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Gas sensing properties of single crystalline ZnO nanowires grown by thermal evaporation technique
Prabhakar Rai,리쥔찬,Rafiq Ahmad,한윤봉,이인환,유연태 한국물리학회 2013 Current Applied Physics Vol.13 No.8
The ZnO NWs were applied as effective material for the fabrication of ethanol (C2H5OH) and carbon monoxide (CO) gas sensor. The ZnO NWs were grown by thermal evaporation techniques on non-catalytic Si (100) substrates. The average width and length of ZnO NWswas 60 nmand 20 mm, respectively and they were single crystalline in nature. The maximumresponsewas 51.64 at 300 ℃ for 1000 ppm of CO gas, while 104.23 at 400 ℃ for 250 ppm of ethanol gas. The response of ZnO NWswas very high for ethanol compared to the CO, whereas the recovery time for ethanol was very poor compare to CO gas. The response of ZnO NWs was about 25 times higher for ethanol compare to CO, at 400 ℃ for 100 ppm of each gas. The high response for ethanol is related to electron donating effect of ethanol (10e-) which was higher than the CO gas (2e-). The high response of ZnO NWs was attributed to large contacting surface area for electrons,oxygen, target gas molecule, and abundant channels for gas diffusion.
Prabhakar, A.K.,Lai, H.Y.,Potroz, M.G.,Corliss, M.K.,Park, J.H.,Mundargi, R.C.,Cho, D.,Bang, S.I.,Cho, N.J. Korean Society of Industrial and Engineering Chemi 2017 Journal of industrial and engineering chemistry Vol.53 No.-
Pine pollen is widely used in traditional Chinese medicine and has been consumed as a food product for thousands of years. Owing to wind pollination, its pollen grains are composed of a sporoplasmic central cavity along with two empty air sac compartments. While this architectural configuration is evolutionarily optimized for wind dispersal, such features also lend excellent potential for encapsulating materials, especially in the context of preparing sporopollenin exine capsules (SECs). Herein, we systematically evaluated one-pot acid processing methods in order to generate pine pollen SECs that support compound loading. Morphological properties of the SECs were analysed by scanning electron microscopy (SEM) and dynamic imaging particle analysis (DIPA), and protein removal was evaluated by CHN elemental analysis and confocal laser scanning microscopy (CLSM). It was identified that 5-h acidolysis with 85% w/v phosphoric acid at 70<SUP>o</SUP>C yielded an optimal balance of high protein removal and preservation of microcapsule architecture, while other processing methods were also feasible with an additional enzymatic step. Importantly, the loading efficiency of the pine pollen SECs was three-times greater than that of natural pine pollen, highlighting their potential for microencapsulation. Taken together, our findings outline a successful strategy to prepare intact pine pollen SECs and demonstrate for the first time that SECs can be prepared from multi-compartmental pollen capsules, opening the door to streamlined processing approaches to utilize pine pollen microcapsules in industrial applications.
Use of GammaPlan convolution algorithm for dose calculation on CT and cone-beam CT images
Prabhakar Ramachandran,Ben Perrett,Orrie Dancewicz,Venkatakrishnan Seshadri,Catherine Jones,Akash Mehta,Matthew Foote 대한방사선종양학회 2021 Radiation Oncology Journal Vol.39 No.2
Purpose: The aim of this study was to assess the suitability of using cone-beam computed tomography images (CBCTs) produced in a Leksell Gamma Knife (LGK) Icon system to generate electron density information for the convolution algorithm in Leksell GammaPlan (LGP) Treatment Planning System (TPS). Materials and Methods: A retrospective set of 30 LGK treatment plans generated for patients with multiple metastases was selected in this study. Both CBCTs and fan-beam CTs were used to provide electron density data for the convolution algorithm. Plan quality metrics such as coverage, selectivity, gradient index, and beam-on time were used to assess the changes introduced by convolution using CBCT (convCBCT) and planning CT (convCT) data compared to the homogeneous TMR10 algorithm. Results: The mean beam-on time for TMR10 and convCBCT was found to be 18.9 ± 5.8 minutes and 21.7 ± 6.6 minutes, respectively. The absolute mean difference between TMR10 and convCBCT for coverage, selectivity, and gradient index were 0.001, 0.02, and 0.0002, respectively. The calculated beam-on times for convCBCT were higher than the time calculated for convCT treatment plans. This is attributed to the considerable variation in Hounsfield values (HU) dependent on the position within the field of view. Conclusion: The artifacts from the CBCT’s limited field-of-view and considerable HU variation need to be taken into account before considering the use of convolution algorithm for dose calculation on CBCT image datasets, and electron data derived from the onboard CBCT should be used with caution.
