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Mail : Dept. Time-dependent density functional theory TD-DFT is currently the only tractable ab initio method for calculating electronic excitation energies in systems with more than 20â€”30 atoms. However, the high level of accuracy exhibited by TD-DFT in small-molecule calculations does not always carry over to larger systems. Moreover, the calculation of excited states in very large molecules those containing hundreds of atoms described at the DFT levelwhile technically feasible, is neither trivial nor routine.

Thus, we are working to extend both the computational feasibility via improved algorithms and the accuracy by means of improved functionals of large-molecule TD-DFT calculations.

The TDKS approach can describe strong-field, attosecond electron dynamics, and can also provide broad-band excitation spectra from valence- to core-level excitations in a single shot. So far, we have developed new propagators for the TDKS equation that facilitate longer time steps, with better numerical stability, as compared to previous approaches.

In some of our group's early work applying TD-DFT to relatively large molecules and especially clusters or other systems with explicit solvent molecules, we pointed out that the appearance of spurious, low-energy charge-transfer CT excited states is practically inevitable in large systems, when standard functionals such as BLYP, B3LYP, or PBE0 are employed.

The density of spurious states grows with the size of the molecule or cluster, and these spurious states can anomalously borrow intensity from the real bright states. This problem is substantially ameliorated by the use of "long-range corrected" LRC density functionals, also known as "range-separated hybrid" functionals.

These functionals have the correct asymptotic distance dependence for a charge-separated state, and thereby eliminate spurious CT states, at least in the low-energy UV region of the spectrum. Such a calculation would not have been possible using standard functionals e. A variety of LRC functionals have been developed by several different research groups. An important observation in these studies is that the optimal parameters for ground-state thermochemistry are often quite different from those that afford the best excitation energies, and to obtain a robust functional one must carefully balance the parameterization.

At the same time, the accuracy of ground-state predictions is not significantly degraded. These are the couplings between excited states that are needed for nonadiabatic molecular dynamics simulations, and our algorithm allows one to perform such calculations, and to locate minimum-energy crossing points along conical seams and minimum-energy photochemical pathways, at DFT cost. Unlike derivative couplings computing using ordinary spin-conserving CIS or TD-DFT, spin-flip methods correctly describe the topology of the two-dimensional branching space around a conical intersection.

The example shown here is the conical intersection corresponding to the Jahn-Teller effect in the H 3 radical; in this particular case, there is a symmetry-required ground-state degeneracy, and a conical intersection that lifts the degeneracy, when the molecule has D 3h symmetry.

While H 3 is only a toy model, these methods are actively being used to understand excited-state dynamics in complex systems such as DNA. A "spin-complete" version of spin-flip TD-DFT, which resolves the spin contamination problem with that method, has also been developed. Natural transition orbitals for several electronic transitions of the aqueous electron.Chemissian is an analyzing tool of the molecule electronic structure and spectra.

It allows one to build and analyze molecular orbital energy-level diagrams Hartree-Fock and Kohn-Sham ; analyze calculated experimental UV-VIS electronic spectrum and compare it with experimental one on the same plot; calculate and visualize natural transition orbitals, electronic and spin densities and prepare them for publication.

Chemissian tools can be used to investigate the nature of transitions in UV-vis spectra, bonding nature, etc. Chemissian has a rich graphical analyzer of composition of MOs and a wide range of capabilities to analyze electronic spectra of molecules. In a single document accumulate and analyze results of several calculations, e. As a simple example: having one the source reagents and the final reaction product one wants to understand the changes that have occurred at the electronic structure level.

For this it is possible to add several calculations reagent and product on a single diagram, and they will be presented in the common energy scale; one will be able to switch between different calculations, compare and analyze electronic structures of all of the participants at the same time. Save the obtained document in a special file format, which allows to keep all data in a single compressed file uncompressed wave function takes up a lot of disk space!

For the news see news page Chemissian Features: Build Molecular Orbitals energy level diagrams Due to the integrated graphical editor it is easy to add text labels to MO diagrams, add connecting lines between MO energy levels, occupy the energy levels with the electrons: One can analyze the electronic structure of molecules.

