How to Resolve Convergence Failures in Gaussian NH3+ Calculations?

  • Thread starter bcjochim07
  • Start date
  • Tags
    Gaussian
In summary, the conversation discusses the use of gaussian to calculate the potential energy surface for NH3+, but the person is having issues with convergence failures. They searched online and found that using SCF=qc can sometimes help with convergence failures. They also share the input they used for the calculation and mention that the scan failed due to an error related to curvature, possibly because NH3+ is planar. They ask for suggestions on how to solve the issue.
  • #1
bcjochim07
374
0

Homework Statement


I am using gaussian to calculate the potential energy surface for NH3+, but I have been having troubles with convergence failures. I did some searching on the internet and found that using SCF=qc can sometimes help with convergence failures since it instruct the program to have less strict criteria. So here's what I entered:

Route Section: #MP2 cc-PVDZ SCF=qc Scan Pop=Reg Guess=INDO

Title: Ammonia Cation Scan

Charge, Multiplicity: 1 2

N
X 1 1.0
H 1 nh 2 xnh
H 1 nh 2 xnh 3 120.0
H 1 nh 2 xnh 3 -120.0

nh 0.5 60 .04
xnh 29.0 60 1.0

And the scan failed after about 2 hrs. and 44 min. I looked at the output file, and it said that the error was due to the curvature, and I'm not quite sure what that means. Any suggestions?


Homework Equations





The Attempt at a Solution

 
Physics news on Phys.org
  • #2
Anyone? Is this maybe due to the fact that NH3+ is planar?
 

FAQ: How to Resolve Convergence Failures in Gaussian NH3+ Calculations?

What is a Gaussian distribution?

A Gaussian distribution, also known as a normal distribution, is a type of probability distribution that is symmetrical around its mean. It is often used to model random variables in natural phenomena, such as heights or test scores.

How is a Gaussian distribution different from other distributions?

Unlike other distributions, a Gaussian distribution has a bell-shaped curve, with most data clustered around the mean and decreasing in frequency as it moves away from the mean. It also has a defined standard deviation, which allows for precise calculations of the likelihood of a given value occurring.

What is the significance of Gaussian distributions in science?

Gaussian distributions are commonly used in statistical analysis and modeling because many natural phenomena follow this distribution. They are also useful in hypothesis testing, confidence intervals, and predictive modeling.

How can I recognize a Gaussian distribution in my data?

You can recognize a Gaussian distribution by visualizing your data in a histogram or a probability plot. If the data points form a bell-shaped curve, then it is likely that your data follows a Gaussian distribution. Additionally, you can use statistical tests, such as the Shapiro-Wilk test, to determine if your data is normally distributed.

Are there any limitations to using Gaussian distributions?

While Gaussian distributions are useful in many applications, they may not be appropriate for all types of data. In some cases, the data may follow a different distribution, such as a skewed or bimodal distribution. It is important to assess the data and choose the appropriate distribution for your analysis.

Similar threads

A How can I tell Gaussian to read coordinates as Cartesian?
Replies
1
Views
2K
MCNP Cylindrical Phantom Calculation Help
Replies
1
Views
3K
Do Google Ads Significantly Impact Website Load Times?
Replies
1
Views
7K

Hot Threads

Recent Insights

Back
Top