scholarly journals Monitoring Electrical Biasing of Pb(Zr0.2Ti0.8)O3 Ferroelectric Thin Films In Situ by DPC-STEM Imaging

Materials ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4749
Author(s):  
Alexander Vogel ◽  
Martin F. Sarott ◽  
Marco Campanini ◽  
Morgan Trassin ◽  
Marta D. Rossell
Keyword(s):  
Thin Film ◽  
Real Time ◽  
Data Storage ◽  
Ferroelectric Properties ◽  
Polarization State ◽  
Ferroelectric Materials ◽  
Time Data ◽  
Transmission Electron ◽  
The Impact

Increased data storage densities are required for the next generation of nonvolatile random access memories and data storage devices based on ferroelectric materials. Yet, with intensified miniaturization, these devices face a loss of their ferroelectric properties. Therefore, a full microscopic understanding of the impact of the nanoscale defects on the ferroelectric switching dynamics is crucial. However, collecting real-time data at the atomic and nanoscale remains very challenging. In this work, we explore the ferroelectric response of a Pb(Zr0.2Ti0.8)O3 thin film ferroelectric capacitor to electrical biasing in situ in the transmission electron microscope. Using a combination of high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and differential phase contrast (DPC)-STEM imaging we unveil the structural and polarization state of the ferroelectric thin film, integrated into a capacitor architecture, before and during biasing. Thus, we can correlate real-time changes in the DPC signal with the presence of misfit dislocations and ferroelastic domains. A reduction in the domain wall velocity of 24% is measured in defective regions of the film when compared to predominantly defect-free regions.

scholarly journals MOSAiC goes O2A - Arctic Expedition Data Flow from Observations to Archives

2020 ◽  
Author(s):  
Antonia Immerz ◽  
Angela Schaefer ◽  
Keyword(s):  
Data Management ◽  
Real Time ◽  
Data Storage ◽  
Data Flow ◽  
Global Climate ◽  
Research Infrastructure ◽  
The Arctic ◽  
Sample Collection ◽  
Time Data

<p>During the largest polar expedition in history starting in September 2019, the German research icebreaker Polarstern spends a whole year drifting with the ice through the Arctic Ocean. The MOSAiC expedition takes the closest look ever at the Arctic even throughout the polar winter to gain fundamental insights and most unique on-site data for a better understanding of global climate change. Hundreds of researchers from 20 countries are involved. Scientists will use the in situ gathered data instantaneously in near-real time modus as well as long afterwards all around the globe taking climate research to a completely new level. Hence, proper data management, sampling strategies beforehand, and monitoring actual data flow as well as processing, analysis and sharing of data during and long after the MOSAiC expedition are the most essential tools for scientific gain and progress.</p><p>To prepare for that challenge we adapted and integrated the research data management framework <strong>O2A </strong>“Data flow from <strong>O</strong>bservations <strong>to</strong> <strong>A</strong>rchives” to the needs of the MOSAiC expedition on board Polarstern as well as on land for data storage and access at the Alfred Wegener Institute Computing and Data Center in Bremerhaven, Germany. Our <strong>O2A</strong>-framework assembles a modular research infrastructure comprising a collection of tools and services. These components allow researchers to register all necessary sensor metadata beforehand linked to automatized data ingestion and to ensure and monitor data flow as well as to process, analyze, and publish data to turn the most valuable and uniquely gained arctic data into scientific outcomes. The framework further allows for the integration of data obtained with discrete sampling devices into the data flow.</p><p>These requirements have led us to adapt the generic and cost-effective framework O2A to enable, control, and access the flow of sensor observations to archives in a cloud-like infrastructure on board Polarstern and later on to land based repositories for international availability.</p><p>Major roadblocks of the MOSAiC-O2A data flow framework are (i) the increasing number and complexity of research platforms, devices, and sensors, (ii) the heterogeneous interdisciplinary driven requirements towards, e. g., satellite data, sensor monitoring, in situ sample collection, quality assessment and control, processing, analysis and visualization, and (iii) the demand for near real time analyses on board as well as on land with limited satellite bandwidth.</p><p>The key modules of O2A's digital research infrastructure established by AWI are implementing the FAIR principles:</p><ul><li><strong>SENSORWeb</strong>, to register sensor applications and sampling devices and capture controlled meta data before and alongside any measurements in the field</li> <li><strong>Data ingest</strong>, allowing researchers to feed data into storage systems and processing pipelines in a prepared and documented way, at best in controlled near real-time data streams</li> <li><strong>Dashboards </strong>allowing researchers to find and access data and share and collaborate among partners</li> <li><strong>Workspace</strong> enabling researchers to access and use data with research software utilizing a cloud-based virtualized infrastructure that allows researchers to analyze massive amounts of data on the spot</li> <li><strong>Archiving </strong>and<strong> publishing data </strong>via repositories and Digital Object Identifiers (DOI)</li> </ul>

