本文由 武漢高仕睿聯(lián)科技有限公司 整理匯編

2024-09-11 17:47 567閱讀次數(shù)

收藏 評(píng)價(jià) 舉報(bào)

• 分享

立即下載

參與評(píng)論

評(píng)論

登錄后參與評(píng)論

登錄或新用戶注冊(cè)

• 微信登錄
• 密碼登錄
• 短信登錄

請(qǐng)用手機(jī)微信掃描下方二維碼
快速登錄或注冊(cè)新賬號(hào)

微信掃碼，手機(jī)電腦聯(lián)動(dòng)

注冊(cè)登錄即表示同意《儀器網(wǎng)服務(wù)條款》和《隱私協(xié)議》

賬  號(hào)：

密  碼：

圖片碼： 看不清？
換一張？

手機(jī)和郵箱號(hào)注冊(cè)新賬號(hào)>> 忘記密碼？

手機(jī)號(hào)：

圖片碼： 看不清？
換一張？

短信碼： 獲取短信碼

手機(jī)和郵箱號(hào)注冊(cè)新賬號(hào)>> 忘記密碼？

更多資料

• Surface-enhanced oxidation and detection of Sunset Y

  Surface-enhanced oxidation and detection of Sunset Y[詳細(xì)]

  2024-09-11 17:47

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• Surface-enhanced oxidation and detection

  Surface-enhanced oxidation and detection[詳細(xì)]

  2024-09-11 19:24

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• high-temperature oxidation resistance

  high-temperature oxidation resistance[詳細(xì)]

  2013-03-01 00:00

  課件

  |

  • 
  • 
  • 
  • 

• Oxidation Profile Analysis

  Oxidation Profile Analysis[詳細(xì)]

  2004-02-19 00:00

  實(shí)驗(yàn)操作

  |

  • 
  • 
  • 
  • 

• 派洛寧Y

  派洛寧Y[詳細(xì)]

  2024-09-27 23:58

  課件

  |

  • 
  • 
  • 
  • 

• Electrochemical Oxidation of MnMnO Films

  Electrochemical Oxidation of MnMnO Films[詳細(xì)]

  2006-02-15 00:00

  選購(gòu)指南

  |

  • 
  • 
  • 
  • 

• 神經(jīng)肽Y（NPY）

  神經(jīng)肽Y（NPY）[詳細(xì)]

  2024-09-28 00:05

  實(shí)驗(yàn)操作

  |

  • 
  • 
  • 
  • 

• Anodic oxidation of zirconium in silicate solu

  Anodic oxidation of zirconium in silicate solu[詳細(xì)]

  2014-08-13 00:00

  安裝說(shuō)明

  |

  • 
  • 
  • 
  • 

• Anodic oxidation of zirconium in silicate solutions

  Herein,astudyofthesurfacemodificationofzirconiumbyanodicoxidationisreported.TheoxidationprocesswascarriedoutinasolutioncontainingK2SiO3andKOH.Theanodizationwasconductedatvoltagesof100,200and400V.Itwasfoundthatthemorphologyofthesurfacedidnotchangeduringtheoxidationofthezirconiumat100and200V.Theapplicationof400Vresultedintheincorporationofsiliconintotheformedoxidelayerandasignificantmodificationofthesurfacemorphology.Theobtainedcoatingsaretypicalofcoatingproducedduringanelectrolyticplasmaoxidationprocessandcontainaconsiderableamountofsilicon.TheanodicoxidationofzirconiumleadstoasignificantimprovementinthecorrosionresistanceofthematerialinthepresenceofRinger’sphysiologicalsolution.[詳細(xì)]

  2018-08-21 10:00

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• Detection of paracetamol by capillary electrophoresi

  Detection of paracetamol by capillary electrophoresi[詳細(xì)]

  2007-06-21 00:00

  標(biāo)準(zhǔn)

  |

  • 
  • 
  • 
  • 

• Better Detection of Insulin Analogues

  Better Detection of Insulin Analogues[詳細(xì)]