It is possible to move between energy levels simply using the keyboard or the mouse cursor. Having experimental spectra you can compare it with the calculated ones on a single diagram in the same wavelength scale. Any number of spectra can be added on a single diagram, which is useful, e. Like in the MO diagram editor it is possible to move between peaks in a spectrum and correlate the current peak with transitions between MO levels: Chemissian allows editing the obtained spectrum diagram by adding text labels and other graphical objects.

Different energy units are available. Using Chemissian tools it is easy to investigate and interpret the nature of spectra transitions, e. Calculating and visualizing natural transition orbitals: Analyze electronic density distribution Using Chemissian it is possible to analyze the electronic and spin density distribution, difference "defomation" density, individual molecular orbital, and any arbitrary linear combination of them e.

It is also possible to analyze "generalized bond, e. Work with several calculations at the same time In a single document accumulate and analyze results of several calculations, e. Save results in a single file Save the obtained document in a special file format, which allows to keep all data in a single compressed file uncompressed wave function takes up a lot of disk space!The TD-DFT method in Gaussian makes it practical to study excited state systems since it produces results that are comparable in accuracy to ground state DFT calculations.

Sometimes, characterizing the specific transition associated with an excited state is straightforward. In other instances, however, the state may be described by a substantial list of orbital transitions with coefficients that are similar in magnitude, without any single dominant component.

Natural transition orbitals NTOs can be a helpful way of obtaining a qualitative description of electronic excitations.

They do so by transforming the ordinary orbital representation into a more compact form in which each excited state is expressed as a single pair of orbitals if possible : the NTO transition occurs from excited particle occupied to the empty hole unoccupied.

See [ Martin03 ] for a detailed description of natural transition orbitals. Here is an example input file for the first step. It is a TD-DFT calculation on a molecular structure that we have previously optimized and verified as a minimum:.

Now we need to run a second calculation to generate and save the NTOs for visualization in GaussView or another graphics package.

In this example, we compute the NTOs for the third excited state:. GaussView and other graphics packages will visualize whatever orbitals are present in the checkpoint file, so no special handling is required inside the visualization program. Note that we use a separate checkpoint file for the NTOs. If you plan to compute the NTOs for multiple states, use a different checkpoint file for each state.

For example, the following second job step within the preceding input file will generate and save the NTOs for the sixth excited state:. It copies information from the old checkpoint file tddft. If you are using an older version of Gaussian, you should manually copy the checkpoint file to a new name before the second generating the NTOs; you will use the name of the copy as the checkpoint file in the second job. We will consider the 19th excited state of Pt dcbpy Cl 2 as an example see [ Roy09 ] for details about this compound.

The component transitions of this excited state are numerous, and no one or two transitions is decisively dominant. The following figure shows the relevant molecular orbitals and transitions, labeling each with the corresponding coefficient:. When we compute the NTOs for this state, we obtain two pairs. This greatly simplifies the process of characterizing this transition. Examine the calculation results to determine the excited state of interest.

Run a single point calculation to generate the NTOs for the desired excited state. The third step can be repeated for each excited state in which you are interested.

### 7.3 Time-Dependent Density Functional Theory (TDDFT)

The following figure shows the relevant molecular orbitals and transitions, labeling each with the corresponding coefficient: When we compute the NTOs for this state, we obtain two pairs. References [ Martin03 ] Martin, R.The capabilities of the module are summarized as follows:.

The accuracy of CIS and TDHF for excitation energies of closed-shell systems are comparable to each other, and are normally considered a zeroth-order description of the excitation process. However, for open-shell systems, the errors in the CIS and TDHF excitation energies are often excessive, primarily due to the multi-determinantal character of the ground and excited state wave functions of open-shell systems in a HF reference.

The scaling of the computational cost of a CIS or TDHF calculation per state with respect to the system size is the same as that for a HF calculation for the ground state, since the critical step of the both methods are the Fock build, namely, the contraction of two-electron integrals with density matrices. It is usually necessary to include two sets of diffuse exponents in the basis set to properly account for the diffuse Rydberg excited states of neutral species.

In general, the exchange-correlation functionals that are widely used today and are implemented in NWChem work well for low-lying valence excited states. However, for high-lying diffuse excited states and Rydberg excited states in particular, TDDFT employing these conventional functionals breaks down and the excitation energies are substantially underestimated.

A rough but useful index is the negative of the highest occupied KS orbital energy; when the calculated excitation energies become close to this threshold, these numbers are most likely underestimated relative to experimental results.

