An ultrafast-temporally-responsive flexible photodetector with high sensitivity based on high-crystallinity organic–inorganic perovskite nanoflake

Nanoscale ◽  
2017 ◽  
Vol 9 (34) ◽  
pp. 12718-12726 ◽  
Author(s):  
Wei Zheng ◽  
Richeng Lin ◽  
Zhaojun Zhang ◽  
Qixian Liao ◽  
Jiajun Liu ◽  
...  
Keyword(s):  
Early Warning ◽  
High Sensitivity ◽  
Wearable Devices ◽  
Inorganic Perovskite ◽  
High Crystallinity ◽  
Security Personnel ◽  
Flexible Photodetector

Flexible cameras are important early warning wearable devices to protect security personnel from dangerous events.

scholarly journals High-sensitivity of initial SrO growth on the residual resistivity in epitaxial thin films of SrRuO$$_3$$ on SrTiO$$_3$$ (001)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Uddipta Kar ◽  
Akhilesh Kr. Singh ◽  
Song Yang ◽  
Chun-Yen Lin ◽  
Bipul Das ◽  
...  
Keyword(s):  
Volume Fraction ◽  
High Sensitivity ◽  
Orthorhombic Phase ◽  
Residual Resistivity ◽  
Epitaxial Thin Films ◽  
Residual Resistivity Ratio ◽  
Resistivity Ratio ◽  
Growth Technique ◽  
X Ray ◽  
High Crystallinity

AbstractThe growth of SrRuO$$_3$$ 3 (SRO) thin film with high-crystallinity and low residual resistivity (RR) is essential to explore its intrinsic properties. Here, utilizing the adsorption-controlled growth technique, the growth condition of initial SrO layer on TiO$$_2$$ 2 -terminated SrTiO$$_3$$ 3 (STO) (001) substrate was found to be crucial for achieving a low RR in the resulting SRO film grown afterward. The optimized initial SrO layer shows a c(2 $$\times $$ × 2) superstructure that was characterized by electron diffraction, and a series of SRO films with different thicknesses (ts) were then grown. The resulting SRO films exhibit excellent crystallinity with orthorhombic-phase down to $$t \approx $$ t ≈ 4.3 nm, which was confirmed by high resolution X-ray measurements. From X-ray azimuthal scan across SRO orthorhombic (02 ± 1) reflections, we uncover four structural domains with a dominant domain of orthorhombic SRO [001] along cubic STO [010] direction. The dominant domain population depends on t, STO miscut angle ($$\alpha $$ α ), and miscut direction ($$\beta $$ β ), giving a volume fraction of about 92 $$\%$$ % for $$t \approx $$ t ≈ 26.6 nm and $$(\alpha , \beta ) \approx $$ ( α , β ) ≈ (0.14$$^{\mathrm{o}}$$ o , 5$$^{\mathrm{o}}$$ o ). On the other hand, metallic and ferromagnetic properties were well preserved down to t$$\approx $$ ≈ 1.2 nm. Residual resistivity ratio (RRR = $$\rho ({\mathrm{300 K}})$$ ρ ( 300 K ) /$$\rho ({\mathrm{5K}})$$ ρ ( 5 K ) ) reduces from 77.1 for t$$\approx $$ ≈ 28.5 nm to 2.5 for t$$\approx $$ ≈ 1.2 nm, while $$\rho ({\mathrm{5K}})$$ ρ ( 5 K ) increases from 2.5 $$\upmu \Omega $$ μ Ω cm for t$$\approx $$ ≈ 28.5 nm to 131.0 $$\upmu \Omega $$ μ Ω cm for t$$\approx $$ ≈ 1.2 nm. The ferromagnetic onset temperature ($$T'_{\mathrm{c}}$$ T c ′ ) of around 151 K remains nearly unchanged down to t$$\approx $$ ≈ 9.0 nm and decreases to 90 K for t$$\approx $$ ≈ 1.2 nm. Our finding thus provides a practical guideline to achieve high crystallinity and low RR in ultra-thin SRO films by simply adjusting the growth of initial SrO layer.

GROUNDWATER PROTECTION THROUGH EARLY DETECTION OF HYDROCARBON LEAKS

1985 ◽  
Vol 1985 (1) ◽  
pp. 263-265
Author(s):  
L. F. Donaghey
Keyword(s):  
Early Detection ◽  
Early Warning ◽  
Groundwater Protection ◽  
High Sensitivity ◽  
Leak Detection ◽  
Liquid Hydrocarbon ◽  
Storage Tanks ◽  
Current Technology ◽  
Detection Systems

ABSTRACT Early-warning hydrocarbon leak detection is a key to protecting groundwater from contamination by leaking storage tanks. This paper reviews the technology for vapor and liquid leak detection and evaluates methods of using it. Current technology offers both vapor and liquid hydrocarbon detectors. However, none that we tested was completely free of problems. Vapor detectors age and degrade in service. Liquid detectors lack high sensitivity. Of the different methods for early leak detection, vapor detectors respond in the shortest time. Detection systems need to be developed further to overcome remaining problems. In particular, they also need to be able to distinguish real tank leaks from normal hydrocarbon backgrounds.

