scholarly journals Dense, low-power sensor network for three-dimensional thermal characterization of large-scale atria spaces

2012 ◽  
Author(s):  
Nan-Wei Gong ◽  
Laura Ware ◽  
Steve Ray ◽  
Gary Ware ◽  
Brett Leida ◽  
...  
Keyword(s):  
Low Power ◽  
Sensor Network ◽  
Large Scale ◽  
Three Dimensional ◽  
Thermal Characterization ◽  
Power Sensor

Rapid Three-Dimensional Thermal Characterization of Large-Scale Computing Facilities

2008 ◽  
Vol 31 (2) ◽  
pp. 444-448 ◽  
Author(s):  
H.F. Hamann ◽  
J.A. Lacey ◽  
M. O'Boyle ◽  
R.R. Schmidt ◽  
M. Iyengar
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Thermal Characterization ◽  
Large Scale Computing

Thermal characterization of ABS-Graphene blended three dimensional printed functional prototypes for electro chemical energy storage

2018 ◽  
Vol 1 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Kamaljit Singh Boparai ◽  
Rupinder Singh
Keyword(s):  
Energy Storage ◽  
Structural Changes ◽  
Fused Deposition Modeling ◽  
Morphological Changes ◽  
Three Dimensional ◽  
Thermal Characterization ◽  
Chemical Energy ◽  
Flow Index ◽  
Fused Deposition

This study highlights the thermal characterization of ABS-Graphene blended three dimensional (3D) printed functional prototypes by fused deposition modeling (FDM) process. These functional prototypes have some applications as electro-chemical energy storage devices (EESD). Initially, the suitability of ABS-Graphene composite material for FDM applications has been examined by melt flow index (MFI) test. After establishing MFI, the feedstock filament for FDM has been prepared by an extrusion process. The fabricated filament has been used for printing 3D functional prototypes for printing of in-house EESD. The differential scanning calorimeter (DSC) analysis was conducted to understand the effect on glass transition temperature with the inclusion of Graphene (Gr) particles. It has been observed that the reinforced Gr particles act as a thermal reservoir (sink) and enhances its thermal/electrical conductivity. Also, FT-IR spectra realized the structural changes with the inclusion of Gr in ABS matrix. The results are supported by scanning electron microscopy (SEM) based micrographs for understanding the morphological changes.

scholarly journals Characterization of Polycaprolactone Nanohydroxyapatite Composites with Tunable Degradability Suitable for Indirect Printing

Polymers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 295
Author(s):  
Stephanie E. Doyle ◽  
Lauren Henry ◽  
Ellen McGennisken ◽  
Carmine Onofrillo ◽  
Claudia Di Bella ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Large Scale ◽  
Three Dimensional ◽  
Cell Number ◽  
Compressive Modulus ◽  
Degradation Rates ◽  
Scaffold Materials ◽  
Natural Tissue ◽  
Complete Regeneration

Degradable bone implants are designed to foster the complete regeneration of natural tissue after large-scale loss trauma. Polycaprolactone (PCL) and hydroxyapatite (HA) composites are promising scaffold materials with superior mechanical and osteoinductive properties compared to the single materials. However, producing three-dimensional (3D) structures with high HA content as well as tuneable degradability remains a challenge. To address this issue and create homogeneously distributed PCL-nanoHA (nHA) scaffolds with tuneable degradation rates through both PCL molecular weight and nHA concentration, we conducted a detailed characterisation and comparison of a range of PCL-nHA composites across three molecular weight PCLs (14, 45, and 80 kDa) and with nHA content up to 30% w/w. In general, the addition of nHA results in an increase of viscosity for the PCL-nHA composites but has little effect on their compressive modulus. Importantly, we observe that the addition of nHA increases the rate of degradation compared to PCL alone. We show that the 45 and 80 kDa PCL-nHA groups can be fabricated via indirect 3D printing and have homogenously distributed nHA even after fabrication. Finally, the cytocompatibility of the composite materials is evaluated for the 45 and 80 kDa groups, with the results showing no significant change in cell number compared to the control. In conclusion, our analyses unveil several features that are crucial for processing the composite material into a tissue engineered implant.

scholarly journals Synthesis, Spectral, Structural and Thermal Characterization of Inorganic Crystal: Phenyl Trimethylammonium Tetrachlorocobaltate

2019 ◽  
Vol 31 (8) ◽  
pp. 1779-1784
Author(s):  
V. Mohanraj ◽  
R. Pavithra ◽  
M. Thenmozhi ◽  
R. Umarani
Keyword(s):  
Three Dimensional ◽  
Thermal Characterization ◽  
Dimensional Structure ◽  
X Ray Diffraction ◽  
Monoclinic Crystal ◽  
Evaporation Technique ◽  
Ft Ir ◽  
Thermal Stability Of ◽  
Ft Ir Spectroscopy

Phenyl trimethylammonium tetrachlorocobaltate, crystals were grown by slow evaporation technique. The crystal was bright, transparent. The three dimensional structure of the phenyl trimethylammonium tetrachlorocobaltate was obtained from single crystal X-ray diffraction studies. The molecule belongs to monoclinic crystal system with C2/c space group. The presence of functional groups and modes of vibrations were identified by FT-IR spectroscopy. 1H NMR spectroscopy was also used to characterise the compound and the thermal stability of the crystal was established by TGA/DT analysis. This work undergoes phase transition which makes the study interesting.

scholarly journals Architecture and Design of a Spiking Neuron Processor Core Towards the Design of a Large-scale Event-Driven 3D-NoC-based Neuromorphic Processor

2020 ◽  
Vol 77 ◽  
pp. 04003
Author(s):  
Mark Ogbodo ◽  
Khanh Dang ◽  
Fukuchi Tomohide ◽  
Abderazek Abdallah
Keyword(s):  
Low Power ◽  
Large Scale ◽  
Fault Tolerant ◽  
Three Dimensional ◽  
Spiking Neuron ◽  
Chip Area ◽  
Processor Core ◽  
Neuromorphic Systems ◽  
Event Driven ◽  
On Chip

Neuromorphic computing tries to model in hardware the biological brain which is adept at operating in a rapid, real-time, parallel, low power, adaptive and fault-tolerant manner within a volume of 2 liters. Leveraging the event driven nature of Spiking Neural Network (SNN), neuromorphic systems have been able to demonstrate low power consumption by power gating sections of the network not driven by an event at any point in time. However, further exploration in this field towards the building of edge application friendly agents and efficient scalable neuromorphic systems with large number of synapses necessitates the building of small-sized low power spiking neuron processor core with efficient neuro-coding scheme and fault tolerance. This paper presents a spiking neuron processor core suitable for an event-driven Three-Dimensional Network on Chip (3D-NoC) SNN based neuromorphic systems. The spiking neuron Processor core houses an array of leaky integrate and fire (LIF) neurons, and utilizes a crossbar memory in modelling the synapses, all within a chip area of 0.12mm2 and was able to achieves an accuracy of 95.15% on MNIST dataset inference.

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