  2024-09-17 20:02

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• Y系列壓力表說(shuō)明書(shū)

  壓力表廣泛應(yīng)用于石油、化工、化纖、冶金、電站等工業(yè)部門對(duì)耐蝕、抗振要求較高的工藝流程中測(cè)量各種流體介質(zhì)的壓力．不銹鋼壓力表的整體結(jié)構(gòu)設(shè)計(jì)合理、工藝精致、具有較高的測(cè)量極ng確度和良好的穩(wěn)定性，因此不僅可提供出口，尤為國(guó)內(nèi)用戶對(duì)引進(jìn)國(guó)外先進(jìn)技術(shù)裝備中的同類儀表實(shí)現(xiàn)國(guó)產(chǎn)化的理想配套產(chǎn)品．壓力表主要技術(shù)指標(biāo):1。精度等級(jí):±1.0%;±1.6%;±2.5%。2。表殼直徑:60mm;100mm;150mm;200mm。3。表殼材質(zhì):304不銹鋼，316不銹鋼。4。表殼形式:安全殼構(gòu)造，隔板裝置后釋放5。彈性元件及接頭體材質(zhì):304;316，彈性元件與接頭體氬弧焊接。6。機(jī)芯材質(zhì):304不銹鋼，316不銹鋼。7。接頭螺紋:M14×1.5;G1/4;M20×1.5;1/2NPT等。8。測(cè)量范圍:-0.1~0MPa或,0.1~160MPa9。指針:普通10。表玻璃:有機(jī)玻璃、安全型雙層玻璃11。耐震型充填材質(zhì)甘油98%(可選擇硅油、氟油或其它類別)12。使用環(huán)境溫度:1)-25~70℃(外殼內(nèi)充液)2)-40~70℃(外殼內(nèi)不充液)壓力表測(cè)量范圍、極ng確度等級(jí)表盤直徑（mm）測(cè)量范圍(MPa)精度度等級(jí)(%)￠600~0.1、0~0.16、0~0.25、0~0.4、0~0.6、0~1、0~1.6、0~2.5、0~4、0~6、0~10、0~16、0~25、0~40、0~60、0~100；-0.1~0、-0.1~0.06、-0.1~0.15、-0.1~0.3、-0.1~0.5、-0.1~0.9、-0.1~1.5、-0.1~2.42.5(1.6)￠1000~0.1、0~0.16、0~0.25、0~0.4、0~0.6、0~1、0~1.6、0~2.5、0~4、0~6、0~10、0~16、0~25、0~40、0~60、0~100；-0.1~0、-0.1~0.06、-0.1~0.15、-0.1~0.3、-0.1~0.5、-0.1~0.9、-0.1~1.5、-0.1~2.41.6(1.0)￠1500~0.1、0~0.16、0~0.25、0~0.4、0~0.6、0~1、0~1.6、0~2.5、0~4、0~6、0~10、0~16、0~25、0~40、0~60、0~100；-0.1~0、-0.1~0.06、-0.1~0.15、-0.1~0.3、-0.1~0.5、-0.1~0.9、-0.1~1.5、-0.1~2.41.6(1.0)注：括號(hào)內(nèi)的精度等級(jí)僅供特殊訂貨。壓力表[詳細(xì)]

  2018-11-10 10:00

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• 人神經(jīng)肽Y說(shuō)明書(shū)

  人神經(jīng)肽Y說(shuō)明書(shū)[詳細(xì)]

  2024-10-10 14:23

  操作手冊(cè)

  |

  • 
  • 
  • 
  • 

• Observing Oxidation Kinetics On an Aluminium Alloy S

  Observing Oxidation Kinetics On an Aluminium Alloy S[詳細(xì)]

  2005-01-12 00:00

  選購(gòu)指南

  |

  • 
  • 
  • 
  • 

• High-temperature oxidation of CrN/AlN multilayer coatings

  High-temperature oxidation of CrN/AlN multilayer coatings[詳細(xì)]