scholarly journals Semiconductor Sensor With Loaded SnO2 Nanoparticles For Early Warning Of Indoor Fires

2019 ◽  
Vol Vol. 14, No.1 ◽  
pp. 37-42 ◽  
Author(s):  
Nelly Maksymovyc ◽  
Ludmila Oleksenko ◽  
Georgiy Fedorenko ◽  
Ganna Arinarkhova ◽  
Keyword(s):  
Early Warning ◽  
Tin Dioxide ◽  
Sno2 Nanoparticles ◽  
Sol Gel ◽  
Average Particle Size ◽  
High Sensitivity ◽  
Average Particle ◽  
Sensitive Layer ◽  
Semiconductor Sensor ◽  
Wide Range

Nanosized tin dioxide material with an average particle size of 10-11 nm was prepared by a sol-gel method. The material has been tested as a gas sensitive layer of a semiconductor sensor. Platinum was introduced into the gas sensitive layer to increase the sensor response to hydrogen. It was shown that the Pt-containing sensor has high sensitivity to hydrogen: its electrical resistance changes in 9.2 times in the presence of 22 ppm H2 in air. It was demonstrated that the sensor applicable to a wide range of H2 measurements in air (3-935 ppm) and has a fast dynamic response. The sensor demonstrates rather good reproducibility of its signal to H2 and withstands hydrogen overload (935 ppm) without a loss of its sensitivity to H2 microconcentration (22 ppm). The results are prospective for applying the sensor in the detectors for early warning of indoor fires.

High-sensitivity dual UV/NIR-excited luminescence thermometry by rare earth vanadate nanoparticles

2020 ◽  
Vol 49 (3) ◽  
pp. 911-922 ◽  
Author(s):  
Rafael Vieira Perrella ◽  
Paulo Cesar de Sousa Filho
Keyword(s):  
Rare Earth ◽  
High Performance ◽  
High Sensitivity ◽  
High Crystallinity ◽  
Excited Luminescence ◽  
Luminescence Thermometry

High-crystallinity Ln3+-doped YVO4 nanoparticles combine multiple emissions under dual UV/NIR excitation, promoting high performance self-referenced luminescence thermometry.

Donor–Acceptor Competition via Halide Vacancy Filling for Oxygen Detection of High Sensitivity and Stability by All‐Inorganic Perovskite Films

Small ◽  
2021 ◽  
Vol 17 (40) ◽  
pp. 2102733
Author(s):  
Weiwei Xing ◽  
Qianqian Yao ◽  
Wenpeng Zhu ◽  
He Jiang ◽  
Xiaoyue Zhang ◽  
...  
Keyword(s):  
High Sensitivity ◽  
Inorganic Perovskite ◽  
Oxygen Detection ◽  
Donor Acceptor

scholarly journals Multi-task deep learning for cardiac rhythm detection in wearable devices

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Jessica Torres-Soto ◽  
Euan A. Ashley
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Deep Learning ◽  
Biomedical Applications ◽  
Large Scale ◽  
High Sensitivity ◽  
Wearable Devices ◽  
Replication Cohort ◽  
Data Problem

Abstract Wearable devices enable theoretically continuous, longitudinal monitoring of physiological measurements such as step count, energy expenditure, and heart rate. Although the classification of abnormal cardiac rhythms such as atrial fibrillation from wearable devices has great potential, commercial algorithms remain proprietary and tend to focus on heart rate variability derived from green spectrum LED sensors placed on the wrist, where noise remains an unsolved problem. Here we develop DeepBeat, a multitask deep learning method to jointly assess signal quality and arrhythmia event detection in wearable photoplethysmography devices for real-time detection of atrial fibrillation. The model is trained on approximately one million simulated unlabeled physiological signals and fine-tuned on a curated dataset of over 500 K labeled signals from over 100 individuals from 3 different wearable devices. We demonstrate that, in comparison with a single-task model, our architecture using unsupervised transfer learning through convolutional denoising autoencoders dramatically improves the performance of atrial fibrillation detection from a F1 score of 0.54 to 0.96. We also include in our evaluation a prospectively derived replication cohort of ambulatory participants where the algorithm performed with high sensitivity (0.98), specificity (0.99), and F1 score (0.93). We show that two-stage training can help address the unbalanced data problem common to biomedical applications, where large-scale well-annotated datasets are hard to generate due to the expense of manual annotation, data acquisition, and participant privacy.