Prabhakar, Arun K.,Potroz, Michael G.,Tan, Ee-Lin,Jung, Haram,Park, Jae Hyeon,Cho, Nam-Joon American Chemical Society 2018 ACS APPLIED MATERIALS & INTERFACES Vol.10 No.34
<P>Pine pollen offers an all-natural multicavity structure with dual hollow air sacs, providing ample cargo capacity available for compound loading. However, the pollen exhibits reduced permeability because of the presence of a thin natural water-proofing layer of lipidic compounds. Herein, we explore the potential for compound loading within pine pollen and the potential for developing all-natural formulations for targeted delivery to the intestinal tract. Removal of the surface-adhered lipidic compounds is shown to improve surface wetting, expose nanochannel structures in the outer pollen shell and enhance water uptake throughout the whole pollen structure. Optimization of loading parameters enabled effective compound loading within the outer pollen shell sexine structure, with bovine serum albumin (BSA) serving as a representative protein. All-natural oral delivery formulations for targeted intestinal delivery are developed based on tableting of BSA-loaded defatted pine pollen, with the incorporation of xanthan gum as a natural binder, or ionotropically cross-linked sodium alginate as an enteric coating. Looking forward, the large cargo capacity, ease of compound loading, competitive cost, abundant availability, and extensive historical usage as food and medicine make pine pollen an attractive microencapsulant for a wide range of potential applications.</P> [FIG OMISSION]</BR>
Improved flame-retardant and tensile properties of thermoplastic starch/flax fabric green composites
Prabhakar, M.N.,Rehman Shah, Atta ur,Song, Jung-Il Applied Science Publishers 2017 Carbohydrate Polymers Vol.168 No.-
<P><B>Abstract</B></P> <P>This article highlights the development of biodegradable flame-retardant composites using a compression technique on low-cost starch, flax fabric (FF) and ammonium polyphosphate (APP) raw materials. The starch was plasticized into thermoplastic starch through a mechano-ball milling process and composites were developed by reinforcing the FF and incorporating varying amounts of APP. The effects of APP on the flammability and thermal properties of the composites were studied. Limited oxygen index and horizontal-burning tests exhibited significant sustainability of the composites toward flame and direct flame self-extinguishment. It was observed that at higher temperatures, APP leads to formation of thermally stable char. The flame retardant properties of the composites were speculated to be due to the protective compact crosslinked network (POP and POC) of the char. The reported effects of APP include improvement in mechanical and biodegradation properties. This investigation provides the design of novel flame-retardant green composites with excellent properties.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Flame retardant green composites were developed from plasticized starch and APP. </LI> <LI> Mechano-ball milling process was employed to prepare plasticized starch powder. </LI> <LI> The properties of the composites were investigated as a function of APP. </LI> <LI> The composites exhibit superior flame retardant and mechanical properties. </LI> </UL> </P>
Electroencephalography-based imagined speech recognition using deep long short-term memory network
Prabhakar Agarwal,Sandeep Kumar 한국전자통신연구원 2022 ETRI Journal Vol.44 No.4
This article proposes a subject-independent application of brain–computer interfacing (BCI). A 32-channel Electroencephalography (EEG) device is used to measure imagined speech (SI) of four words (sos, stop, medicine, washroom) and one phrase (come-here) across 13 subjects. A deep long short-term memory (LSTM) network has been adopted to recognize the above signals in seven EEG frequency bands individually in nine major regions of the brain. The results show a maximum accuracy of 73.56% and a network prediction time (NPT) of 0.14 s which are superior to other state-of-the-art techniques in the literature. Our analysis reveals that the alpha band can recognize SI better than other EEG frequencies. To reinforce our findings, the above work has been compared by models based on the gated recurrent unit (GRU), convolutional neural network (CNN), and six conventional classifiers. The results show that the LSTM model has 46.86% more average accuracy in the alpha band and 74.54% less average NPT than CNN. The maximum accuracy of GRU was 8.34% less than the LSTM network. Deep networks performed better than traditional classifiers.