This may be traced to the fact that, in DFT, the ground state wave function is represented well as a single KS determinant, with less multi-determinantal character and less spin contamination, and hence the excitation thereof is described well as a simple one electron transition. The computational cost per state of TDDFT calculations scales as the same as the ground state DFT calculations, although the prefactor of the scaling may be much greater in the former.

Recently, we proposed a new, expedient, and self-contained asymptotic correction that does not require an ionization potential or shift as an external parameter from a separate calculation. In this scheme, the shift is computed by a semi-empirical formula proposed by Zhan, Nichols, and Dixon[6]. Both Casida-Salahub scheme and this new asymptotic correction scheme give considerably improved Koopmans type ionization potentials and Rydberg excitation energies.

The latter, however, supply the shift by itself unlike to former. When no second argument of the task directive is given, a single-point excitation energy calculation will be assumed. For geometry optimizations, it is usually necessary to specify the target excited state and its irreducible representation it belongs to. See the section of Sample input and output for more details. Note that the keyword for the asymptotic correction must be given in the DFT input block, since all the effects of the correction and also changes in the computer program occur in the SCF calculation stage.

These keywords toggle the Tamm-Dancoff approximation. However, the computational cost is slightly greater in the latter due to the fact that the latter involves a non-Hermitian eigenvalue problem and requires left and right eigenvectors while the former needs just one set of eigenvectors of a Hermitian eigenvalue problem. The latter has much greater chance of aborting the calculation due to triplet near instability or other instability problems.

One can specify the number of excited state roots to be determined. The default value is 1. It is advised that the users request several more roots than actually needed, since owing to the nature of the trial vector algorithm, some low-lying roots can be missed when they do not have sufficient overlap with the initial guess vectors.

Typically, 10 to 20 trial vectors are needed for each excited state root to be converged. However, it need not exceed the product of the number of occupied orbitals and the number of virtual orbitals. The default value is The threshold refers to the norm of residual, namely, the difference between the left-hand side and right-hand side of the matrix eigenvalue equation with the current solution vector. With the default value of 1e-4, the excitation energies are usually converged to 1e-5 hartree.

It typically takes iterations for the Davidson algorithm to get converged results. At the moment, excited-state first geometry derivatives can be calculated analytically for a set of functionals, while excited-state second geometry derivatives are obtained by numerical differentiation.

These keywords may be used to specify which excited state root is being used for the geometrical derivative calculation. For instance, when TARGET 3 and TARGETSYM a1g are included in the input block, the total energy ground state energy plus excitation energy of the third lowest excited state root excluding the ground state transforming as the irreducible representation a1g will be passed to the module which performs the derivative calculations.These poles are Bohr frequencies, or in other words the excitation energies.

Operationally, this involves solution of an eigenvalue equation. Elements of are similar. TDDFT is popular because its computational cost is roughly similar to that of the simple CIS method, but a description of differential electron correlation effects is implicit in the method.

On the other hand, standard density functionals do not yield a potential with the correct long-range Coulomb tail, owing to the so-called self-interaction problem, and therefore excitation energies corresponding to states that sample this tail e.

However, see Ref. Richard for a cautionary note regarding this metric. The reference is a high-spin triplet quartet for a system with an even odd number of electrons.

One electron is spin-flipped from an alpha Kohn-Sham orbital to a beta orbital during the excitation.

SF-DFT can describe the ground state as well as a few low-lying excited states, and has been applied to bond-breaking processes, and di- and tri-radicals with degenerate or near-degenerate frontier orbitals.

Shao for extensive benchmarks. Much of chemistry and biology occurs in solution or on surfaces. The molecular environment can have a large effect on electronic structure and may change chemical behavior. This is implemented within the TDA, so. This allows the excited states of a solute molecule to be studied with a large number of solvent molecules reducing the rapid rise in computational cost. The success of this approach relies on there being only weak mixing between the electronic excitations of interest and those omitted from the single excitation space.

For systems in which there are strong hydrogen bonds between solute and solvent, it is advisable to include excitations associated with the neighboring solvent molecule s within the reduced excitation space. The reduced single excitation space is constructed from excitations between a subset of occupied and virtual orbitals.

These can be selected from an analysis based on Mulliken populations and molecular orbital coefficients. For this approach the atoms that constitute the solvent needs to be defined. Alternatively, the orbitals can be defined directly.

