RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제
      • 좁혀본 항목 보기순서

        • 원문유무
        • 등재정보
        • 학술지명
        • 주제분류
        • 발행연도
        • 작성언어
        • 저자
          펼치기

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • KCI등재후보

        OPTIMIZATION OF THE MECHANICAL STRENGTH PROPERTIES OF POLY(L-LACTIDE)/MULTI-WALLED CARBON NANOTUBE SCAFFOLDS USING RESPONSE SURFACE METHODOLOGY

        HASSAN ADELI,SHARIF HUSSEIN SHARIF ZEIN,SOON HUAT TAN,ABDUL LATIF AHMAD 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2011 NANO Vol.6 No.2

        In this study the response surface methodology (RSM) coupled with the central composite design (CCD) were used to optimize the mechanical strength properties of poly(L-lactide)/multi-walled carbon nanotube (MWCNT) scaffolds. The scaffolds were prepared by the freeze-extraction method. MWCNTs were incorporated into PLLA composite as a reinforcement agent in order to improve the strength properties of the scaffolds. The effect of process parameters such as ratio of PLLA/(PLLA + MWCNT) (93–100%), solvent amount (100–200 ml), freezing time (5–7 h) and immersing time (2–4 days) were studied using the design of experiment (DOE). Based on CCD, quadratic model was obtained and developed to correlate the process parameters to the strength of the scaffolds. An analysis of variance (ANOVA) was applied to determine the significant factors affecting the experimental design response (strength) of the scaffolds. The predicted values after optimization process were in good agreement with the experimental values. The model was able to accurately predict the response of strength with less than 5% error.

      • KCI등재

        Fabrication of heparinized nano ZnO/poly(vinylalcohol)/carboxymethyl cellulose bionanocomposite hydrogels using artificial neural network for wound dressing application

        Alireza Joorabloo,Mohammad Taghi Khorasani,Hassan Adeli,Zohreh Mansoori-Moghadam,Armaghan Moghaddam 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.70 No.-

        This study aimed to optimize hydrogel wound dressings to achieve favorable properties of the watervapor transmission rate (WVTR) and proper degree of swelling ratio (DSR) to overcome the issues oftenassociated with most commercial dressings including improper breathability and insufficient exudateabsorption. Artificial neural network and response surface methodologies were utilized to design andmodel bionanocomposites. Besides, the effect of the ratio of components as input data, and WVTR andDSR properties as output (response) data were investigated. Hydrogel systems were produced via thefreeze–thaw method and were identified using infrared spectroscopy, dynamic light scattering, andscanning electron microscopy. To increase the antibacterial property of manufactured specimens, zincoxide nanoparticles were functionalized with heparin, and, other properties including mechanicalproperties, in vitro wound healing as well as toxicity analysis were investigated on the optimumformulation. Results showed an improvement in mechanical properties in the presence of nanoparticlesand also enhanced antibacterial property after conjugating heparin on nanoparticles. In vitro healing andcell viability results approved the biocompatibility and non-toxicity of the samples. Therefore,manufactured dressings were considered to have good DSR and WVTR, mechanical and biocompatibilityproperties and they exhibited good ability to heal and protect wounds.

      • KCI등재

        Using artificial neural network for design and development of PVA/chitosan/starch/heparinized nZnO hydrogels for enhanced wound healing

        Alireza Joorabloo,Mohammad Taghi Khorasani,Hassan Adeli,Peiman Brouki Milan,Moein Amoupour 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.108 No.-

        A study of many individual parameters is required to provide a robust investigation of a system inbiomedical applications. A comprehensive understanding of these parameters is achievable by an appropriateexperimental model as a valid description to predict the outputs (responses). A combination ofresponse surface methodology and artificial neural network has been employed to design hydrogel dressingsincluding polyvinyl alcohol, chitosan, and starch. The optimal ratio of components of hydrogels asinput data based on the water vapor transmission rate, gel content, swelling ratio, and porosity propertiesas output parameters was determined using the quick propagation algorithm. Zinc-oxide nanoparticleswere coupled with heparin and applied in the optimal formulation to investigate its effect on physicaland mechanical properties, cytotoxicity, and antibacterial activities as well as in vivo wound healing. Mechanical strength improved in the presence of zinc-oxide nanoparticles. Heparin release reached withthe saturation state in a longer period after conjugation onto zinc-oxide nanoparticles. Minimum inhibitoryconcentration decreased significantly by conjugation of heparin to the nanoparticles and current systemscould protect wounds against infections. In vivo wound healing and immunohistochemistry assayindicated accelerated wound closure, re-epithelialization, and skin regeneration for hydrogel dressingscontaining heparin functionalized zinc-oxide nanoparticles.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