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Free-energy diagrams, or reaction coordinate diagrams, are graphs showing the energy changes that occur during a chemical reaction. The reaction coordinate represented on the horizontal axis shows how far the reaction has progressed structurally. Positions along the x-axis close to the reactants have structures resembling the reactants, while positions close to the products resemble the products.  Peaks on the energy diagram represent stable structures with measurable lifetimes, while...
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UV–Vis Spectroscopy: Molecular Electronic Transitions01:16

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In Ultraviolet–Visible (UV–Vis) spectroscopy, the absorption of electromagnetic radiation is used to probe the electronic structure of molecules. This technique provides insights into molecular electronic transitions, particularly the movement of electrons between different molecular orbitals. Radiation is absorbed if the energy of the electromagnetic radiation passing through the molecule is precisely equal to the energy difference between the excited and ground states. During this...
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The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
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¹H NMR: Interpreting Distorted and Overlapping Signals01:02

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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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Fermi Level Dynamics01:12

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The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
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Energy Bands in Solids01:01

Energy Bands in Solids

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Isolated atoms have discrete energy levels that are well described by the Bohr model. And, it quantifies the energy of an electron in a hydrogen atom as En. Higher quantum numbers 'n' yield less negative, closer electron energy levels.
 Band Formation:
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Related Experiment Video

Updated: Jun 13, 2025

Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research
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Author Spotlight: Exploring Light-Driven Chemical Reactions and Energy-Harnessing Devices in Photochemical Research

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Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles.

Jakub Rydzewski1

  • 1Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziadzka 5, 87-100 Toruń, Poland.

Journal of Chemical Theory and Computation
|September 12, 2024
PubMed
Summary
This summary is machine-generated.

Spectral mapping identifies key slow variables in complex molecular systems. This technique simplifies protein folding dynamics, revealing a single variable that captures essential folding characteristics.

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Study of Protein Dynamics via Neutron Spin Echo Spectroscopy
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Area of Science:

  • Physical chemistry
  • Computational chemistry
  • Statistical mechanics

Background:

  • Complex molecular systems exhibit long-time dynamics crucial for their characteristics.
  • Simplifying dynamics involves identifying slow collective variables (CVs) and treating fast variables as noise.
  • This reduction allows modeling dynamics as diffusion on a free-energy landscape, approximating Markovian behavior.

Purpose of the Study:

  • Advance the spectral map technique for learning slow CVs.
  • Apply the enhanced framework to a high-dimensional protein folding process.
  • Demonstrate the utility of learned CVs for understanding molecular dynamics and protein folding.

Main Methods:

  • Utilized spectral map, a statistical learning technique maximizing spectral gaps of transition matrices.
  • Implemented Markov transition matrix coarse-graining to partition the CV space kinetically.
  • Defined transition state ensembles based on the partitioned CV space.

Main Results:

  • Learned slow CVs closely approximate the Markovian limit for overdamped diffusion.
  • Coordinate-dependent diffusion coefficients showed minimal impact on free-energy landscapes.
  • Spectral maps effectively quantified feature importance and compared learned CVs with traditional structural descriptors.

Conclusions:

  • A single slow CV identified by spectral map can serve as a physical reaction coordinate.
  • The technique accurately captures essential characteristics of protein folding dynamics.
  • Spectral map offers a powerful tool for analyzing complex molecular systems.