therefore provide a new basis for the future development of coupled nanogenerators which are capable of harvesting multiple sources of energy.</p

Multi-Effects Coupled Nanogenerators for Simultaneously Harvesting Solar, Thermal, and Mechanical Energies

As a result of the widespread use of small-scale and low-power electronic devices, the demand for micro-energy sources has increased, in particular the potential to harvest the wide variety of energy sources present in their surrounding environment. In this paper, a novel coupled nanogenerator that can realize energy harvesting for multiple energy sources is reported. Based on the unique electrical properties of ferroelectric Bi 0.5Na 0.5TiO 3 (BNT) materials, it is possible to combine a photovoltaic cell, pyroelectric nanogenerator, and triboelectric-piezoelectric nanogenerator in a single element to harvest light, heat, and mechanical energy simultaneously. To evaluate the effectiveness of coupling for different materials, a Yang coupling factor (k C,Q) is defined in terms of transferred charge, where BNT has the largest k C,Q of 1.29 during heating, indicating that BNT has the best coupling enhancement compared to common ferroelectric materials. This new criterion and novel device structure therefore provide a new basis for the future development of coupled nanogenerators which are capable of harvesting multiple sources of energy.</p

Highly efficient triazine/carbazole-based host material for green phosphorescent organic light-emitting diodes with low efficiency roll-off

Two novel triazin/carbazole-based host materials were designed and synthesized, which demonstrated outstanding EL performance with maximum CE, PE and EQE of 69.3 cd A−1, 54.2 lm W−1 and 21.9%, respectively.</p

Self-Powered Stretchable Sensor Arrays Exhibiting Magnetoelasticity for Real-Time Human–Machine Interaction

Stretchable strain sensors are highly desirable for human motion monitoring, and can be used to build new forms of bionic robots. However, the current use of flexible strain gauges is hindered by the need for an external power supply, and the demand for long-term operation. Here, a new flexible self-powered strain sensor system based on an electromagnetic generator that possesses a high stretchability in excess of 150%, a short response time of 30 ms, and an excellent linearity (R2 &gt; 0.98), is presented. Based on this new form of sensor, a human–machine interaction system is designed to achieve remote control of a robot hand and vehicle using a human hand, which provides a new scheme for real-time gesture interaction.</p

TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification

Audiovisual data is everywhere in this digital age, which raises higher requirements for the deep learning models developed on them. To well handle the information of the multi-modal data is the key to a better audiovisual modal. We observe that these audiovisual data naturally have temporal attributes, such as the time information for each frame in the video. More concretely, such data is inherently multi-modal according to both audio and visual cues, which proceed in a strict chronological order. It indicates that temporal information is important in multi-modal acoustic event modeling for both intra- and inter-modal. However, existing methods deal with each modal feature independently and simply fuse them together, which neglects the mining of temporal relation and thus leads to sub-optimal performance. With this motivation, we propose a Temporal Multi-modal graph learning method for Acoustic event Classification, called TMac, by modeling such temporal information via graph learning techniques. In particular, we construct a temporal graph for each acoustic event, dividing its audio data and video data into multiple segments. Each segment can be considered as a node, and the temporal relationships between nodes can be considered as timestamps on their edges. In this case, we can smoothly capture the dynamic information in intra-modal and inter-modal. Several experiments are conducted to demonstrate TMac outperforms other SOTA models in performance. Our code is available at https://github.com/MGitHubL/TMac.Comment: This work has been accepted by ACM MM 2023 for publicatio

Carbon-neutral power system enabled e-kerosene production in Brazil in 2050

Rich in renewable resources, extensive acreage, and bioenergy expertise, Brazil, however, has no established strategies for sustainable aviation fuels, particularly e‑kerosene. We extend the lens from the often‑studied economic feasibility of individual e‑kerosene supply chains to a system‑wide perspective. Employing energy system analyses, we examine the integration of e‑kerosene production into Brazil’s national energy supplies. We introduce PyPSA‑Brazil, an open‑source energy system optimisation model grounded in public data. This model integrates e‑kerosene production and offers granular spatial resolution, enabling federal‑level informed decisions on infrastructure locations and enhancing transparency in Brazilian energy supply scenarios. Our findings indicate that incorporating e‑kerosene production can bolster system efficiency as Brazil targets a carbon‑neutral electricity supply by 2050. The share of e‑kerosene in meeting kerosene demand fluctuates between 2.7 and 51.1%, with production costs varying from 113.3 to 227.3 €/MWh. These costs are influenced by factors such as biokerosene costs, carbon pricing, and export aspirations. Our findings are relevant for Brazilian policymakers championing aviation sustainability and offer a framework for other countries envisioning carbon‑neutral e‑kerosene production and export