Category:Transition states - Revision history

Csheldon: /* Dynamic methods */

2026-06-09T12:34:02Z

Dynamic methods

← Older revision		Revision as of 12:34, 9 June 2026
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	An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.		An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.

	It is difficult to use MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using [[Constrained molecular dynamics\|constrained MD]], e.g. a [[Blue moon ensemble\|blue moon simulation]]{{Cite\|gesvandtnerova:rucco:bucko:2021}}, a path-based coordinate ({{FILE\|IRCCAR}}), or [[metadynamics]]{{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible.		It is difficult to use MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using [[Constrained molecular dynamics\|constrained MD]], e.g. a [[Blue moon ensemble\|blue moon simulation]]{{Cite\|gesvandtnerova:rucco:bucko:2021}}, a path-based coordinate ({{FILE\|IRCCAR}}), or [[metadynamics]] (cf. [[Using metadynamics to train a machine-learned force field\|metadynamics for transition state MLFFs]]){{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible.

	More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.		More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.

Csheldon: /* Dynamic methods */

2026-06-09T12:33:17Z

Dynamic methods

← Older revision		Revision as of 12:33, 9 June 2026
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	More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.		More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.

	*[[Using metadynamics to train a machine-learned force field\|Using metadynamics to train a machine-learned force field for transition states]]

	== Additional resources ==		== Additional resources ==

Csheldon: /* Dynamic methods */

2026-06-09T12:32:21Z

Dynamic methods

← Older revision		Revision as of 12:32, 9 June 2026
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	An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.		An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.

	It is difficult ~~using~~ MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using [[Constrained molecular dynamics\|constrained MD]], e.g. a [[Blue moon ensemble\|blue moon simulation]]{{Cite\|gesvandtnerova:rucco:bucko:2021}}, or [[metadynamics]]{{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible. More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.		It is difficult to use MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using [[Constrained molecular dynamics\|constrained MD]], e.g. a [[Blue moon ensemble\|blue moon simulation]]{{Cite\|gesvandtnerova:rucco:bucko:2021}}, a path-based coordinate ({{FILE\|IRCCAR}}), or [[metadynamics]]{{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible.

			More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.

			*[[Using metadynamics to train a machine-learned force field\|Using metadynamics to train a machine-learned force field for transition states]]

	== Additional resources ==		== Additional resources ==

Csheldon: /* How to */

2026-06-09T11:42:50Z

How to

← Older revision		Revision as of 11:42, 9 June 2026
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	=== How to ===		=== How to ===
	*Training an [[Using metadynamics to train a machine-learned force field\|MLFF for ~~rare events~~ using metadynamics]].		*Training an [[Using metadynamics to train a machine-learned force field\|MLFF for transition states using metadynamics]].

	=== Tutorials ===		=== Tutorials ===

Csheldon: /* Additional resources */

2026-06-09T11:42:39Z

Additional resources

← Older revision		Revision as of 11:42, 9 June 2026
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	=== Books ===		=== Books ===
	*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.		*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.

			=== How to ===
			*Training an [[Using metadynamics to train a machine-learned force field\|MLFF for rare events using metadynamics]].

	=== Tutorials ===		=== Tutorials ===

Csheldon: /* Additional resources */

2026-05-29T10:09:35Z

Additional resources

← Older revision		Revision as of 10:09, 29 May 2026
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	=== Books ===		=== Books ===
	*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.		*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.

	~~=== Lectures ===~~
	*Lecture on modeling chemical reactions (and transition states) using {{Video\|static:tomas:2025\|static approaches}}.
	*Lecture on modeling chemical reactions (and transition states) using {{Video\|dynamic:tomas:2025\|dynamic approaches}}.
	*Lecture on modeling chemical reactions (and transition states) using {{Video\|chem_mlff:ferenc:2025\|machine-learned force fields}}.

	=== Tutorials ===		=== Tutorials ===
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	<!--=== How to ===		<!--=== How to ===
	*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->		*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->

			=== Lectures ===
			*Lecture on modeling chemical reactions (and transition states) using {{Video\|static:tomas:2025\|static approaches}}.
			*Lecture on modeling chemical reactions (and transition states) using {{Video\|dynamic:tomas:2025\|dynamic approaches}}.
			*Lecture on modeling chemical reactions (and transition states) using {{Video\|chem_mlff:ferenc:2025\|machine-learned force fields}}.

	== References ==		== References ==

	[[Category:VASP\|Transition States]][[Category:Ionic minimization]][[Category:Advanced molecular-dynamics sampling]]		[[Category:VASP\|Transition States]][[Category:Ionic minimization]][[Category:Advanced molecular-dynamics sampling]]

Csheldon: /* Additional resources */

2026-05-29T10:09:24Z

Additional resources

← Older revision		Revision as of 10:09, 29 May 2026
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	== Additional resources ==		== Additional resources ==
	=== Books ~~and lectures~~ ===		=== Books ===
	*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.		*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.

			=== Lectures ===
	*Lecture on modeling chemical reactions (and transition states) using {{Video\|static:tomas:2025\|static approaches}}.		*Lecture on modeling chemical reactions (and transition states) using {{Video\|static:tomas:2025\|static approaches}}.
	*Lecture on modeling chemical reactions (and transition states) using {{Video\|dynamic:tomas:2025\|dynamic approaches}}.		*Lecture on modeling chemical reactions (and transition states) using {{Video\|dynamic:tomas:2025\|dynamic approaches}}.

