Fabrication of Ordered, Large Scale, Horizontally-Aligned Si Nanowire Arrays Based on an In Situ Hard Mask Block Copolymer Approach

2013 ◽  
Vol 26 (8) ◽  
pp. 1207-1216 ◽  
Author(s):  
Tandra Ghoshal ◽  
Ramsankar Senthamaraikannan ◽  
Matthew T. Shaw ◽  
Justin D. Holmes ◽  
Michael A. Morris
2014 ◽  
Author(s):  
Tandra Ghoshal ◽  
Ramsankar Senthamaraikannan ◽  
Matthew T. Shaw ◽  
Justin D. Holmes ◽  
Michael A. Morris

Nanoscale ◽  
2016 ◽  
Vol 8 (4) ◽  
pp. 2177-2187 ◽  
Author(s):  
Tandra Ghoshal ◽  
Christos Ntaras ◽  
John O'Connell ◽  
Matthew T. Shaw ◽  
Justin D. Holmes ◽  
...  

Nanoscale ◽  
2012 ◽  
Vol 4 (24) ◽  
pp. 7743 ◽  
Author(s):  
Tandra Ghoshal ◽  
Ramsankar Senthamaraikannan ◽  
Matthew T. Shaw ◽  
Justin D. Holmes ◽  
Michael A. Morris
Keyword(s):  

2006 ◽  
Vol 931 ◽  
Author(s):  
Jing Zhu ◽  
Jun Luo ◽  
Changqiang Chen ◽  
Yu Shi ◽  
Xiaohua Liu ◽  
...  

ABSTRACTOne-dimensional (1D) nano-materials have attracted a plenty of attention due to their novel structures and properties. Our group has carried out researches on synthesis, structure and property of 1D nano-materials, which are introduced in this paper. First, size effects on the crystal structure of Ag nanowires and on Young's modulus in [0001] oriented ZnO nanowires, respectively, have been revealed and modeled. The former is concerning the systemic energy of an individual Ag nanowire. The latter is caused by the surface stiffening effect arising from surface relaxation induced bond length contractions in the ZnO nanowires. Second, structures of 1D helical nano-materials including SWCNT (single-walled carbon nanotube), B-DNA and MWCNT (mutli-walled carbon nanotube) have been studied. It is shown that there is strong orientation dependence of diffraction intensities from SWCNT and B-DNA, which can even result in certain layer lines missing in their diffraction patterns. Also, it is demonstrated that high-resolution transmission electron microscope (TEM) images of sidewall regions of MWCNTs are not structural ones and from the interference of the {0002} and the {1011} diffraction waves. Third, arrays of four types of 1D heterojunctions have been synthesized. Among these 1D heterojunctions, the interfacial structures of the Ni/MWCNT/a-CNT(amorphous carbon nanotube) heterojunctions show that multiple outer walls in the MWCNTs can simultaneously participate in electrical transport. The electrical properties of the Ni/MWCNT/a-CNT and the Ag/a-CNT heterojunctions have been measured. As a result, it is found that the contacts between the Ag nanowires and the a-CNTs are ohmic ones with universal significance, and that each Ni/MWCNT/ a-CNT contains two diodes connected in series face-to-face. Moreover, most of the diodes have the most nearly ideal characteristics of Schottky contacts, indicated by quantitative analysis with the thermionic emission theory. Last, our group has developed a novel technique for rapidly producing large-area highly-oriented Si nanowire arrays on Si wafers by scratching the Si surface with metal nanoparticles near room temperature in HF solution. By this method, Si nanowires with desirable axial crystallographic directions, desirable doping characteristics and remarkable antireflection property can be readily obtained. The Si nanowire arrays have the potential applicability as an antireflective layer for photovoltaic devices and optical detectors. Furthermore, a combination of this method and the nanosphere lithography has been developed to fabricate large-scale Si and Si1−xGex quantum dot arrays with controllable height, diameter and center-to-center distance.


ACS Nano ◽  
2021 ◽  
Author(s):  
Tandra Ghoshal ◽  
Ramsankar Senthamaraikannan ◽  
Matthew T. Shaw ◽  
Ross Lundy ◽  
Andrew Selkirk ◽  
...  

2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e16-e16
Author(s):  
Ahmed Moussa ◽  
Audrey Larone-Juneau ◽  
Laura Fazilleau ◽  
Marie-Eve Rochon ◽  
Justine Giroux ◽  
...  

Abstract BACKGROUND Transitions to new healthcare environments can negatively impact patient care and threaten patient safety. Immersive in situ simulation conducted in newly constructed single family room (SFR) Neonatal Intensive Care Units (NICUs) prior to occupancy, has been shown to be effective in testing new environments and identifying latent safety threats (LSTs). These simulations overlay human factors to identify LSTs as new and existing process and systems are implemented in the new environment OBJECTIVES We aimed to demonstrate that large-scale, immersive, in situ simulation prior to the transition to a new SFR NICU improves: 1) systems readiness, 2) staff preparedness, 3) patient safety, 4) staff comfort with simulation, and 5) staff attitude towards culture change. DESIGN/METHODS Multidisciplinary teams of neonatal healthcare providers (HCP) and parents of former NICU patients participated in large-scale, immersive in-situ simulations conducted in the new NICU prior to occupancy. One eighth of the NICU was outfitted with equipment and mannequins and staff performed in their native roles. Multidisciplinary debriefings, which included parents, were conducted immediately after simulations to identify LSTs. Through an iterative process issues were resolved and additional simulations conducted. Debriefings were documented and debriefing transcripts transcribed and LSTs classified using qualitative methods. To assess systems readiness and staff preparedness for transition into the new NICU, HCPs completed surveys prior to transition, post-simulation and post-transition. Systems readiness and staff preparedness were rated on a 5-point Likert scale. Average survey responses were analyzed using dependent samples t-tests and repeated measures ANOVAs. RESULTS One hundred eight HCPs and 24 parents participated in six half-day simulation sessions. A total of 75 LSTs were identified and were categorized into eight themes: 1) work organization, 2) orientation and parent wayfinding, 3) communication devices/systems, 4) nursing and resuscitation equipment, 5) ergonomics, 6) parent comfort; 7) work processes, and 8) interdepartmental interactions. Prior to the transition to the new NICU, 76% of the LSTs were resolved. Survey response rate was 31%, 16%, 7% for baseline, post-simulation and post-move surveys, respectively. System readiness at baseline was 1.3/5,. Post-simulation systems readiness was 3.5/5 (p = 0.0001) and post-transition was 3.9/5 (p = 0.02). Staff preparedness at baseline was 1.4/5. Staff preparedness post-simulation was 3.3/5 (p = 0.006) and post-transition was 3.9/5 (p = 0.03). CONCLUSION Large-scale, immersive in situ simulation is a feasible and effective methodology for identifying LSTs, improving systems readiness and staff preparedness in a new SFR NICU prior to occupancy. However, to optimize patient safety, identified LSTs must be mitigated prior to occupancy. Coordinating large-scale simulations is worth the time and cost investment necessary to optimize systems and ensure patient safety prior to transition to a new SFR NICU.


2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.


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