Growth kinetics of Al2Cu in an Al-1.5Cu thin film by in Situ TEM

1993 ◽  
Vol 51 ◽  
pp. 1172-1173
Author(s):  
M. Park ◽  
S.J. Krause ◽  
S.R. Wilson
Keyword(s):  
Thin Film ◽  
In Situ Tem ◽  
Collector Plate ◽  
Transmission Electron ◽  
Device Processing ◽  
Corrosion Susceptibility ◽  
Precipitation Phenomena ◽  
Semiconductor Chips ◽  
Kinetics Of

Cu alloying in Al interconnection lines on semiconductor chips improves their resistance to electromigration and hillock growth. Excess Cu in Al can result in the formation of Cu-rich Al2Cu (θ) precipitates. These precipitates can significantly increase corrosion susceptibility due to the galvanic action between the θ-phase and the adjacent Cu-depleted matrix. The size and distribution of the θ-phase are also closely related to the film susceptibility to electromigration voiding. Thus, an important issue is the precipitation phenomena which occur during thermal device processing steps. In bulk alloys, it was found that the θ precipitates can grow via the grain boundary “collector plate mechanism” at rates far greater than allowed by volume diffusion. In a thin film, however, one might expect that the growth rate of a θ precipitate might be altered by interfacial diffusion. In this work, we report on the growth (lengthening) kinetics of the θ-phase in Al-Cu thin films as examined by in-situ isothermal aging in transmission electron microscopy (TEM).

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

Microstructural and Ferroelectric Properties of a Chemical Solution Deposited Epitaxial PbZr0.5 Ti0.5O3 Thin Film on a SrRuO3/SrTiO3 Substrate

1999 ◽  
Vol 14 (4) ◽  
pp. 1190-1193 ◽  
Author(s):  
J. H. Kim ◽  
A. T. Chien ◽  
F. F. Lange ◽  
L. Wills
Keyword(s):  
Thin Film ◽  
Ferroelectric Properties ◽  
Chemical Solution ◽  
X Ray Diffraction ◽  
Solution Deposition ◽  
Chemical Solution Deposition Method ◽  
Transmission Electron ◽  
Saturation Polarization ◽  
Pzt Thin Film ◽  
Relationship Of

Epitaxial PbZr0.5Ti0.5O3 (PZT) thin films were grown on top of a SrRuO3 epitaxial electrode layer on a (100) SrTiO3 substrate by the chemical solution deposition method at 600 °C. The microstructure of the PZT thin film was investigated by x-ray diffraction and transmission electron microscopy, and the ferroelectric properties were measured using the Ag/PZT/SRO capacitor structure. The PZT thin film has the epitaxial orientational relationship of (001) [010]PZT ║ (001) [010]SRO ║ (001) [010]STO with the substrate. The remnant (Pr ) and saturation polarization (Ps) density were measured to be Pr ~ 51.4 µC/cm2 and Ps ~ 62.1 µC/cm2 at 5 V, respectively. Ferroelectric fatigue measurements show that the net-switching polarization begins to drop (to 98% of its initial value) after 7 × 108 cycles.

IIOT and Real Time Data Analytics - Maximizing the Impact on Safety and Productivity

2021 ◽  
Author(s):  
Ryan Daher ◽  
Nesma Aldash
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Data Analytics ◽  
Contact Tracing ◽  
Time Data ◽  
Seamless Integration ◽  
Location Services ◽  
Industrial Internet ◽  
Potential Applications ◽  
The Impact

Abstract With the global push towards Industry 4.0, a number of leading companies and organizations have invested heavily in Industrial Internet of Things (IIOT's) and acquired a massive amount of data. But data without proper analysis that converts it into actionable insights is just more information. With the advancement of Data analytics, machine learning, artificial intelligence, numerous methods can be used to better extract value out of the amassed data from various IIOTs and leverage the analysis to better make decisions impacting efficiency, productivity, optimization and safety. This paper focuses on two case studies- one from upstream and one from downstream using RTLS (Real Time Location Services). Two types of challenges were present: the first one being the identification of the location of all personnel on site in case of emergency and ensuring that all have mustered in a timely fashion hence reducing the time to muster and lessening the risks of Leaving someone behind. The second challenge being the identification of personnel and various contractors, the time they entered in productive or nonproductive areas and time it took to complete various tasks within their crafts while on the job hence accounting for efficiency, productivity and cost reduction. In both case studies, advanced analytics were used, and data collection issues were encountered highlighting the need for further and seamless integration between data, analytics and intelligence is needed. Achievements from both cases were visible increase in productivity and efficiency along with the heightened safety awareness hence lowering the overall risk and liability of the operation. Novel/Additive Information: The results presented from both studies have highlighted other potential applications of the IIOT and its related analytics. Pertinent to COVID-19, new application of such approach was tested in contact tracing identifying workers who could have tested positive and tracing back to personnel that have been in close proximity and contact therefore reducing the spread of COVID. Other application of the IIOT and its related analytics has also been tested in crane, forklift and heavy machinery proximity alert reducing the risk of accidents.

scholarly journals Tracking Metamorphic Dehydration Reactions in Real Time with Transmission Small- and Wide-Angle Synchrotron X-ray Scattering: the Case of Gypsum Dehydration

2020 ◽  
Vol 61 (6) ◽  
Author(s):  
C E Schrank ◽  
K Gioseffi ◽  
T Blach ◽  
O Gaede ◽  
A Hawley ◽  
...  
Keyword(s):  
Real Time ◽  
Wide Angle ◽  
Length Scales ◽  
X Ray ◽  
Rock Samples ◽  
X Ray Scattering ◽  
Dehydration Reactions ◽  
The Impact ◽  
Ray Scattering

Abstract We present a review of a unique non-destructive method for the real-time monitoring of phase transformations and nano-pore evolution in dehydrating rocks: transmission small- and wide-angle synchrotron X-ray scattering (SAXS/WAXS). It is shown how SAXS/WAXS can be applied to investigating rock samples dehydrated in a purpose-built loading cell that allows the coeval application of high temperature, axial confinement, and fluid pressure or flow to the specimen. Because synchrotron sources deliver extremely bright monochromatic X-rays across a wide energy spectrum, they enable the in situ examination of confined rock samples with thicknesses of ≤ 1 mm at a time resolution of order seconds. Hence, fast kinetics with reaction completion times of about hundreds of seconds can be tracked. With beam sizes of order tens to hundreds of micrometres, it is possible to monitor multiple interrogation points in a sample with a lateral extent of a few centimetres, thus resolving potential lateral spatial effects during dehydration and enlarging sample statistics significantly. Therefore, the SAXS/WAXS method offers the opportunity to acquire data on a striking range of length scales: for rock samples with thicknesses of ≤ 10-3 m and widths of 10-2 m, a lateral interrogation-point spacing of ≥ 10-5 m can be achieved. Within each irradiated interrogation-point volume, information concerning pores with sizes between 10-9 and 10-7 m and the crystal lattice on the scale of 10-10 m is acquired in real time. This article presents a summary of the physical principles underpinning transmission X-ray scattering with the aim of providing a guide for the design and interpretation of time-resolved SAXS/WAXS experiments. It is elucidated (1) when and how SAXS data can be used to analyse total porosity, internal surface area, and pore-size distributions in rocks on length scales from ∼1 to 300 nm; (2) how WAXS can be employed to track lattice transformations in situ; and (3) which limitations and complicating factors should be considered during experimental design, data analysis, and interpretation. To illustrate the key capabilities of the SAXS/WAXS method, we present a series of dehydration experiments on a well-studied natural gypsum rock: Volterra alabaster. Our results demonstrate that SAXS/WAXS is excellently suited for the in situ tracking of dehydration kinetics and the associated evolution of nano-pores. The phase transformation from gypsum to bassanite is correlated directly with nano-void growth on length scales between 1 and 11 nm for the first time. A comparison of the SAXS/WAXS kinetic results with literature data emphasises the need for future dehydration experiments on rock specimens because of the impact of rock fabric and the generally heterogeneous and transient nature of dehydration reactions in nature. It is anticipated that the SAXS/WAXS method combined with in situ loading cells will constitute an invaluable tool in the ongoing quest for understanding dehydration and other mineral replacement reactions in rocks quantitatively.

scholarly journals In situ wide-field visualization of palladium hydrogenation

2020 ◽  
Author(s):  
Chongjun Jin ◽  
Nicholas Fang ◽  
Xiaoyi She ◽  
Huifeng Du ◽  
Yang Shen ◽  
...  
Keyword(s):  
Real Time ◽  
Hydrogen Diffusion ◽  
Fast Response ◽  
Wide Field ◽  
Ion Diffusion ◽  
Optical Contrast ◽  
Self Organized ◽  
Transmission Electron ◽  
Kinetics Of

Abstract Visualizing hydrogenation processes in metals in real-time is important to various hydrogen-involved applications. However, observing hydrogen diffusion was limited by transmission electron microscopy, and the kinetics of hydrogenation in the interior of the metals was not reported. Here we proposed an optical microscopy-based visualization of palladium hydrogenation from diffusion surface to the interior by introducing a fast-response mechanical platform that transforms the hydrogen diffusion into self-organized ordered wrinkles with sharp optical contrast. This platform is an Au/Pd double layer on elastomer which results in directional hydrogenation from sidewall to the interior. The kinetics of hydrogenation in the interior of the palladium along the diffusion direction was monitored in real-time. This platform will enable in-situ visualization of atom/ion diffusion on metals that are crucial in energy storage and hydrogen detection.

scholarly journals Analisa Real-Time Data log honeypot menggunakan Algoritma K-Means pada serangan Distributed Denial of Service

Repositor ◽  
2020 ◽  
Vol 2 (5) ◽  
pp. 541
Author(s):  
Denni Septian Hermawan ◽  
Syaifuddin Syaifuddin ◽  
Diah Risqiwati
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Denial Of Service ◽  
The Internet ◽  
Distributed Denial Of Service ◽  
Time Data ◽  
Local Networks ◽  
Real Time Data ◽  
Internet Networks ◽  
Data Log

AbstrakJaringan internet yang saat ini di gunakan untuk penyimpanan data atau halaman informasi pada website menjadi rentan terhadap serangan, untuk meninkatkan keamanan website dan jaringannya, di butuhkan honeypot yang mampu menangkap serangan yang di lakukan pada jaringan lokal dan internet. Untuk memudahkan administrator mengatasi serangan digunakanlah pengelompokan serangan dengan metode K-Means untuk mengambil ip penyerang. Pembagian kelompok pada titik cluster akan menghasilkan output ip penyerang.serangan di ambil sercara realtime dari log yang di miliki honeypot dengan memanfaatkan MHN.Abstract The number of internet networks used for data storage or information pages on the website is vulnerable to attacks, to secure the security of their websites and networks, requiring honeypots that are capable of capturing attacks on local networks and the internet. To make it easier for administrators to tackle attacks in the use of attacking groupings with the K-Means method to retrieve the attacker ip. Group divisions at the cluster point will generate the ip output of the attacker. The strike is taken as realtime from the logs that have honeypot by utilizing the MHN.