Csheldon: /* Dynamic methods */

2026-05-29T10:08:18Z

Dynamic methods

← Older revision		Revision as of 10:08, 29 May 2026
Line 38:		Line 38:
	An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.		An alternative to the static approach for modeling the TS, is to use a dynamic (or anharmonic) approach, that is to use molecular dynamics (MD). The static approach models a single structure for the reactant R, TS, and product P. An MD simulation treats each of these states as an ensemble, a combination of many possible structures.

	It is difficult using MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using constrained MD, e.g. a blue moon simulation{{Cite\|gesvandtnerova:rucco:bucko:2021}}, or metadynamics{{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible. More detail for each of these methods, as well as other advanced MD approaches can be found on the ~~relevant~~ [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] page.		It is difficult using MD to find uncommon states or rare events, such as the TS. An MD simulation is for a short period of time, typically only femto or picoseconds, while seconds would be required to encounter a TS. However, using [[Constrained molecular dynamics\|constrained MD]], e.g. a [[Blue moon ensemble\|blue moon simulation]]{{Cite\|gesvandtnerova:rucco:bucko:2021}}, or [[metadynamics]]{{Cite\|klein:2006}}{{Cite\|tiwary:parrinello:2006}}, finding even rare events like the TS becomes feasible. More detail for each of these methods, as well as other advanced MD approaches can be found on the [[:Category:Advanced molecular-dynamics sampling\|advanced MD]] category page.

	== Additional resources ==		== Additional resources ==

Csheldon: /* Additional resources */

2026-03-24T13:50:51Z

Additional resources

← Older revision		Revision as of 13:50, 24 March 2026
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	=== Books and lectures ===		=== Books and lectures ===
	*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.		*''Investigating chemical reactions with VASP - A practical guide'' by Tomáš Bučko - a book guiding modeling chemical reactions in VASP {{Cite\|bucko:book:2025}}.
	*Lecture on modeling chemical reactions (and transition states) using ~~[https~~:~~//youtu.be/mLK7CtDmw0A~~ static approaches].		*Lecture on modeling chemical reactions (and transition states) using {{Video\|static:tomas:2025\|static approaches}}.
	*Lecture on modeling chemical reactions (and transition states) using ~~[https~~:~~//youtu.be/Rk0S-yvxFUo~~ dynamic approaches].		*Lecture on modeling chemical reactions (and transition states) using {{Video\|dynamic:tomas:2025\|dynamic approaches}}.
	*Lecture on modeling chemical reactions (and transition states) using ~~[https~~:~~//youtu.be/bzzHpTBwxbA)~~ machine-learned force fields].		*Lecture on modeling chemical reactions (and transition states) using {{Video\|chem_mlff:ferenc:2025\|machine-learned force fields}}.

	=== Tutorials ===		=== Tutorials ===
	*Tutorial for ~~[https~~:~~//vasp.at/tutorials/latest/transition_states/~~part1/ NEB, IDM, elbow plot, and IRC calculations].		*Tutorial for {{Tutorial\|transition_states:part1\|NEB, IDM, elbow plot, and IRC calculations}}.
	*Tutorial for modeling reaction pathways and calculating free energies of reaction using ~~[https~~:~~//vasp.at/tutorials/latest/transition_states/~~part2/ static methods].		*Tutorial for modeling reaction pathways and calculating free energies of reaction using {{Tutorial\|transition_states:part2\|static methods}}.
	*Tutorial for modeling reaction pathways and calculating free energies of reaction using ~~[https~~:~~//vasp.at/tutorials/latest/transition_states/~~part3/ dynamic methods].		*Tutorial for modeling reaction pathways and calculating free energies of reaction using {{Tutorial\|transition_states:part3\|dynamic methods}}.
	*Tutorial for ~~[https~~:~~//www.vasp.at/tutorials/latest/md/~~part3~~/#MD-e08~~ dynamic methods for chloromethane-chloride inversion].		*Tutorial for {{Tutorial\|md:part3\|dynamic methods for chloromethane-chloride inversion}}.
	<!--=== How to ===		<!--=== How to ===
	*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->		*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->

Csheldon: /* Additional resources */

2026-02-10T13:04:28Z

Additional resources

← Older revision		Revision as of 13:04, 10 February 2026
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	*Tutorial for modeling reaction pathways and calculating free energies of reaction using [https://vasp.at/tutorials/latest/transition_states/part3/ dynamic methods].		*Tutorial for modeling reaction pathways and calculating free energies of reaction using [https://vasp.at/tutorials/latest/transition_states/part3/ dynamic methods].
	*Tutorial for [https://www.vasp.at/tutorials/latest/md/part3/#MD-e08 dynamic methods for chloromethane-chloride inversion].		*Tutorial for [https://www.vasp.at/tutorials/latest/md/part3/#MD-e08 dynamic methods for chloromethane-chloride inversion].
	<!--=== How to's ===		<!--=== How to ===
	*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->		*How to for [[Using_metadynamics_to_train_a_machine-learned_force_field \| training a machine-learned force field (MLFF) using metadynamics for chloromethane-chloride inversion]].-->