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Pjotrs Žguns
Observed names:
P. Žguns,
Pjotrs A. Žguns,
Pjotrs Zguns,
Pjotrs, Žguns,
Zguns, Pjotrs,
Žguns, Pjotrs
show all 6
Institutions:
Institute of Solid State Physics, UL,
Massachusetts Institute of Technology,
Auburn University,
University of Latvia
Observed institutions:
Uppsala University,
Institute of Solid State Physics, UL,
Massachusetts Institute of Technology,
Auburn University,
KTH Royal Institute of Technology,
University of Latvia
show all 6
ORCID:
0000-0002-3387-2919
Observed ORCID:
0000-0002-3387-2919
OpenAlex ID:
A5083164222
Uncovering fast solid-acid proton conductors based on dynamics of polyanion groups and proton bonding strength
2024
·
Pjotrs Žguns
, Konstantin Klyukin
, et al.
·
Energy & Environmental Science
·
31
PDF
Phase diagram and oxygen–vacancy ordering in the CeO 2 –Gd 2 O 3 system: a theoretical study
2018
·
Pjotrs A. Žguns
, Andrei V. Ruban
, et al.
·
Physical Chemistry Chemical Physics
·
31
Ordering and phase separation in Gd-doped ceria: a combined DFT, cluster expansion and Monte Carlo study
2017
·
Pjotrs A. Žguns
, Andrei V. Ruban
, et al.
·
Physical Chemistry Chemical Physics
·
25
Computational Insights into Electrolyte-Dependent Li-Ion Charge-Transfer Kinetics at the Li x CoO 2 Interface
2024
·
Joakim Halldin Stenlid
, Pjotrs Žguns
, et al.
·
ACS Energy Letters
·
22
Interpretation of unexpected behavior of infrared absorption spectra of ScF3 beyond the quasiharmonic approximation
2016
·
Sergei Piskunov
, Pjotrs A. Žguns
, et al.
·
Physical review. B./Physical review. B
·
21
Strain Sensitivity of Li -ion Conductivity inβ- Li3PS4 Solid Electrolyte
2022
·
Pjotrs Žguns
, Bilge Yildiz
·
PRX Energy
·
17
PDF
Benchmarking CHGNet Universal Machine Learning Interatomic Potential against DFT and EXAFS: The Case of Layered WS2 and MoS2
2025
·
Pjotrs Žguns
, Inga Pudza
, et al.
·
Journal of Chemical Theory and Computation
·
13
PDF
Electronic structure of cubic ScF3 from first-principles calculations
2016
·
D. Bocharov
, P. Žguns
, et al.
·
Low Temperature Physics
·
13
PDF
Electrochemical Ionic Synapses with Mg2+ as the Working Ion
2024
·
Miranda Schwacke
, Pjotrs Žguns
, et al.
·
Advanced Electronic Materials
·
10
PDF
Flexibility of oxygen sublattice and hydrogen bond length predict proton mobility in ternary metal oxides
2025
·
Heejung W. Chung
, Pjotrs Žguns
, et al.
·
Matter
·
9
PDF
Influence of composition and oxygen-vacancy ordering on lattice parameter and elastic moduli of Ce1-Gd O2-/2: A theoretical study
2018
·
Pjotrs A. Žguns
, Andrei V. Ruban
, et al.
·
Scripta Materialia
·
8
Modeling Kinetics of Water Adsorption on the Rutile TiO 2 (110) Surface: Influence of Exchange‐Correlation Functional
2017
·
Johan O. Nilsson
, Mikael Leetmaa
, et al.
·
physica status solidi (b)
·
7
Cu adatom charging on Mo supported ScN, MgO and NaF
2015
·
Pjotrs A. Žguns
, Michael Wessel
, et al.
·
RSC Advances
·
4
PDF
Hydrogen in brownmillerite perovskites: First-principles insights into energetics and induced electronic-magnetic changes
2026
·
Vladislav Korostelev
, Pjotrs Žguns
, et al.
·
Physical Review Materials
·
2
PDF
Effect of protons on polaron mobility in transition metal oxides
2026
·
Pjotrs Žguns
, Bilge Yildiz
·
Physical Review Materials
·
2
Polaron and strain effects on ion migration in W O 3
2026
·
Matthäus Siebenhofer
, Pjotrs Žguns
, et al.
·
Physical Review Materials
·
1
PDF
The CHGNet uMLIP model fine-tuned for 2Hc-WS2
2026
·
Žguns, Pjotrs
·
Zenodo (CERN European Organization for Nuclear Research)
·
1
DFT and machine-learning datasets for main figures in “Hydrogen in Brownmillerite Perovskites: First-Principles Insights into Energetics and Induced Electronic–Magnetic Changes”
2026
·
Korostelev, Vladislav
, Klyukin, Konstantin
, et al.
·
Figshare
·
1
Superconductivity and Pronounced Electron‐Phonon Coupling in Rock‐Salt Al1−xO1−x and Ti1−xO1−x
2024
·
Pjotrs Žguns
, Nuh Gedik
, et al.
·
Advanced Electronic Materials
·
1
Modeling Kinetics of Water Adsorption on the Rutile TiO2 (110) Surface: Influence of Exchange‐Correlation Functional (Phys. Status Solidi B 3/2018)
2018
·
Johan O. Nilsson
, Mikael Leetmaa
, et al.
·
physica status solidi (b)
·
1
PDF
Can Universal Machine-Learning Interatomic Potentials Capture Small Polarons? A Geometry-Based Benchmark in Transition-Metal Oxides
2026
·
Korostelev, Vladislav
, Žguns, Pjotrs
, et al.
·
arXiv (Cornell University)
PDF
Synthesis and characterization of Re-doped VO2 thin films
2026
·
Boris Polyakov
, Tamara Tsebriienko
, et al.
·
Journal of Alloys and Compounds
Optimized uMLIP model for copper molybdate
2026
·
Žguns, Pjotrs
·
Zenodo (CERN European Organization for Nuclear Research)
Local lattice dynamics of hcp zinc from EXAFS and machine-learning interatomic potentials
2026
·
Vitalijs Dimitrijevs
, Pjotrs Žguns
, et al.
·
Physica B Condensed Matter
PDF
EXAFS Thermometry via Digital Twins from Machine Learning Interatomic Potentials
2026
·
Alexei, Kuzmin
, Pjotrs, Žguns
·
Zenodo (CERN European Organization for Nuclear Research)
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Works count:
39
Citation count:
220
H-index:
9
I10-index:
9
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