We analyzed micrometer-scale titanium-niobium-oxide prototype memristors, which exhibited low write-power (<3 μW) and energy (<200 fJ per bit per μm), low read-power (∼nW), and high endurance (>millions of cycles). To understand their physico-chemical operating mechanisms, we performed in operando synchrotron X-ray transmission nanoscale spectromicroscopy using an ultra-sensitive time-multiplexed technique. We observed only spatially uniform material changes during cell operation, in sharp contrast to the frequently detected formation of a localized conduction channel in transition-metal-oxide memristors. We also associated the response of assigned spectral features distinctly to non-volatile storage (resistance change) and writing of information (application of voltage and Joule heating). These results provide critical insights into high-performance memristors that will aid in device design, scaling and predictive circuit-modeling, all of which are essential for the widespread deployment of successful memristor applications.
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http://dx.doi.org/10.1039/c6nr07671h | DOI Listing |
Laser absorption spectroscopy (LAS) is a well-established measurement technique for quantitative chemical speciation in a combustion environment. However, LAS measurement of nitric oxide (NO) in ammonia flames has never been reported in the literature. This is despite the community's recent strong interest in carbon-neutral ammonia combustion and the associated NO formation problem.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
The Swiss Institute for Dryland Environmental and Energy Research, BIDR, Ben-Gurion University of the Negev, Midreshet Ben-Gurion 8499000, Israel.
Plants often respond to drier climates by slow evolutionary adaptations from fast-growing to stress-tolerant species. These evolutionary adaptations increase the plants' resilience to droughts but involve productivity losses that bear on agriculture and food security. Plants also respond by spatial self-organization, through fast vegetation patterning involving differential plant mortality and increased water availability to the surviving plants.
View Article and Find Full Text PDFPLoS One
January 2025
Nanjing University of Information Science and Technology, Nanjing, China.
The forensic examination of AIGC(Artificial Intelligence Generated Content) faces poses a contemporary challenge within the realm of color image forensics. A myriad of artificially generated faces by AIGC encompasses both global and local manipulations. While there has been noteworthy progress in the forensic scrutiny of fake faces, current research primarily focuses on the isolated detection of globally and locally manipulated fake faces, thus lacking a universally effective detection methodology.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Economics, University Carlos III, Getafe, Spain.
Climate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact. The value added of this paper lies in introducing a quantitative methodology grounded in the trend analysis of temperature distribution quantiles to analyze climate change heterogeneity (CCH). By converting these quantiles into time series objects, the methodology empowers the definition and measurement of various relevant concepts in climate change analysis (warming, warming typology, warming amplification and warming acceleration) in a straightforward and robust testable linear regression format.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Department of Chemistry, University of California Berkeley, Berkeley, California 94720, United States.
Deployment of large numbers of low capital cost sensors to increase the spatial density of air quality measurements enables applications that build on mapping air at neighborhood scales. Effective deployment requires not only low capital costs for observations but also a simultaneous reduction in labor costs. The Berkeley Environmental Air Quality and CO Network (BEACON) is a sensor network measuring O, CO, NO, and NO, particulate matter (PM), and CO at dozens of locations in cities where it is deployed.
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