  2007-08-10 00:00

  其它

  |

  • 
  • 
  • 
  • 

• Observing Oxidation Kinetics On an Aluminium Alloy S

  Observing Oxidation Kinetics On an Aluminium Alloy S[詳細(xì)]

  2015-09-22 00:00

  選購(gòu)指南

  |

  • 
  • 
  • 
  • 

• A facile and sensitive chemiluminescence detection o

  A facile and sensitive chemiluminescence detection o[詳細(xì)]

  2007-06-21 00:00

  選購(gòu)指南

  |

  • 
  • 
  • 
  • 

• Detection of adulteration in camellia seed oilses

  Anelectronicnosewasusedforthedetectionofmaizeoiladulterationincamelliaseedoilandsesameoil.Theresultsofmultivariateanalysisofvarianceshowedthatthesensorsignalsofdifferentkindsofoilaresignificantlydifferentfromeachother.Prin-cipalcomponentanalysisPCAcannotbeusedtodiscriminatetheadulterationofcamelliaseedoil,butcanbeusedinthediscriminationofadulterationinsesameoil.LineardiscriminantanalysisLDAismoreeffectivethanPCAandcanbeusedinadulterationdiscriminationforbothcamelliaseedoilandsesameoil.InordertocheckthediscriminativepowerofLDA,canonicaldiscriminantanalysiswasperformedaswell.Acceptableresultswerealsoobtained:Theaccuracyofpredictionwas83.6%forcamelliaseedoiland94.5%forsesameoil.TheartificialneuralnetworkANNmodelwasusedtodetectthepercentageofadulterationincamelliaseedoilandsesameoil.Theresultsshowedthat,basedonANNasitspatternrecognitiontechnique,theelec-tronicnosecannotpredictthepercentageofadulterationincamelliaseedoil,butcanbeusedinthequantitativedeterminationofadulterationinsesameoil.[詳細(xì)]

  2018-08-16 10:00

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• Electronic nosedata analysis for detection of mai

  an!°electronicnose!±hasbeenusedforthedetectionofadulterationsofsesameoil.thesystem,comprising10metaloxidesemiconductsensors,wasusedtogenerateapatternofthevolatilecompoundspresentinthesamples.priortodifferentsupervisedpatternrecognitiontreatments,featureextractiontechniqueswereemployedtochooseasetofoptimaldiscriminantvariables.principalcomponentanalysispca,fisherlineartransformationflt,stepwiselineardiscriminantanalysisstep-lda,se-lectionbyfisherweightssfwwereused,respectively.andthen,lineardiscriminantanalysislda,probabilisticneuralnetworkspnn,backpropagationneuralnetworksbpnnandgeneralregressionneuralnetworkgrnnwereappliedaspatternrecognitiontechniquesfortheelectronicnose.asforldaandpnn,fltwasthemosteffectivefeatureextractionmethod,whilestep-ldawasthemosteffectivewayforbpnnandfltwasmoresuitableforgrnn.withonlyonesamplemisclassi?edinourexperiment,ldaismorepowerfulthanpnn.excellentresultswereobtainedinthepredictionofpercentageofadulterationinsesameoilbybpnnandgrnn.aftertrainingforsometime,bpnncouldpredicttheadulterationquantitativelymorepreciselythangrnn,whereaswithfltasitsfeatureextractionmethodandwithoutiterativetraining,grnncouldalsoyieldratheracceptableresults.?2006elsevierb.v.allrightsreserved.[詳細(xì)]

  2018-08-16 10:00

  產(chǎn)品樣冊(cè)

  |

  • 
  • 
  • 
  • 

• Advances of Optical Rotation Detection

  Advances of Optical Rotation Detection[詳細(xì)]

  2024-09-11 18:03

  操作手冊(cè)

  |

  • 
  • 
  • 
  •