There are several points to be aware of:. Remember to set the spin multiplicity to 3 for systems with an even-number of electrons e.Excited states may be obtained from density functional theory by time-dependent density functional theory, [ CasidaDreuw and Head-Gordon ] which calculates poles in the response of the ground state density to a time-varying applied electric field.

These poles are Bohr frequencies, or in other words the excitation energies. Operationally, this involves solution of an eigenvalue equation. TDDFT is popular because its computational cost is roughly similar to that of the simple CIS method, but a description of differential electron correlation effects is implicit in the method.

It is advisable to only employ TDDFT for low-lying valence excited states that are below the first ionization potential of the molecule, [ Casida ] or more conservatively, below the first Rydberg state, and in such cases the valence excitation energies are often remarkably improved relative to CIS, with an accuracy of 0.

On the other hand, standard density functionals do not yield a potential with the correct long-range Coulomb tail, owing to the so-called self-interaction problem, and therefore excitation energies corresponding to states that sample this tail e. Richard for a cautionary note regarding this metric. The reference is a high-spin triplet quartet for a system with an even odd number of electrons. One electron is spin-flipped from an alpha Kohn-Sham orbital to a beta orbital during the excitation.

SF-DFT can describe the ground state as well as a few low-lying excited states, and has been applied to bond-breaking processes, and di- and tri-radicals with degenerate or near-degenerate frontier orbitals. Shao for extensive benchmarks. Much of chemistry and biology occurs in solution or on surfaces. The molecular environment can have a large effect on electronic structure and may change chemical behavior.

Q-Chem is able to compute excited states within a local region of a system through performing the TDDFT or CIS calculation with a reduced single excitation subspace, [ Besley ] in which some of the amplitudes in Eq.

This is implemented within the TDA, so. This allows the excited states of a solute molecule to be studied with a large number of solvent molecules reducing the rapid rise in computational cost. The success of this approach relies on there being only weak mixing between the electronic excitations of interest and those omitted from the single excitation space.

For systems in which there are strong hydrogen bonds between solute and solvent, it is advisable to include excitations associated with the neighboring solvent molecule s within the reduced excitation space. The reduced single excitation space is constructed from excitations between a subset of occupied and virtual orbitals. These can be selected from an analysis based on Mulliken populations and molecular orbital coefficients.

For this approach the atoms that constitute the solvent needs to be defined.A common warning sign of smartphone or Internet addiction is experiencing withdrawal symptoms when you try to cut back on your smartphone use. Do you often absent-mindedly pass the time by using your phone even when there are better things to do. Do you use your phone at all hours of the day and nighteven when it means interrupting other things.

Do you use your phone while driving or doing other activities that require your focused attention. When you leave the house do you ALWAYS have your smartphone with you and feel ill-at-ease when you accidentally leave it at home.

When your phone buzzes do you feel an intense urge to check for texts, tweets, emails, updates, etc. Do you find yourself mindlessly checking your phone many times a day even when you know there is likely nothing new or important to see.

Adapted from: Smartphone Abuse Test by Dr. David Greenfield, The Center for Internet and Technology Addiction.

## Chemissian

There are a number of steps you can take to get your smartphone use under control. While you can initiate many of these measures yourself, an addiction is hard to beat on your own, especially when temptation is always within easy reach.

It can be all too easy to slip back into old patterns of usage. To help you identify your problem areas, keep a log of when and how much you use your smartphone for non-work or non-essential activities.

There are specific apps that can help with this, enabling you to track the time you spend on your phone (see the Resources section below). Are there times of day that you use your phone more. Are there other things you could be doing instead. The more you understand your smartphone use, the easier it will be to curb your habits and regain control of your time.

Recognize the triggers that make you reach for your phone. If you are struggling with depression, stress, or anxiety, for example, your excessive smartphone use might be a way to self-soothe rocky moods.

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Understand the difference between interacting in-person and online. Human beings are social creatures. The inner ear, face, and heart are wired together in the brain, so socially interacting with another person face-to-facemaking eye contact, responding to body language, listening, talkingcan make you feel calm, safe, and understood, and quickly put the brakes on stress. Interacting through text, email or messaging may feel important but it bypasses these nonverbal cues so can never have the same effect on your emotional well-being.

Besides, online friends can't hug you when a crisis hits, visit you when you're sick, or celebrate a happy occasion with you.

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