4 research outputs found

    Spiral Ganglion Neuron Explant Culture and Electrophysiology on Multi Electrode Arrays

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    Spiral ganglion neurons (SGNs) participate in the physiological process of hearing by relaying signals from sensory hair cells to the cochlear nucleus in the brain stem. Loss of hair cells is a major cause of sensory hearing loss. Prosthetic devices such as cochlear implants function by bypassing lost hair cells and directly stimulating SGNs electrically, allowing for restoration of hearing in deaf patients. The performance of these devices depends on the functionality of SGNs, the implantation procedure and on the distance between the electrodes and the auditory neurons. We hypothesized, that reducing the distance between the SGNs and the electrode array of the implant would allow for improved stimulation and frequency resolution, with the best results in a gapless position. Currently we lack in vitro culture systems to study, modify and optimize the interaction between auditory neurons and electrode arrays and characterize their electrophysiological response. To address these issues, we developed an in vitro bioassay using SGN cultures on a planar multi electrode array (MEA). With this method we were able to perform extracellular recording of the basal and electrically induced activity of a population of spiral ganglion neurons. We were also able to optimize stimulation protocols and analyze the response to electrical stimuli as a function of the electrode distance. This platform could also be used to optimize electrode features such as surface coatings

    PDMS๊ธฐ๋ฐ˜์˜ ๊ณ ์›ํ˜• ์‹ ๊ฒฝ ์ ‘์† ์ „๊ทน ๊ตฌ์กฐ ์„ค๊ณ„ ๋ฐ ๊ตฌํ˜„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€, 2016. 2. ์„œ์ข…๋ชจ.๋ณต์žกํ•œ ํ‘œ๋ฉด ๊ตด๊ณก์„ ๊ฐ–๋Š” ์‹ ๊ฒฝ ์กฐ์ง๊ณผ ํšจ๊ณผ์ ์œผ๋กœ ์ธํ„ฐํŽ˜์ด์Šคํ•˜๊ธฐ ์œ„ํ•œ PDMS๊ธฐ๋ฐ˜์˜ ์œ ์—ฐํ•œ ํ‰ํŒํ˜• ๋ฏธ์„ธ์ „๊ทน์„ ๊ฐœ๋ฐœํ•˜๊ณ  ๊ทธ ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๊ธฐ๋ก์ „๊ทน ์ธก๋ฉด์—์„œ, ๊ธฐ์กด์˜ ์š”์ฒ ํ˜• ์ „๊ทน ๊ตฌ์กฐ๋ฅผ ํƒˆํ”ผํ•˜๊ณ  ๊ณ ์›์ง€ํ˜• ๋ชจ์–‘์˜ ์ „๊ทน์„ ํŠน์ง•์œผ๋กœํ•˜๋Š” ํ”Œ๋ผํ† (plateau)์ „๊ทน ์ œ์กฐ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ๋‹ค๋ฅธ ์ƒ์ฒด์ ํ•ฉ์„ฑ ํด๋ฆฌ๋จธ์ธ ํด๋ฆฌ์ด๋ฏธ๋“œ๋‚˜ ํŒจ๋Ÿด๋ฆฐ์œผ๋กœ ์ œ์ž‘๋œ ๋‹ค์ฑ„๋„์ „๊ทน์€ ๋‚ฎ์€ ์ ํ•ฉ์„ฑ(conformability)๊ณผ ์‹ ๊ฒฝ์กฐ์ง๊ณผ ๋น„๊ตํ•˜์—ฌ ๋†’์€ ์˜๋ฅ  ๊ทธ๋ฆฌ๊ณ  ๋‰ด๋Ÿฐ๊ณผ ์ „๊ทน ์‚ฌ์ด์— ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ์ด ๋ฐœ์ƒํ•˜๋Š” ํ•œ๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋‹ค. ์ „๊ทน์˜ ์š”์ฒ  ๊ตฌ์กฐ๋Š” ๋‡Œ์™€ ๊ฐ™์ด ๋ถ€๋“œ๋Ÿฌ์šด ์‹ ๊ฒฝ ์กฐ์ง์—์„œ๋Š” ์žฌ๋ถ„ํฌ(repopulation)ํ˜„์ƒ์œผ๋กœ ๋ฌธ์ œ๊ฐ€ ์™„ํ™”๋˜์ง€๋งŒ ์ฒ™์ˆ˜์™€ ๊ฐ™์ด ์‹ ๊ฒฝ ๋‹ค๋ฐœ๋กœ ์ด๋ฃจ์–ด์ง„ ์กฐ์ง์—์„œ๋Š” ์‹ ํ˜ธ ์—ดํ™”์˜ ์ฃผ๋œ ์š”์ธ์ด ๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ์‚ฌ์šฉํ•œPDMS๋Š”์ƒ์ฒด์ ํ•ฉ์„ฑํด๋ฆฌ๋จธ์ค‘๊ฐ€์žฅ์‹ ๊ฒฝ์กฐ์ง๊ณผ์˜์˜๋ฅ ์ด์œ ์‚ฌํ•˜๊ณ  ๋›ฐ์–ด๋‚œ ์ ํ•ฉ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด ๊ธฐ๋ก์šฉ์ „๊ทน์˜ ์žฌ๋ฃŒ๋กœ ์ ํ•ฉํ•˜๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋‹ค๋ฅธํด๋ฆฌ๋จธ์™€ ์œ ์‚ฌํ•˜๊ฒŒ PDMS์˜ ์†Œ์ˆ˜์„ฑ ํŠน์„ฑ์œผ๋กœ ์ธํ•˜์—ฌ ์ „๊ทน์˜ ํฌ๊ธฐ๊ฐ€ ์ž‘์•„์งˆ์ˆ˜๋ก ๊ณต๊ธฐ ๊ฐ‡ํž˜ํ˜„์ƒ์ด ๋‘๋“œ๋Ÿฌ์ง€๊ฒŒ ๋ฐœ์ƒํ•˜์˜€๊ณ  ์ด๋กœ์ธํ•˜์—ฌ ์‹คํ—˜์˜ ์‹ ๋ขฐ์„ฑ์— ๋ฌธ์ œ๊ฐ€ ๋ฐœ์ƒํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ํ”Œ๋ผํ† ์ „๊ทน์€ ์‹ ๊ฒฝ์กฐ์ง๊ณผ์˜ ์ ํ•ฉ์„ฑ ๋ฐ ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ์„ ํšจ๊ณผ์ ์œผ๋กœ ํ•ด๊ฒฐํ•จ์œผ๋กœ์จ ์‹ ๋ขฐ์„ฑ์žˆ๋Š” ๋™๋ฌผ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ž๊ทน์ „๊ทน ์ธก๋ฉด์—์„œ, ๊ธฐ์กด ์ˆ˜์งํ˜• ๋ฒฝ๋ฉด ์ „๊ทน์˜ ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ๋Š” ์ „๊ทน์˜ ๊ฐ€์žฅ์ž๋ฆฌ์—์„œ ๊ฐ€์žฅ ๊ฐ•ํ•˜๊ฒŒ ๋‚˜ํƒ€๋‚˜ ์กฐ์ง์„ ๊ท ์ผํ•˜๊ฒŒ ์ž๊ทนํ•˜๊ธฐ ์–ด๋ ค์› ๋‹ค. ํ•˜์ง€๋งŒ ์ „๊ทน์˜ ๋ฒฝ๋ฉด ๋ชจ์–‘์— ๋”ฐ๋ผ ์ „๊ทน์˜ ํ‘œ๋ฉด์— ์œ ๊ธฐ๋˜๋Š” ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ๊ฐ€ ๋ณ€ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜๊ณ  PDMS๊ธฐ๋ฐ˜์˜ ๊ฒฝ์‚ฌ๋ฒฝ๋ฉด์„ ๊ฐ–๋Š” ์ „๊ทน ์ œ์ž‘ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•˜๊ณ  ์ œ์ž‘ํ•˜์˜€๋‹ค. ๊ฒฝ์‚ฌ๊ฐ์„ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•ด์„œ ์Œ์„ฑ๊ฐ๊ด‘์ œ์˜ ๋…ธ๊ด‘์—๋„ˆ์ง€๋ฅผ ๋ณ€ํ™”์‹œํ‚ค๋Š” ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์˜€๋‹ค. ๊ณผ์†Œ๋…ธ๊ด‘์ •๋„์™€ ๋งˆ์Šคํฌ์™€ ๊ฐ๊ด‘์ œ์˜ ๊ฐ„๊ฒฉ์— ๋”ฐ๋ผ ๊ฐ๊ด‘์ œ ๊ธฐ๋‘ฅ์˜ ๊ฒฝ์‚ฌ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ์ œ์–ดํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ,์ด๋ฅผ ์ด์šฉํ•˜์—ฌ ์ „๊ทน ๋ฒฝ๋ฉด์˜ ๊ฒฝ์‚ฌ๋ฅผ ์ œ์–ดํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ˆ˜์ง ๋ฒฝ๋ฉด ์ „๊ทน, ๊ฒฝ์‚ฌ๋ฒฝ๋ฉด ์ „๊ทน, ํ‘œ๋ฉด ๋ถ€์ฐฉํ˜• ์ „๊ทน๊ตฌ์กฐ์—์„œ ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ๋ฅผ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ COMSOL์„ ์ด์šฉํ•ด ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ๋ฅผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜์˜€๋‹ค. ๋‹ค์ธต ๊ธฐํŒ ์ œ์ž‘์— ์žˆ์–ด ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์ธต๊ฐ„์—ฐ๊ฒฐ ๊ธฐ๋ฒ•์„ ๊ธฐ์กด์˜ ์ˆ˜์งํ˜• ์ธต๊ฐ„์—ฐ๊ฒฐ์—์„œ ๊ฒฝ์‚ฌํ˜• ์ธต๊ฐ„์—ฐ๊ฒฐ๋กœ ๋Œ€์ฒดํ•จ์œผ๋กœ์จ ๋„๊ธˆ๊ณต์ •์—†์ด ๋‹ค์ธต๊ธฐํŒ์„ ์ œ์ž‘ํ•˜๋Š” ๊ณต์ • ๊ธฐ์ˆ ์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ธต๊ฐ„์—ฐ๊ฒฐ ๊ณผ์ •์—์„œ PDMS์™€ ๊ธˆ์„ ์—ฐ๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ํ‹ฐํƒ€๋Š„์„ ๋ฐฐ์ œํ•˜๋Š” ๊ณต์ •์„ ์ œ์•ˆํ•จ์œผ๋กœ์จ ์ธต๊ฐ„์—ฐ๊ฒฐ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ €ํ•ญ์„ ํšจ๊ณผ์ ์„ ๋ฐฉ์ง€ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  PDMS๊ธฐํŒ์˜ ์ธ์žฅ ๋ฐ ๊ตฝํž˜์‹œํ—˜์„ ์ˆ˜ํ–‰ํ•˜์—ฌ ์ธ์žฅ๋น„์œจ์ด4%์ด๋‚ด์—์„œ๋Š” ๋‹จ์„ ์ด ๋ฐœ์ƒํ•˜์ง€ ์•Š์Œ์„ ํ™•์ธํ•˜์˜€๊ณ  3000ํšŒ์˜๊ตฝํž˜ ์‹คํ—˜ ๋™์•ˆ์— ์„ฑ๋Šฅ์˜ ์—ดํ™”๊ฐ€ ๋ฏธ๋ฏธํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 8๊ฐœ์˜ ์ธต๊ฐ„์—ฐ๊ฒฐ๊ณผ 5ํšŒ์˜ ๋„์„  ๊ต์ฐจ๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ์–‘๋ฉด ๊ธฐํŒ์„ ์ œ์ž‘ํ•˜์—ฌ ์ œ์•ˆ ๊ธฐ๋ฒ•์˜ ์œ ํšจ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๊ธฐ์กด ๋ฐฉ์‹์œผ๋กœ ์ œ์ž‘ํ•œ ์˜ค๋ชฉํ•œ(recessed) ์ „๊ทน๊ณผ ์ œ์•ˆํ•œ ํ”Œ๋ผํ†  ์ „๊ทน์„ ์ด์šฉํ•˜์—ฌ ๋™๋ฌผ ์‹คํ—˜์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์˜ค๋ชฉํ•œ ์ „๊ทน์—์„œ๋Š” ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ์œผ๋กœ ์ธํ•˜์—ฌ ์‹ ๋ขฐ์„ฑ ์žˆ๋Š” ์‹ ํ˜ธ ๊ธฐ๋ก์ด ์ด๋ฃจ์–ด์ง€์ง€ ์•Š์•˜์œผ๋‚˜, ํ”Œ๋ผํ†  ์ „๊ทน์—์„œ๋Š” ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ์ด ์ผ์–ด๋‚˜์ง€ ์•Š์•„ ํšจ๊ณผ์ ์œผ๋กœ ์ƒ์ฒด ์‹ ํ˜ธ๋ฅผ ๊ธฐ๋กํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋™๋ฌผ ์‹คํ—˜์€ ๋‘๊ฐ€์ง€ ํ™˜๊ฒฝ์—์„œ ์ง„ํ–‰ํ•˜์˜€๋Š”๋ฐ, ํ•œ ์‹คํ—˜์€ ์„ค์น˜๋ฅ˜์˜ ํšŒ์Œ๋ถ€๋ฅผ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ์ž๊ทนํ•จ์œผ๋กœ์จ ๋ฐœ์ƒํ•˜๋Š” ์ฒ™์ˆ˜์‹ ๊ฒฝ ์‹ ํ˜ธ๋ฅผ ๊ธฐ๋กํ•จ์œผ ๋กœ์จ ์ž๊ทน์˜ ์œ ํšจ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๊ณ , ๋‹ค๋ฅธํ•˜๋‚˜๋Š” 2๊ฐ€์ง€์˜ ๋ƒ„์ƒˆ๋ฌผ์งˆ์„ ์„ค์น˜๋ฅ˜์˜ ์ฝ”์— ์ฃผ์ž…ํ•œ ํ›„, ๋‡Œ์˜ ํ›„๊ฐ๋ง์šธ์—์„œ ๊ทธ ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•จ์œผ๋กœ์จ ์ž๊ทน์˜ ์œ ํšจ์„ฑ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค.I. ์„œ ๋ก  1 1.1 ์‹ ๊ฒฝ ์ ‘์† ๊ธฐ์ˆ  1 1.2 ๋‹ค์ฑ„๋„ ์ „๊ทน์—ด ๊ธฐ์ˆ  4 1.2.1 ํด๋ฆฌ๋จธ ๊ธฐ๋ฐ˜์˜ ์œ ์—ฐํ•œ ํ‘œ๋ฉดํ˜• MEA 6 1.2.2 ์‹ค๋ฆฌ์ฝ˜ ๊ณ ๋ฌด 9 1.2.3 PDMS ๊ธฐ๋ฐ˜์˜ ์œ ์—ฐํ•œ ํ‘œ๋ฉดํ˜• MEA 12 1.3 PDMS๊ธฐ๋ฐ˜์˜ ๋ฐ˜๋„์ฒด ๊ณต์ • ๊ธฐ์ˆ  15 1.3.1 ๋ฏธ์„ธ ๊ณต์ • ๋ฌธ์ œ 15 1.3.2 ๊ธฐ๋ก ์ „๊ทน ๋ฌธ์ œ 16 1.3.3 ์ž๊ทน ์ „๊ทน ๋ฌธ์ œ 17 1.3.4 ๋‹ค์ธต ๊ธฐํŒ ๋ฌธ์ œ 18 1.4 ์š”์•ฝ 20 II. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• 23 2.1 PDMS๋ฅผ ์ด์šฉํ•œ ๋ฐ˜๋„์ฒด ๊ณต์ • 24 2.1.1 ํ‘œ๋ฉด ์ฒ˜๋ฆฌ ๊ธฐ์ˆ  24 2.1.2 ๊ธˆ์† ๋„์„  ์‹๊ฐ 29 2.1.3 ๊ธฐ์กด์˜ PDMS ํŒจํ„ฐ๋‹ ๊ธฐ๋ฒ• 42 2.1.4 ์ œ์•ˆ ์ฃผ๋ฌผ ๊ธฐ๋ฒ• 44 2.2 ๊ธฐ๋ก์šฉ ํ”Œ๋ผํ† (Plateau) ์ „๊ทน 50 2.2.1 ํ”Œ๋ผํ†  ์ „๊ทน ์ œ์ž‘ ๊ณต์ • 51 2.2.2 ์ „๊ทน ํ”„๋กœํŒŒ์ผ 56 2.2.3 ์ž„ํ”ผ๋˜์Šค ์ธก์ • 58 2.2.4 ์ „๊ทน์˜ ํ‘œ๋ฉด ์ ‘์ด‰ ์„ฑ๋Šฅ 60 2.3 ์ž๊ทน์šฉ ๊ฒฝ์‚ฌ ์ „๊ทน(slated-edge electrode) 60 2.3.1 ๊ธฐ์กด ์ „๊ทน์˜ ์ „๋ฅ˜ ๋ฐ€๋„ ๋ฌธ์ œ 61 2.3.2 ๊ฒฝ์‚ฌ ์ „๊ทน ์ œ์ž‘ ๊ณต์ • 62 2.3.3 ์‹ ๋ขฐ์„ฑ ์‹คํ—˜ 67 2.3.4 ์ „๊ทน ๊ตฌ์กฐ์— ๋”ฐ๋ฅธ ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ 69 2.4 PDMS ๊ธฐ๋ฐ˜์˜ ๋‹ค์ธต ๊ธฐํŒ ์ œ์ž‘์˜ ํ•„์š”์„ฑ 69 2.4.1 MPTMS๋ฅผ ์ด์šฉํ•œ PDMS ํ‘œ๋ฉด ๊ฐœ์งˆ 71 2.4.2 ์—ด์••์ฐฉ๊ธฐ๋ฅผ ์ด์šฉํ•œ PDMS๋ฐ•๋ง‰ ํ‰ํƒ„๋„ ํ–ฅ์ƒ 73 2.4.3 ๋‹ค์ธต ๊ธฐํŒ์„ ์œ„ํ•œ ์—ฐ๊ฒฐํ†ต๋กœ(Via) ๊ตฌ์กฐ 74 2.4.4 ๋‹ค์ธต ๊ธฐํŒ ์ œ์ž‘ ๊ณต์ • ๊ธฐ๋ฒ• 75 2.4.5 ์ •์ „ ์šฉ๋Ÿ‰ ์ธก์ • 79 2.5 ํ”Œ๋ผํ† (plateau) ์ „๊ทน์„ ์ด์šฉํ•œ ๋™๋ฌผ์‹คํ—˜ 79 2.5.1 ์‹ ๊ฒฝ ์‹ ํ˜ธ ๊ธฐ๋ก์„ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค ์ œ์ž‘ 80 2.5.2 ์ฒ™์ˆ˜ ์‹ ๊ฒฝ ์‹ ํ˜ธ ๊ธฐ๋ก ์‹คํ—˜ 82 2.5.3 ํ›„๊ฐ๋ง์šธ ์‹ ๊ฒฝ ์‹ ํ˜ธ ๊ธฐ๋ก ์‹คํ—˜ 84 III. ๊ฒฐ๋ก  86 3.1 PDMS ๊ธฐ๋ฐ˜์˜ ๋ฐ˜๋„์ฒด ๊ณต์ • ๊ฒฐ๊ณผ 86 3.1.1 PDMS ํ‘œ๋ฉด ๊ฐœ์งˆ ๊ฒฐ๊ณผ 86 3.1.2 ๊ธˆ์† ๋ฐ•๋ง‰๊ณผ PDMS ๊ณ„๋ฉด์˜ ์ ‘์ฐฉ๋ ฅ ์‹คํ—˜ ๊ฒฐ๊ณผ 86 3.1.3 ๊ธˆ์† ๋„์„  ์ œ์ž‘ ์‹คํ—˜ ๊ฒฐ๊ณผ 90 3.1.4 ์ธ์žฅ ๋ฐ ๊ตฝํž˜ ์‹คํ—˜ ๊ฒฐ๊ณผ 97 3.1.5 PDMS ํŒจํ„ฐ๋‹ ๊ธฐ๋ฒ• ๊ฒฐ๊ณผ 98 3.2 ๊ธฐ๋ก์šฉ ํ”Œ๋ผํ†  ์ „๊ทน ์ œ์ž‘ ๊ฒฐ๊ณผ 110 3.2.1 ์ „๊ทน 3D ํ”„๋กœํŒŒ์ผ ๊ฒฐ๊ณผ 111 3.2.2 ์ž„ํ”ผ๋˜์Šค ์ธก์ • ๊ฒฐ๊ณผ 114 3.2.3 ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ ๋ฐฉ์ง€ ๊ฒฐ๊ณผ 117 3.3 ์ž๊ทน์šฉ ๊ฒฝ์‚ฌ ์ „๊ทน ์ œ์ž‘ ๊ฒฐ๊ณผ 117 3.3.1 ์‹ ๋ขฐ์„ฑ ์‹คํ—˜ ๊ฒฐ๊ณผ 121 3.3.2 ์ „๋ฅ˜ ๋ฐ€๋„ ๋ถ„ํฌ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ 122 3.4 PDMS๊ธฐ๋ฐ˜์˜ ๋‹ค์ธต ๊ธฐํŒ ์ œ์ž‘ ๊ฒฐ๊ณผ 124 3.4.1 ์ •์ „์šฉ๋Ÿ‰ ์ธก์ •๊ฒฐ๊ณผ 124 3.4.2 ๋ˆ„ํ™”(cross talk) ์žก์Œ 127 3.4.3 ๋ ˆ์ด์ €๋ฅผ ์ด์šฉํ•œ ์™ธํ˜• ์ ˆ๋‹จ ๋ฐ MEA ํšŒ์ˆ˜ 130 3.5 In Vivo ์‹คํ—˜ 132 3.5.1 ์ฒ™์ˆ˜ ์‹ ๊ฒฝ ์‹ ํ˜ธ ๊ธฐ๋ก ์‹คํ—˜ ๊ฒฐ๊ณผ 132 3.5.2 ํ›„๊ฐ๋ง์šธ ์‹ ๊ฒฝ ์‹ ํ˜ธ ๊ธฐ๋ก ์‹คํ—˜ ๊ฒฐ๊ณผ 135 IV. ํ† ์˜ 139 4.1 PDMS ํ‘œ๋ฉด์ฒ˜๋ฆฌ ๊ธฐ์ˆ  139 4.2 ์‚ฌ์ง„๊ณต์ •์„ ์œ„ํ•œ ์Œ์„ฑ ๊ฐ๊ด‘์ œ ์„ ํƒ 140 4.3 ์œ ๊ธฐ ์šฉ์•ก์— ์˜ํ•œ PDMS ๋ณ€ํ˜• 141 4.4 ์ฃผ๋ฌผ ๊ณต์ • ์ œ์•ˆ 141 4.5 ๊ธฐ๋ก์šฉ ํ”Œ๋ผํ†  ์ „๊ทน 142 4.6 ์ž๊ทน์šฉ ์™„๋งŒํ•œ ๊ฒฝ์‚ฌ ์ „๊ทน 142 4.7 ๋‹ค์ธต ๊ธฐํŒ ์ œ์ž‘์„ ์œ„ํ•œ ์—ฐ๊ฒฐํ†ต๋กœ 143 V. ๊ฒฐ๋ก  ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ๋ฐฉํ–ฅ 144 5.1 ๊ฒฐ๋ก  144 5.2 ํ–ฅํ›„ ์—ฐ๊ตฌ๋ฐฉํ–ฅ 146 ์ฐธ๊ณ  ๋ฌธํ—Œ 148 Abstract 161Docto

    A PDMS-Parylene Hybrid MultiChannel Electrode Array for Olfactory Cortical Interface

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2017. 8. ์„œ์ข…๋ชจ.์‹ ๊ฒฝ ์กฐ์ง์˜ ์†์ƒ์„ ์ตœ์†Œํ™”ํ•˜๊ณ  ์‚ผ์ฐจ์› ๊ตฌ์กฐ์˜ ๋‡Œ์กฐ์ง๊ณผ ํšจ๊ณผ์ ์œผ๋กœ ์ธํ„ฐํŽ˜์ด์Šค ํ•  ์ˆ˜ ์žˆ๋Š” ์œ ์—ฐ์„ฑ ํด๋ฆฌ๋จธ ๊ธฐ๋ฐ˜์— ํ‰ํŒํ˜• ๋ฏธ์„ธ ์ „๊ทน์„ ์„ค๊ณ„ ๋ฐ ์ œ์ž‘ํ•˜์˜€์œผ๋ฉฐ ์ฅ์˜ ํ›„๊ฐ์˜์—ญ๋‹ด๋‹น ๋‡Œํ”ผ์งˆ ์œ„์— ์‚ฝ์ž…ํ•˜์—ฌ ํŠน์ • ํ›„๊ฐ ์ž๊ทน์— ์˜ํ•œ ์‹ ๊ฒฝ ์‹ ํ˜ธ์˜ ํŒจํ„ด์„ ์ธ์‹ํ•˜๊ณ  ๋ถ„๋ฅ˜ํ•˜๋Š” ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ „์ž์ฝ”(Electronic nose)๋Š” ํ–ฅ๊ธฐ๋‚˜ ๋ƒ„์ƒˆ ๋ฌผ์งˆ์˜ ํ™”ํ•™์  ํŠน์„ฑ์„ ์ธก์ •ํ•˜๊ณ  ๋ถ„์„ํ•œ ์žฅ๋น„๋กœ์จ ์˜๋ฃŒ, ๋†์—…, ์‹ํ’ˆ์•ˆ์ „, ๋…๊ทน๋ฌผ ๊ฒฝ๊ณ  ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ์—ฐ๊ตฌ๊ฐœ๋ฐœ๋˜์–ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์ธ๊ณต์ ์œผ๋กœ ์ œ์ž‘๋œ ํ›„๊ฐ ์„ผ์„œ์˜ ๊ฒฝ์šฐ ์ฃผ๋ณ€ํ™˜๊ฒฝ์ด ๋‹ค์ฑ„๋กญ๊ฒŒ ๋ณ€ํ•˜๊ฑฐ๋‚˜ ๋‹ค์–‘ํ•œ ๋ƒ„์„ธ ๋ฌผ์งˆ์ด ํ˜ผํ•ฉ๋˜์–ด ์žˆ์„ ๊ฒฝ์šฐ ์•ˆ์ •์ ์œผ๋กœ ํ›„๊ฐ ๋ฌผ์งˆ์„ ์ธก์ •ํ•˜๊ธฐ ์–ด๋ ต๋‹ค. ๋ฐ˜๋ฉด์— ์‚ฌ๋žŒ๊ณผ ๋™๋ฌผ์˜ ํ›„๊ฐ ๊ธฐ๊ด€์˜ ๊ฒฝ์šฐ, ์ˆ˜ ๋งŒ๊ฐ€์ง€ ์ด์ƒ์˜ ๋ฌผ์งˆ์„ ๊ตฌ๋ณ„ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์ฃผ๋ณ€ ํ™˜๊ฒฝ ๋ณ€ํ™”์—๋„ ๊ฐ•์ธํ•œ ํŠน์„ฑ์„ ๋ณด์ด๊ณ  ๋†’์€ ๋ฏผ๊ฐ์„ฑ์„ ๋ณด์ธ๋‹ค. ๋”ฐ๋ผ์„œ ๊ณตํ•ญ์ด๋‚˜ ๊ตฐ๋Œ€์—์„œ๋Š” ๋™๋ฌผ๋“ค์„ ํ›ˆ๋ จ์‹œ์ผœ ๋งˆ์•ฝ์ด๋‚˜ ํญํƒ„๋ฌผ ๊ฐ™์€ ๋ฌผ์งˆ์„ ๊ฐ์ง€ํ•œ๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ๋ฐฉ์‹์€ ๋น„์šฉ์ด ๋น„์‹ธ๊ณ  ํ›ˆ๋ จ ๊ธฐ๊ฐ„์ด ๊ธธ๊ธฐ ๋•Œ๋ฌธ์— ๊ธฐ์กด์˜ ํ™”ํ•™ ์„ผ์„œ๋ฅผ ๋Œ€์ฒดํ•˜๊ธฐ์—๋Š” ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ์‹ ๊ฒฝ์ ‘์†๊ธฐ์ˆ ์„ ์ด์šฉํ•˜์—ฌ ๋™๋ฌผ์˜ ํ›„๊ฐ ๋‹ด๋‹น ํ”ผ์งˆ ์˜์—ญ์˜ ์‹ ๊ฒฝ ์‹ ํ˜ธ๋ฅผ ์ธก์ • ํ›„ ํŒจํ„ด ์ธ์‹์„ ํ†ตํ•ด ๋ƒ„์ƒˆ ๋ฌผ์งˆ์„ ๊ตฌ๋ณ„ํ•ด ๋‚ด๋Š” ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํžˆ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ์œผ๋ฉฐ ์ด์™€ ๊ฐ™์€ ๋ฐฉ๋ฒ•์œผ๋กœ ์ ์€ ๋น„์šฉ์œผ๋กœ ํ›ˆ๋ จ๊ธฐ๊ฐ„ ์—†์ด ๋™๋ฌผ์˜ ํ›„๊ฐ ๊ธฐ๊ด€์„ ์ด์šฉํ•˜์—ฌ ๋ƒ„์ƒˆ ๋ฌผ์งˆ์„ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ฅ์˜ ํ›„๊ฐ์˜์—ญ์„ ๋‹ด๋‹นํ•˜๋Š” ๋‡Œ์˜ ํ‘œ๋ฉด์—์„œ์˜ ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•˜์—ฌ ๋ƒ„์ƒˆ ๋ฌผ์งˆ์„ ๊ตฌ๋ณ„ํ•ด ๋‚ด๋Š” ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์กฐ์ง ์†์ƒ์„ ์ตœ์†Œํ™” ํ•˜๋ฉด์„œ ๋‡Œ ํ‘œ๋ฉด์— ์ „๊ทน์„ ๋ฐ€์ฐฉ์‹œ์ผœ ๋ถ€์ฐฉํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์œ ์—ฐํ•œ ๊ธฐํŒ์œผ๋กœ ์ œ์ž‘๋œ ์ „๊ทน์ด ํ•„์š”ํ•˜๋‹ค. ์กฐ์ง๊ณผ์˜ ์œ ์—ฐ์„ฑ์ด ๋น„์Šทํ•œ PDMS๋กœ ์ œ์ž‘๋œ ์ƒ์ฒด ์‚ฝ์ž… ์žฅ์น˜๋Š” ์˜๋ฅ (Youngs modulus) ์ฐจ์ด๋กœ ์ธํ•ด ๋ฐœ์ƒ๋˜๋Š” ์—ผ์ฆ๋ฐ˜์‘์ด๋‚˜ ์กฐ์ง ์†์ƒ์„ ์ตœ์†Œํ™” ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ ์กฐ์ง๊ณผ์˜ ์ ‘์ฐฉ๋ ฅ์ด ๋›ฐ์–ด๋‚˜ ์žฅ์‹œ๊ฐ„ ์•ˆ์ •์ ์œผ๋กœ ๋ถ€์ฐฉ๋  ์ˆ˜ ์žˆ๋‹ค. ํ•˜์ง€๋งŒ PDMS ๊ธฐ๋ฐ˜์— ๋ฏธ์„ธ์ „์ž๊ธฐ๊ณ„์‹œ์Šคํ…œ (micro electro mechanical systems) ๊ณต์ •์€ PDMS์˜ ๋ฌผ๋ฆฌ์  ์„ฑ์งˆ ๋•Œ๋ฌธ์— ๊ธˆ์† ๋ฐ•๋ฆฌ, ๊ฐˆ๋ผ์ง, ์—ดํŒฝ์ฐฝ๋“ฑ ๋งŽ์€ ์–ด๋ ค์›€์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด์ ์„ ๊ฐœ์„ ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ˆ˜ ฮผm์˜ ์–‡์€ ํŒจ๋Ÿด๋ฆฐ(Parylene-C) ๋ฐ•๋ง‰์„ ์ด์šฉํ•ด PDMS ๊ณต์ • ๋‹จ์ ์„ ๋ณด์™„ํ•œ ๊ณต์ • ๋ฐฉ์‹์„ ๊ฐœ๋ฐœํ•˜์˜€๋‹ค. ๋˜ํ•œ ๊ธฐ์กด ์ „๊ทน์— ์˜ค๋ชฉ ๊ตฌ์กฐ๋กœ ์ธํ•ด ๋ฐœ์ƒ๋˜๋Š” ๊ณต๊ธฐ ๊ฐ‡ํž˜ํ˜„์ƒ๊ณผ ์‹ ํ˜ธ ์—ดํ™” ํ˜„์ƒ์„ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ „๊ทน ํ‘œ๋ฉด์ด ๊ฐ€์ ธ์•ผํ•  ๊ตฌ์กฐ์  ์กฐ๊ฑด๋“ค์— ๋Œ€ํ•ด ์ด๋ก ์ ์œผ๋กœ ์กฐ์‚ฌํ•˜์˜€๊ณ , ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๋ณผ๋กํ•œ ์–ธ๋• ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง€๋Š” ์ „๊ทน์„ ์ œ์ž‘ํ•˜์˜€๋‹ค. ์ฅ์˜ ํ›„๊ฐ ์‹ ๊ฒฝ์„ ๋‹ด๋‹นํ•˜๋Š” ์ฃผ์š” ํ›„๊ฐ ๋ง์šธ(main olfactory bulb) ์— ์ œ์ž‘๋œ ์ „๊ทน์„ ์‚ฝ์ž…ํ•˜๊ณ  5๊ฐ€์ง€ ๋ฌผ์งˆ์„ ๋…ธ์ถœ์‹œ์ผœ ์ด 100๊ฐœ์˜ ํ›„๊ฐ ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ์‹ ํ˜ธ์ „์ฒ˜๋ฆฌ(preprocessing) ๊ณผ์ •์„ ๊ฑฐ์นœ ํ›„ ์ด์‚ฐ ๋ณต์†Œ ๋ชจ๋ › ์›จ์ด๋ธ”๋ฆฟ(discrete complex morlet wavelet) ๋ณ€ํ™˜์„ ์ด์šฉํ•ด ํŠน์ • ์ฃผํŒŒ์ˆ˜ ์˜์—ญ์—์„œ์˜ ์‹ ๊ฒฝ ์‹ ํ˜ธ ๋ฐ์ดํ„ฐ๋ฅผ ์ถ”์ถœํ•˜์˜€๋‹ค. ์ถ”์ถœ๋œ ๋ฐ์ดํ„ฐ๋ฅผ ์ฃผ์š”์„ฑ๋ถ„๋ถ„์„(principle component analysis)์„ ํ†ตํ•ด ์ฐจ์›์ถ•์†Œ(dimension reduction)๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๊ณ  ์„ธ๊ฐ€์ง€ ์ข…๋ฅ˜์˜ ๋ถ„๋ฅ˜๊ธฐ(classifier)์— ์‹ ๊ฒฝ ์‹ ํ˜ธ ๋ฐ์ดํ„ฐ๋ฅผ ํ•™์Šต์‹œ์ผœ ํ›„๊ฐ ์‹ ๊ฒฝ ์‹ ํ˜ธ์˜ ํŒจํ„ด์„ ์ธ์‹ํ•˜๊ณ  ๋ถ„๋ฅ˜ํ•˜์˜€๋‹ค. 100๊ฐœ์˜ ํ›„๊ฐ ์‹ ํ˜ธ์ค‘ ๋žœ๋คํ•˜๊ฒŒ 90๊ฐœ๋ฅผ ๋ฝ‘์•„์„œ ๋ถ„๋ฅ˜๊ธฐ ํ•™์Šต์— ์‚ฌ์šฉ๋˜์—ˆ์œผ๋ฉฐ ๋‚˜๋จธ์ง€ 10๊ฐœ๋กœ ํ•™์Šต๋œ ๋ถ„๋ฅ˜๊ธฐ์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ์ด 10๋ฒˆ์˜ ๋ฐ˜๋ณต ์‹คํ—˜์„ ํ†ตํ•ด ์–ป๋Š” ๊ฒฐ๊ณผ๋ฅผ ํ‰๊ท ํ•˜์—ฌ ๋ถ„๋ฅ˜๊ธฐ์˜ ์ •ํ™•๋„๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ๋ถ„๋ฅ˜๊ธฐ๋กœ ์‚ฌ์šฉ๋œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์€ ์„ ํ˜• ํŒ๋ณ„ ๋ถ„์„(Linear discriminant analysis, LDA), ์„œํฌํŠธ ๋ฒกํ„ฐ ๋จธ์‹ (Support vector machine, SVM), ๋‹ค์ธต์ธ์ง€(multilayer perception MLP) ๋ฐฉ์‹์ด๋ฉฐ ์‹คํ—˜ ๊ฒฐ๊ณผ ๋‹ค์ธต์ธ์ง€ ๋ฐฉ์‹์ด ๋‹ค๋ฅธ ๋‘ ๋ฐฉ์‹์— ๋น„ํ•ด ์›”๋“ฑํ•œ ์„ฑ๋Šฅ์„ ๋ณด์˜€๋‹ค.1. ์„œ ๋ก  ๏ผ‘ 1.1. ์ „์ž์ฝ”์˜ ํ™œ์šฉ๋ถ„์•ผ์™€ ํ•œ๊ณ„ ๏ผ‘ 1.2. ์ƒ์ฒด ํ›„๊ฐ ๊ธฐ๊ด€ ๏ผ‘ 1.3. ๋‘๋‡Œ-์ปดํ“จํ„ฐ ์ธํ„ฐํŽ˜์ด์Šค ๏ผ“ 1.4. ์ฅ ํ›„๊ฐ ์ž๊ทน์— ๋”ฐ๋ฅธ ์‹ ํ˜ธ ์ธก์ • ๋ฐ ๋ถ„๋ฅ˜ ๏ผ– 1.5. ๋‡Œํ”ผ์งˆ์ „๋„ ๏ผ˜ 1.6. ํด๋ฆฌ๋จธ ๊ธฐ๋ฐ˜์˜ ์œ ์—ฐํ•œ ํ‰ํŒํ˜• ๋‹ค์ฑ„๋„ ์ „๊ทน ๏ผ‘๏ผ‘ 1.7. PDMS ๊ธฐ๋ฐ˜ ๋‡Œํ”ผ์งˆ์ „๋„ ์‹ ๊ฒฝ ์ „๊ทน ๏ผ‘๏ผ– 1.7.1. ๋ฏธ์„ธ ๊ณต์ • ๋ฌธ์ œ ๏ผ‘๏ผ– 1.7.2. ๊ธฐ๋ก ์ „๊ทน ๋ฌธ์ œ ๏ผ‘๏ผ– 1.8. ์š” ์•ฝ ๏ผ‘๏ผ— 2. ์—ฐ๊ตฌ ๋ฐฉ๋ฒ• ๏ผ‘๏ผ™ 2.1. ๋ฌธ์–ด๋ฐœ ๋ชจ์–‘์˜ ๋„๋ž‘๊ตฌ์กฐ๊ฐ€ ์—†๋Š” ์ „๊ทน ๋””์ž์ธ ๏ผ‘๏ผ™ 2.2. ๋ฏธ์„ธ ํŒจํ„ด ๋ฐ˜๋„์ฒด ๊ณต์ • ๊ธฐ์ˆ  ๏ผ’๏ผ‘ 2.2.1. ํ‘œ๋ฉด ์ฒ˜๋ฆฌ ๊ธฐ์ˆ  ๏ผ’๏ผ‘ 2.2.2. PDMS-ํŒจ๋Ÿด๋ฆฐ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๊ณต์ • ๊ธฐ์ˆ  ๏ผ’๏ผ‘ 2.2.3. TMAH ์ด๋“ฑ๋ฐฉ์„ฑ ์‹๊ฐ. ๏ผ’๏ผ“ 2.3. ๊ธฐ๋ก ์„ฑ๋Šฅ ํ–ฅ์ƒ์„ ์œ„ํ•œ ๊ตฌ์กฐ์  ์„ค๊ณ„ ์ด๋ก  ๏ผ’๏ผ• 2.3.1. ๊ณต๊ธฐ๋ฐฉ์šธ ๊ฐ‡ํž˜ ํ˜„์ƒ์— ๋Œ€ํ•œ ์ด๋ก ์  ๋ถ„์„ ๏ผ’๏ผ• 2.3.1.1. ๊ณ„๋ฉด์—๋„ˆ์ง€์™€ ์ ‘์ด‰๊ฐ ๏ผ’๏ผ– 2.3.1.2. ๋„๋ž‘(trench)์—์„œ์˜ ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ ๋ถ„์„ ๏ผ’๏ผ— 2.3.1.3. ๊ณต๊ธฐ ๊ฐ‡ํž˜ ํ˜„์ƒ์„ ์—†์• ๊ธฐ ์œ„ํ•œ PDMS ์ „๊ทน ์„ค๊ณ„ ๏ผ’๏ผ™ 2.4. PDMS-ํŒจ๋Ÿด๋ฆฐ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ์ „๊ทน ์ œ์ž‘ ๋ฐฉ๋ฒ• ๏ผ“๏ผ‘ 2.4.1. ๋ฒฝ๋ฉด์— ๊ฒฝ์‚ฌ๊ฐ€ ์žˆ๋Š” ๊ฐ๊ด‘์ œ ํŒจํ„ด์„ ์ด์šฉํ•œ ๋ฐฉ๋ฒ• ๏ผ“๏ผ‘ 2.4.2. PDMS ์‹๊ฐ ๋ฐฉ๋ฒ•์˜ ๋‹จ์  ๏ผ“๏ผ• 2.4.3. ์‹ค๋ฆฌ์ฝ˜ ์ด๋“ฑ๋ฐฉ์„ฑ ์‹๊ฐ์„ ์ด์šฉํ•œ ๋ฐฉ์‹ ๏ผ“๏ผ˜ 2.5. ๋™๋ฌผ ์‹คํ—˜ ๏ผ”๏ผ‘ 2.5.1. ๋™๋ฌผ ์ „๊ทน ์‚ฝ์ž…์„ ์œ„ํ•œ ์ •์œ„ ์ˆ˜์ˆ  ๏ผ”๏ผ‘ 2.5.2. ๋™๋ฌผ ํ›„๊ฐ ์ž๊ทน๊ธฐ ๏ผ”๏ผ’ 2.5.3. ํ›„๊ฐ ์ž๊ทน ์‹คํ—˜ ๋ฐฉ๋ฒ• ๏ผ”๏ผ” 2.5.4. ์‹ ๊ฒฝ ๋ฐ์ดํ„ฐ ํš๋“ ๋ฐฉ์‹ ๏ผ”๏ผ– 2.6. ํŒจํ„ด ๋ถ„๋ฅ˜ ๊ธฐ๋ฒ• ๏ผ”๏ผ™ 2.6.1. ์„ ํ˜• ํŒ๋ณ„ ๋ถ„์„ ๏ผ”๏ผ™ 2.6.2. ์„œํฌํŠธ ๋ฐฑํ„ฐ ๋จธ์‹  ๏ผ•๏ผ‘ 2.6.3. ๋‹ค์ธต์ธ์ง€ (multilayer perception MLP) ๏ผ•๏ผ‘ 2.7. ํ›„๊ฐ ์ž๊ทน ์‹ ํ˜ธ ๋ถ„๋ฅ˜๋ฅผ ์œ„ํ•œ ๋จธ์‹ ๋Ÿฌ๋‹ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๏ผ•๏ผ“ 3. ๊ฒฐ๋ก  ๋ฐ ํ† ์˜ ๏ผ•๏ผ– 3.1. PDMS ๋ฌธ์–ด๋ฐœ ํ˜•ํƒœ์˜ ๋ฐ€์ฐฉ๋ ฅ ๋น„๊ต์™€ ๋„๋ž‘ ๊ตฌ์กฐ์— ๊ณต๊ธฐ ๋ฐฉ์šธ ๊ฐ‡ํž˜ ํ˜„์ƒ ์‹คํ—˜๊ฒฐ๊ณผ ๏ผ•๏ผ– 3.2. PDMS ํŒจ๋Ÿด๋ฆฐ ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๊ณต์ • ๏ผ•๏ผ– 3.2.1. ์—ดํŒฝ์ฐฝ์œจ๊ณผ ์œ ์—ฐ์„ฑ์— ๋”ฐ๋ฅธ ๋ฐ•๋ง‰ ์†์ƒ ๋ฐฉ์ง€ ๊ฒฐ๊ณผ ๏ผ•๏ผ˜ 3.2.2. ๊ธˆ์† ๋ฐ•๋ง‰๊ณผ PDMS/ํŒจ๋Ÿด๋ฆฐ ๊ณ„๋ฉด์˜ ์ ‘์ฐฉ๋ ฅ ์‹คํ—˜ ๊ฒฐ๊ณผ ๏ผ–๏ผ 3.2.3. PDMS ์™€ ํŒจ๋Ÿด๋ฆฐ์˜ ์กฐ์ง๊ณผ์˜ ์ ‘์ฐฉ๋ ฅ ๋น„๊ต ์‹คํ—˜ ๊ฒฐ๊ณผ ๏ผ–๏ผ” 3.3. ๋ณผ๋ก ๊ตฌ์กฐ ์ „๊ทน ์ œ์ž‘ ๏ผ–๏ผ– 3.4. ์ „๊ทน ์ž„ํ”ผ๋˜์Šค ์ธก์ • ๊ฒฐ๊ณผ ๏ผ–๏ผ™ 3.5. ํ›„๊ฐ ์ž๊ทน ๋™๋ฌผ ์‹คํ—˜ ๏ผ—๏ผ 3.6. ๋จธ์‹ ๋Ÿฌ๋‹์„ ํ†ตํ•œ ํ›„๊ฐ ์ž๊ทน ์‹ ํ˜ธ ๋ถ„๋ฅ˜ ๏ผ—๏ผ“ 4. ๊ฒฐ๋ก  ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ ๏ผ—๏ผ•Docto

    Investigation of single, binary, and ternary metal oxides of iridium, rhodium, and palladium for neural interfacing applications

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    In this dissertation, thin film single, binary, and ternary metal oxides of iridium (Ir), ruthenium (Ru), rhodium (Rh), and palladium (Pd) were synthesized for use as electrode/microelectrode coatings for neural interfacing applications using DC reactive magnetron sputtering. Synthesis conditions which enhanced the electrochemical properties of films as measured by cyclic voltammetry and electrochemical impedance spectroscopy in a phosphate buffered saline solution of the single metal oxides were identified to be 30 mTorr working pressure, 20% oxygen partial pressure, and cathode power densities โ‰ค 4.9 W/cm2. These parameters were then used to develop the binary and ternary metal oxide films. The binary metal oxides studied included Ir(1-x)Mx where M = Pd, Rh, Ru, and the ternary metal oxides studied included Ir(1-x-z)MxMzโ€™, where M,Mยด = Pd, Rh, and Ru. The binary metal oxide concentrations which produce robust microstructures and exceptional electrochemical performance have been identified to be x โ‰ฅ 0.5 for Ir(1-x)RhxOy, x โ‰ฅ 0.34 for Ir(1-x)RuxOy, and x โ‰ฅ 0.14 for Ir(1-x)PdxOy. Similar compositional ranges have been identified for the ternary metal oxides and include x โ‰ฅ 0.16 and z โ‰ฅ 0.05 for Ir(1-x-z)PdxRuzOy, x โ‰ฅ 0.13 and z โ‰ฅ 0.04 for Ir(1-x-z)PdxRhzOy, and x โ‰ฅ 0.2 and z โ‰ฅ 0.14 for Ir(1-x-z)RuxRhzOy
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