scholarly journals Drilling Efficiency Improvement and Rate of Penetration Optimization by Machine Learning and Data Analytics

2020 ◽  
Vol 5 (3) ◽  
pp. 381-394
Author(s):  
Sridharan Chandrasekaran ◽  
G. Suresh Kumar
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Data Storage ◽  
Predictive Accuracy ◽  
Empirical Models ◽  
Operational Parameters ◽  
Time Data ◽  
Bottom Line ◽  
Rate Of Penetration ◽  
Real Time Data

Rate of Penetration (ROP) is one of the important factors influencing the drilling efficiency. Since cost recovery is an important bottom line in the drilling industry, optimizing ROP is essential to minimize the drilling operational cost and capital cost. Traditional the empirical models are not adaptive to new lithology changes and hence the predictive accuracy is low and subjective. With advancement in big data technologies, real- time data storage cost is lowered, and the availability of real-time data is enhanced. In this study, it is shown that optimization methods together with data models has immense potential in predicting ROP based on real time measurements on the rig. A machine learning based data model is developed by utilizing the offset vertical wells’ real time operational parameters while drilling. Data pre-processing methods and feature engineering methods modify the raw data into a processed data so that the model learns effectively from the inputs. A multi – layer back propagation neural network is developed, cross-validated and compared with field measurements and empirical models.

scholarly journals On the Quality of Real-Time Altimeter Gridded Fields: Comparison with In Situ Data

2009 ◽  
Vol 26 (3) ◽  
pp. 556-569 ◽  
Author(s):  
Ananda Pascual ◽  
Christine Boone ◽  
Gilles Larnicol ◽  
Pierre-Yves Le Traon
Keyword(s):  
Real Time ◽  
Sea Level ◽  
Tide Gauge ◽  
Deep Ocean ◽  
Velocity Estimation ◽  
Time Data ◽  
In Situ Data ◽  
Delayed Time

Abstract The timeliness of satellite altimeter measurements has a significant effect on their value for operational oceanography. In this paper, an Observing System Experiment (OSE) approach is used to assess the quality of real-time altimeter products, a key issue for robust monitoring and forecasting of the ocean state. In addition, the effect of two improved geophysical corrections and the number of missions that are combined in the altimeter products are also analyzed. The improved tidal and atmospheric corrections have a significant effect in coastal areas (0–100 km from the shore), and a comparison with tide gauge observations shows a slightly better agreement with the gridded delayed-time sea level anomalies (SLAs) with two altimeters [Jason-1 and European Remote Sensing Satellite-2 (ERS-2)/Envisat] using the new geophysical corrections (mean square differences in percent of tide gauge variance of 35.3%) than those with four missions [Jason-1, ERS/Envisat, Ocean Topography Experiment (TOPEX)/Poseidoninterlaced, and Geosat Follow-On] but using the old corrections (36.7%). In the deep ocean, however, the correction improvements have little influence. The performance of fast delivery products versus delayed-time data is compared using independent in situ data (tide gauge and drifter data). It clearly highlights the degradation of real-time SLA maps versus the delayed-time SLA maps: four altimeters are needed in real time to get the similar quality performance as two altimeters in delayed time (sea level error misfit around 36%, and zonal and meridional velocity estimation errors of 27% and 33%, respectively). This study proves that the continuous improvement of geophysical corrections is very important, and that it is essential to stay above a minimum threshold of four available altimetric missions to capture the main space and time oceanic scales in fast delivery products.

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