semiempirical

简明释义

英[ˌsemɪɪmˈpɪrɪkəl]美[ˈsemɪemˈpɪrɪkəl]

adj. 半经验的

英英释义

单词用法

同义词

反义词

例句

1.In this paper AM1 semiempirical quantum chemical calculation was used to study the motion of phenyl rings in PEEK chains.

本文使用AM 1半经验量子化学计算研究了苯环在PEEK链内的运动。

2.Experimental investigations show that the semiempirical concavity calculation formulation given here are practical.

提出的计算凹度的半经验公式，经过实践考验证明具有一定的实用价值。

3.The penetration predicted by this model is fairly close to the result calculated by Hiroyasu's semiempirical formula.

由此模型算得的穿透距离与広安博之半实验公式的计算结果相当接近。

4.The electronic structures of 10 kinds of D-form and L-form amino acids have been investigated by employing AM1 semiempirical quantum chemical method firstly.

首次采用AM1半经验量子化学计算方法研究了10种D型和L型氨基酸的电子结构。

5.The molecular orbital coefficients are determined by means of a semiempirical method in the calculation.

计算中，用半经验方法确定了分子轨道系数。

6.The structure antioxidation relationship of typical flavonoid antioxidants is investigated by means of structural chemistry and the semiempirical calculation method of quantum chemistry.

用结构化学和量子化学半经验计算方法研究几种典型黄酮类化合物，探讨影响黄酮类化合物抗氧化活性的结构因素。

7.A semiempirical inverse equation was used to characterize the HTC-air gap relation across the whole stages for experimental data from literature.

通过分析文献实验数据得出了在整个凝固过程中传热系数与空气隙成反比的半经验耦合表达式。

8.In computational chemistry, we often use semiempirical 半经验的 methods to simplify calculations.

在计算化学中，我们常常使用半经验的semiempirical方法来简化计算。

9.The semiempirical 半经验的 techniques are particularly useful for large systems.

对于大型系统，半经验的semiempirical技术特别有用。

10.Researchers applied a semiempirical 半经验的 approach to predict reaction rates.

研究人员应用了一个半经验的semiempirical方法来预测反应速率。

11.The semiempirical 半经验的 model provided a good approximation for the molecular properties.

这个半经验的semiempirical模型为分子性质提供了良好的近似。

12.Using semiempirical 半经验的 formulas can save time in theoretical studies.

使用半经验的semiempirical公式可以节省理论研究中的时间。

作文

In the realm of scientific research and theoretical modeling, various methodologies are employed to bridge the gap between empirical data and theoretical predictions. One such approach is referred to as semiempirical, which combines elements of both empirical and theoretical frameworks. The term semiempirical can be broken down into two parts: 'semi,' meaning partially, and 'empirical,' which relates to knowledge acquired through observation or experimentation. This hybrid methodology is particularly prevalent in fields such as chemistry, physics, and materials science, where complex systems can be challenging to analyze using purely theoretical or purely empirical methods.The significance of semiempirical approaches lies in their ability to simplify complex calculations while still providing reasonably accurate results. For instance, in computational chemistry, researchers often utilize semiempirical methods to predict molecular behavior without needing to solve all quantum mechanical equations at a high level of precision. These methods rely on experimental data to parameterize certain aspects of the model, thus allowing scientists to make predictions about new compounds or reactions based on existing knowledge.One of the most notable examples of semiempirical methods is the PM3 (Parameterized Model 3) technique used in quantum chemistry. PM3 is designed to provide a balance between computational efficiency and accuracy by employing parameters derived from experimental data. Researchers can use PM3 to calculate molecular geometries and energies, which helps in understanding reaction mechanisms or the stability of different molecular configurations. By relying on semiempirical methods like PM3, scientists can save significant amounts of time and computational resources while still gaining valuable insights into chemical systems.Moreover, the application of semiempirical methods extends beyond chemistry. In physics, for example, models that incorporate semiempirical techniques can help in understanding phenomena like nuclear reactions or phase transitions in materials. These models often integrate empirical observations with theoretical constructs, yielding results that are both practical and informative. Such approaches are essential when dealing with systems that are too complex for complete theoretical treatment but where empirical data alone may not provide sufficient understanding.Despite their advantages, semiempirical methods do have limitations. The accuracy of predictions made using these approaches heavily relies on the quality and relevance of the empirical data used to parameterize the models. If the underlying data is flawed or not representative of the system being studied, the results can be misleading. Therefore, it is crucial for researchers to carefully select the empirical data that informs their semiempirical models, ensuring that it aligns closely with the conditions and variables they are investigating.In conclusion, semiempirical methods play a vital role in contemporary scientific research by offering a pragmatic approach to analyzing complex systems. By integrating empirical data with theoretical frameworks, these methods enable scientists to make informed predictions and gain deeper insights into various phenomena. As research continues to evolve, the importance of semiempirical approaches will likely grow, highlighting the need for a balanced perspective that values both empirical evidence and theoretical understanding in the pursuit of knowledge. Ultimately, the fusion of these methodologies exemplifies the dynamic nature of scientific inquiry, where collaboration between observation and theory paves the way for innovation and discovery.

在科学研究和理论建模的领域中，各种方法被用来弥合经验数据与理论预测之间的差距。其中一种方法被称为半经验法，它结合了经验和理论框架的元素。术语半经验法可以分为两部分：“半”意为部分，“经验”与通过观察或实验获得的知识有关。这种混合的方法在化学、物理和材料科学等领域尤为普遍，因为复杂系统在使用纯理论或纯经验方法分析时可能会面临挑战。半经验法方法的重要性在于它们能够简化复杂计算，同时仍提供合理准确的结果。例如，在计算化学中，研究人员通常利用半经验法来预测分子行为，而无需以高精度解决所有量子力学方程。这些方法依赖于实验数据来参数化模型的某些方面，从而使科学家能够根据现有知识对新化合物或反应做出预测。一个最著名的半经验法例子是量子化学中使用的PM3（参数化模型3）技术。PM3旨在通过使用从实验数据中得出的参数，在计算效率和准确性之间提供平衡。研究人员可以使用PM3计算分子几何形状和能量，这有助于理解反应机制或不同分子构型的稳定性。通过依赖像PM3这样的半经验法，科学家可以节省大量时间和计算资源，同时仍能获得对化学系统的宝贵见解。此外，半经验法的应用超越了化学。在物理学中，例如，结合半经验法技术的模型可以帮助理解核反应或材料中的相变等现象。这些模型通常将经验观察与理论构造结合起来，产生既实用又信息丰富的结果。当处理过于复杂而无法完全进行理论处理的系统时，这种方法至关重要，但仅凭经验数据可能不足以提供足够的理解。尽管有其优势，半经验法也存在局限性。使用这些方法所做预测的准确性在很大程度上依赖于用于参数化模型的经验数据的质量和相关性。如果基础数据存在缺陷或未能代表所研究的系统，则结果可能会误导。因此，研究人员必须仔细选择影响其半经验法模型的经验数据，确保其与他们正在调查的条件和变量密切相关。总之，半经验法在当代科学研究中发挥着至关重要的作用，通过提供一种务实的方法来分析复杂系统。通过将经验数据与理论框架相结合，这些方法使科学家能够做出明智的预测，并深入了解各种现象。随着研究的不断发展，半经验法方法的重要性可能会进一步增强，强调在追求知识的过程中，经验证据与理论理解之间的平衡视角的必要性。最终，这些方法的融合体现了科学探究的动态特性，在观察与理论之间的合作为创新和发现铺平了道路。