What are some of the applications of computational chemistry?

Answer 1

Among the applications I am aware of and those I discovered on the ACS website are:

Plus extra!

For a more thorough overview of computational chemistry, including its objectives and difficulties, continue reading below.

A QUICK Introduction to Computer Chemistry

I work in the field of computational chemistry, which is chemistry that uses powerful computers to perform calculations that would normally take humans a very long time to complete on paper, or even to examine molecules that are hard to see in the real world.

We could calculate ground-state energy, vibrational frequencies, specific heat capacity, enthalpy, entropy, and other semi-basic quantities.

The most common equation solved in this field is the Schrodinger equation, which contains #psi#, the wave function which represents a quantum mechanical system, such as an atom or molecule.
#hatHpsi = Epsi#
It just so happens that to solve this equation, we can write linear combinations using the wave function #psi#.

HOW CAN WE GO ABOUT THIS?

To create molecular orbitals, for example, take this linear combination of atomic orbitals:

#color(blue)(psi_("MO") = sum_(i=1)^(n) c_iphi_i^"AO" = c_1phi_1^"AO" + c_2phi_2^"AO" + . . . + c_nphi_n^"AO")#

where

And there exist many more for each type of molecular orbital (#sigma_(2s)#, #pi_(2px)#, etc). So we might have something like this as a basic example to solve:
#psi_(pi_(2px)) = c_1phi_(2pxA) + c_2phi_(2pxB)# #psi_(pi_(2py)) = c_3phi_(2pyA) + c_4phi_(2pyB)# #psi_(sigma_(2pz)) = c_5phi_(2sA) + c_6phi_(2pzB)#

(Don't think that looks easy? It's not. Many algorithms need to solve enormous systems of equations through looping and trial-and-error calculations, which can get very intensive.)

In computational chemistry, it is useful to solve systems of equations like this (one equation for each molecular orbital) using matrices and taking the determinant. An example of a matrix is #[(2,0),(4,7)]#, and its determinant would be #2*7 - 4*0 = 14#.

THE DIFFICULTY OF COMPUTATIONAL DESIGN

It becomes more difficult and harder to solve matrices of higher order (larger dimension), so we have to program powerful computers to solve them as efficiently as possible.

Depending on the size of the molecule, calculations can take hours or days at times. For example, tetracene, which has 18 molecular orbitals, can be computationally demanding for many computers.

For example, as long as we continue to use the current techniques, it will be physically impossible to compute the wave function for a 54-orbital graphene sheet (which makes a good semiconductor) like (5a,4z)-periacene. I am currently developing a way to overcome this obstacle.

Computational chemists have an obligation to program the computer to perform calculations consistently because of the way computational chemistry generalizes its variables to make it easier for the computer to use in multiple scenarios.

Consequently, computing molecular properties consistently in a fast, accurate, and efficient manner is the primary objective of computational chemistry.

Sign up to view the whole answer

By signing up, you agree to our Terms of Service and Privacy Policy

Sign up with email
Answer 2

Some applications of computational chemistry include drug discovery and development, material science, environmental chemistry, catalysis, and understanding chemical reactions at a molecular level.

Sign up to view the whole answer

By signing up, you agree to our Terms of Service and Privacy Policy

Sign up with email
Answer 3

Some applications of computational chemistry include:

  1. Drug Discovery and Design: Computational chemistry is used to simulate molecular interactions between potential drug compounds and target biomolecules, aiding in the discovery and design of new drugs with improved efficacy and reduced side effects.

  2. Material Science: Computational methods are employed to study the properties and behavior of materials at the atomic and molecular level, facilitating the design of new materials with specific properties for various applications, such as in electronics, nanotechnology, and energy storage.

  3. Catalysis: Computational chemistry is used to model and optimize catalysts for chemical reactions, leading to the development of more efficient and sustainable processes in industries such as petroleum refining, pharmaceuticals, and renewable energy production.

  4. Environmental Chemistry: Computational tools help understand complex environmental processes such as atmospheric reactions, pollutant degradation, and environmental remediation, aiding in the development of strategies for pollution prevention and control.

  5. Biochemistry and Molecular Biology: Computational methods are utilized to investigate biomolecular structures, dynamics, and interactions, providing insights into biological processes, protein folding, enzyme mechanisms, and drug-protein interactions.

  6. Quantum Chemistry: Computational quantum chemistry techniques are employed to study electronic structure and properties of atoms and molecules, providing fundamental understanding of chemical bonding, reaction mechanisms, and spectroscopic properties.

  7. Predictive Modeling: Computational chemistry allows for the prediction of chemical properties, reactivity, and behavior of molecules without the need for costly and time-consuming experimental trials, thus accelerating research and development in various fields.

  8. Energy Research: Computational methods are applied in the development of new materials and technologies for energy storage, conversion, and utilization, contributing to the advancement of renewable energy sources and addressing challenges related to energy sustainability and climate change mitigation.

Sign up to view the whole answer

By signing up, you agree to our Terms of Service and Privacy Policy

Sign up with email
Answer from HIX Tutor

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.

Not the question you need?

Drag image here or click to upload

Or press Ctrl + V to paste
Answer Background
HIX Tutor
Solve ANY homework problem with a smart AI
  • 98% accuracy study help
  • Covers math, physics, chemistry, biology, and more
  • Step-by-step, in-depth guides
  • Readily available 24/7