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相关概念视频

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n) to the number of categories (k).
Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used.
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
Properties of DTFT II01:24

Properties of DTFT II

In the study of discrete-time signal processing, understanding the properties of the Discrete-Time Fourier Transform (DTFT) is crucial for analyzing and manipulating signals in the frequency domain. Several properties, including frequency differentiation, convolution, accumulation, and Parseval's relation, offer powerful tools for signal analysis.
The frequency differentiation property is illustrated by considering a DTFT pair and differentiating both sides with respect to ω. Multiplying by j...
Relation of DFT to z-Transform01:20

Relation of DFT to z-Transform

The Discrete Fourier Transform (DFT) is a crucial tool for analyzing the frequency content of discrete-time signals. It converts a sequence of N samples from the time domain into its corresponding sequence in the frequency domain, where each sample represents a specific frequency component.
To understand how the DFT works, it's helpful to consider the z-transform, which is a method for representing discrete sequences in the complex frequency domain. The z-transform involves summing the terms of...

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Rapid Mix Preparation of Bioinspired Nanoscale Hydroxyapatite for Biomedical Applications
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基准测试DFT近似值用于研究阿帕蒂斯.

Aritri Roy1, Bikash Kanungo2, Puneet Kumar Patra3

  • 1Advanced Technology Development Centre, Indian Institute of Technology Kharagpur, West Bengal, 721302, India. aritrits@kgpian.iitkgp.ac.in.

Physical chemistry chemical physics : PCCP
|November 26, 2024
PubMed
概括
此摘要是机器生成的。

这项研究将密度函数理论 (DFT) 方法用于 apatite 研究的基准. 建议使用optB86b-vdW函数和分散校正来准确预测阿帕特性的特性.

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学计算化学
  • 固态物理 固态物理

背景情况:

  • 对阿帕特质的实验研究是有限的.
  • 密度函数理论 (DFT) 越来越多地用于预测.
  • DFT近似可以导致与实验结果的偏差.

研究的目的:

  • 为了对各种DFT方法进行基准测试,以研究apatites.
  • 确定交换相关性 (XC) 函数,伪潜力 (PPs) 和基础集的最佳组合.
  • 为了提高DFT预测的准确性.

主要方法:

  • 16个XC函数 (有分散校正),5个PP和2个基础集的全面基准测试.
  • 预测的格子参数,弹性常数,散量模量和酸,酸和酸的带间隙的比较.
  • 分析XC近似和分散校正对属性预测的影响.

主要成果:

  • 房地产预测显示,对选择PP和基础集的敏感性较弱.
  • XC近似和分散校正显著影响预测准确性.
  • optB86b-vdW 功能表现出与实验数据最好的一致性.

结论:

  • 建议在使用 DFT 研究 apatites 时进行分散校正,并仔细考虑.
  • 选择B86b-vdW函数被确定为最准确的apatite属性预测.
  • 了解XC的功能性行为对于可靠的DFT研究的apatites至关重要.