(E)-1,4-bis-(3-nitro-phenyl)-1,4-diphenyl-butatriene | 116028-60-5

• 分子结构分类: 有机化合物 - 苯类化合物 - 苯和取代衍生物
• 英文名称: (E)-1,4-bis-(3-nitro-phenyl)-1,4-diphenyl-butatriene
• 英文别名: 1,4-Diphenyl-1,4-bis-(m-nitro-phenyl)-butatrien；cis-1,4-Bis-(3-nitro-phenyl)-1,4-diphenyl-butatrien；trans-1,4-Bis-(3-nitro-phenyl)-1,4-diphenyl-butatrien；(E)-1,4-bis-(3-nitro-phenyl)-1,4-diphenyl-butatriene；(E)-1,4-Bis-(3-nitro-phenyl)-1,4-diphenyl-butatrien
• CAS: 116028-60-5
• 化学式: C₂₈H₁₈N₂O₄
• 分子量: 446.462
• InChiKey: RODSOKBAMLYWFA-BYYHNAKLSA-N

计算性质

• 辛醇/水分配系数(LogP)：
  6.82
• 重原子数：
  34.0
• 可旋转键数：
  6.0
• 环数：
  4.0
• sp3杂化的碳原子比例：
  0.0
• 拓扑面积：
  86.28
• 氢给体数：
  0.0
• 氢受体数：
  4.0

反应信息

• 作为反应物：
  描述：

  (E)-1,4-bis-(3-nitro-phenyl)-1,4-diphenyl-butatriene 、 苯 生成 alkaline earth salt of/the/ methylsulfuric acid
  参考文献：
  名称：

  Screening stochastic Life Cycle assessment inventory models

  摘要：

  A screening methodology is presented that utilizes the linear structure within the deterministic life cycle inventory (LCI) model. The methodology ranks each input data element based upon the amount it contributes toward the final output. The identified data elements along with their position in the deterministic model are then sorted into descending order based upon their individual contributions. This enables practitioners and model users to identify those input data elements that contribute the most in the inventory stage. Percentages of the top ranked data elements are then selected, and their corresponding data quality index (DQI) value is upgraded in the stochastic LCI model. Monte Carlo computer simulations are obtained and used to compare the output variance of the original stochastic model with modified stochastic model. The methodology is applied to four real-world beverage delivery system LCA inventory models for verification. This research assists LCA practitioners by streamlining the conversion process when converting a deterministic LCI model to a stochastic model form. Model users and decision-makers can benefit from the reduction in output variance and the increase in ability to discriminate between product system alternatives.

  DOI：

  10.1007/bf02978906