The current paper reports on a sonochemical synthesis method for manufacturing nanostructured (typical grain size of 50 nm) SrTi0.6Fe0.4O2.8 (Sono-STFO40) powder. This powder is characterized using X ray-diffraction (XRD), Mössbauer spectroscopy and Scanning Electron Microscopy (SEM), and results are compared with commercially available SrTi0.4Fe0.6O2.8 (STFO60) powder. In order to manufacture resistive oxygen sensors, both Sono-STFO40 and STFO60 are deposited, by dip-pen nanolithography (DPN) method, on an SOI (Silicon-on-Insulator) micro-hotplate, employing a tungsten heater embedded within a dielectric membrane. Oxygen detection tests are performed in both dry (RH = 0%) and humid (RH = 60%) nitrogen atmosphere, varying oxygen concentrations between 1% and 16% (v/v), at a constant heater temperature of 650 °C. The oxygen sensor, based on the Sono-STFO40 sensing layer, shows good sensitivity, low power consumption (80 mW), and short response time (25 s). These performance are comparable to those exhibited by state-of-the-art O2 sensors based on STFO60, thus proving Sono-STFO40 to be a material suitable for oxygen detection in harsh environments.
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http://dx.doi.org/10.3390/s150717495 | DOI Listing |
Psychon Bull Rev
January 2025
Institute of Psychology, University of Lausanne, Lausanne, Switzerland.
Colour is an integral part of natural and constructed environments. For many, it also has an aesthetic appeal, with some colours being more pleasant than others. Moreover, humans seem to systematically and reliably associate colours with emotions, such as yellow with joy, black with sadness, light colours with positive and dark colours with negative emotions.
View Article and Find Full Text PDFSci Rep
January 2025
Advanced Power and Energy Center (APEC), Electrical Engineering Department, Khalifa University, Abu Dhabi, UAE.
Although detailed analytical models for droop-controlled microgrids are available, they are computationally complex and do not consider real-time variations in microgrid parameters and operating conditions. This paper proposes Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) to identify the dominant modes in droop-controlled inverter-based microgrids (IBMGs) using local real-time measurements. In the proposed approach, a short-duration small disturbance is applied to the selected DG's active power droop gain, and then, the system's dominant modes are estimated from its local measurements.
View Article and Find Full Text PDFZhongguo Zhong Yao Za Zhi
December 2024
State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700, China.
This study aims to identify the main chemical compounds, investigate the effects of different drying methods on the quality, and determine the appropriate drying method of Callicarpae Nudiflorae Folium. UPLC-UV-Q-TOF-MS was employed to characterize and identify 35 main compounds, including phenylethanoid glycosides, flavonoids, and iridoids in Callicarpae Nudiflorae Folium. A method for the simultaneous determination of 8 compounds with strong UV absorption and high content was established to evaluate the quality of Callicarpae Nudiflorae Folium dried by different methods.
View Article and Find Full Text PDFInt J Sports Physiol Perform
January 2025
Department of Exercise Physiology, Faculty of Physical Education and Sport Sciences, University of Guilan, Rasht, Iran.
Purpose: This study aimed to investigate the impact of a 6-week upper-body plyometric-training (PT) program with varying volumes on the immunoendocrine, physiological parameters, and physical performance adaptations in male volleyball players.
Methods: Twenty-four trained college players were randomly allocated into 3 groups with 8 participants. Each group performed 5 exercises at maximal effort with differences in volume: low (3 sets of 7 repetitions), moderate (3 sets of 10 repetitions), and high (3 sets of 13 repetitions).
J Neural Eng
January 2025
ECE & Neurology, University of Texas at Austin, 301 E. Dean Keeton St. C2100, Austin, Texas, 78712-1139, UNITED STATES.
Objective: A motor imagery (MI)-based brain-computer interface (BCI) enables users to engage with external environments by capturing and decoding electroencephalography (EEG) signals associated with the imagined movement of specific limbs. Despite significant advancements in BCI technologies over the past 40 years, a notable challenge remains: many users lack BCI proficiency, unable to produce sufficiently distinct and reliable MI brain patterns, hence leading to low classification rates in their BCIs. The objective of this study is to enhance the online performance of MI-BCIs in a personalized, biomarker-driven approach using transcranial alternating current stimulation (tACS).
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