Enhancing hydrogen positions in X-ray structures of transition metal hydride complexes with dynamic quantum crystallography.
Magdalena WoinskaAnna Agnieszka HoserMichał Leszek ChodkiewiczKrzysztof WoźniakPublished in: IUCrJ (2024)
Hirshfeld atom refinement (HAR) is a method which enables the user to obtain more accurate positions of hydrogen atoms bonded to light chemical elements using X-ray data. When data quality permits, this method can be extended to hydrogen-bonded transition metals (TMs), as in hydride complexes. However, addressing hydrogen thermal motions with HAR, particularly in TM hydrides, presents a challenge. At the same time, proper description of thermal vibrations can be vital for determining hydrogen positions correctly. In this study, we employ tools such as SHADE3 and Normal Mode Refinement (NoMoRe) to estimate anisotropic displacement parameters (ADPs) for hydrogen atoms during HAR and IAM refinements performed for seven structures of TM (Fe, Ni, Cr, Nb, Rh and Os) and metalloid (Sb) hydride complexes for which both the neutron and the X-ray structures have been determined. A direct comparison between neutron and HAR/SHADE3/NoMoRe ADPs reveals that the similarity between neutron hydrogen ADPs and those estimated with NoMoRe or SHADE3 is significantly higher than when hydrogen ADPs are refined with HAR. Regarding TM-H bond lengths, traditional HAR exhibits a slight advantage over the other methods. However, combining NoMoRe/SHADE3 with HAR results in a minor decrease in agreement with neutron TM-H bond lengths. For the Cr complex, for which high-resolution X-ray data were collected, an investigation of resolution-related effects was possible.
Keyphrases
- high resolution
- transition metal
- visible light
- mass spectrometry
- electronic health record
- molecular dynamics
- dual energy
- computed tomography
- magnetic resonance
- climate change
- heavy metals
- high speed
- quality improvement
- data analysis
- deep learning
- high frequency
- transcranial magnetic stimulation
- artificial intelligence