Pre-hospital use of early warning scores to improve detection and outcomes of sepsis

2021 ◽  
Vol 26 (3) ◽  
pp. 122-129
Author(s):  
Marina Maciver
Keyword(s):  
Patient Outcomes ◽  
Early Warning ◽  
Hospital Setting ◽  
High Sensitivity ◽  
Early Warning Score ◽  
Bibliographic Databases ◽  
Eligibility Criteria ◽  
Early Warning Scores ◽  
Life Threatening ◽  
Hospital Use

Sepsis is a life-threatening complication from infection. The early detection of sepsis pre-hospital is challenging. Early warning scores (EWS) are used in hospitals to identify deteriorating patients. The pre-hospital setting could be a beneficial extension to the use of EWSs. This review aimed to determine whether EWSs can identify patients with sepsis pre-hospital and predict patient outcomes. Bibliographic databases were searched for studies evaluating the pre-hospital use of EWSs. Studies were screened using eligibility criteria. Two studies examined the ability of pre-hospital EWSs to identify patients with critical illness, showing high sensitivity but low specificity. Four studies determined the prognostic effects of the National Early Warning Score (NEWS). The patients identified by NEWS to be high-risk were associated with worse outcomes. This systematic review demonstrated the successful use of EWSs in the pre-hospital setting, in identifying patients most at risk of deterioration and as a useful tool for decision-making.

scholarly journals Cost-Effective Fabrication of Transparent Strain Sensors via Micro-Scale 3D Printing and Imprinting

Nanomaterials ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 120
Author(s):  
Rui Wang ◽  
Xiaoyang Zhu ◽  
Luanfa Sun ◽  
Shuai Shang ◽  
Hongke Li ◽  
...  
Keyword(s):  
3D Printing ◽  
Health Monitoring ◽  
Strain Sensor ◽  
High Sensitivity ◽  
Wearable Devices ◽  
Strain Sensors ◽  
Expression Recognition ◽  
Wrist Flexion ◽  
Multiwalled Carbon ◽  
Flexible Strain Sensor

The development of strain sensors with high sensitivity and stretchability is essential for health monitoring, electronic skin, wearable devices, and human-computer interactions. However, sensors that combine high sensitivity and ultra-wide detection generally require complex preparation processes. Here, a novel flexible strain sensor with high sensitivity and transparency was proposed by filling a multiwalled carbon nanotube (MWCNT) solution into polydimethylsiloxane (PDMS) channel films fabricated via an electric field-driven (EFD) 3D printing and molding hybrid process. The fabricated flexible strain sensor with embedded MWCNT networks had superior gauge factors of 90, 285, and 1500 at strains of 6.6%, 14%, and 20%, respectively. In addition, the flexible strain sensors with an optical transparency of 84% offered good stability and durability with no significant change in resistance after 8000 stretch-release cycles. Finally, the fabricated flexible strain sensors with embedded MWCNT networks showed good practical performance and could be attached to the skin to monitor various human movements such as wrist flexion, finger flexion, neck flexion, blinking activity, food swallowing, and facial expression recognition. These are good application strategies for wearable devices and health monitoring.

scholarly journals The Early Warning And Response System (EWARS-TDR) For Dengue Outbreaks: Can It Also Be Applied To Chikungunya And Zika Outbreak Warning?

2021 ◽  
Author(s):  
Rocio Cardenas ◽  
Laith Hussain-Alkhateeb ◽  
David Benitez-Valladares ◽  
Gustavo Sanchez-Tejeda ◽  
Axel Kroeger
Keyword(s):  
Positive Predictive Value ◽  
Early Warning ◽  
Predictive Value ◽  
Large City ◽  
High Sensitivity ◽  
Surveillance Systems ◽  
Insect Vector ◽  
Alarm Signals ◽  
Response System ◽  
Dengue Outbreaks

Abstract Background. In the Americas, endemic countries for Aedes-borne diseases such as dengue, chikungunya, and Zika face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vector Aedes aegypti and Ae. albopictus. The Special Program for Research and Training in Tropical Diseases (TDR- WHO) has developed together with partners an early warning and Response System (EWARS) for dengue outbreaks based on a variety of alarm signals with a high sensitivity and positive predictive value (PPV). The question is if this tool can also be used for the prediction of Zika and chikungunya outbreaks.Methodology. We conducted in nine districts of Mexico and one large city in Colombia a retrospective analysis of epidemiological data (for the outbreak definition) and of climate and entomological data (as potential alarm indicators) produced by the national surveillance systems for dengue, chikungunya and Zika outbreak prediction covering the following outbreak years: for dengue 2012-2016, for Zika 2015-2017, for chikungunya 2014-2016. This period was divided into a “run in period” (to establish the “historical” pattern of the disease) and an “analysis period” (to identify sensitivity and PPV of outbreak prediction). Results. In Mexico, the sensitivity of alarm signals for correctly predicting an outbreak was 92% for dengue, and 97% for Zika (chikungunya data could not be obtained in Mexico); the PPV was 68% for dengue and 100% for Zika. The time period between alarm and start of the outbreak (i.e. the time available for early response activities) was for dengue 6-8 weeks and for Zika 3-5 weeks. In Colombia the sensitivity of the outbreak prediction was 92% for dengue, 93% for chikungunya and 100% for Zika; the PPV was 68% for dengue, 92% for chikungunya and 54% for Zika; the prediction distance was for dengue 3-5 weeks, for chikungunya 10-13 weeks and for Zika 6-10 weeks. Conclusion. The implementation of an early warning and response system (EWARS) could predict outbreaks of three Aedes borne diseases with a high sensitivity and positive predictive value and with a lag time long enough for preparing an adequate outbreak response in order to reduce the magnitude or avert the occurrence of outbreaks with their elevated social and economic tolls.

Sign in / Sign up

Export Citation Format

Share Document