Dr. Christoph Scheurer
Theory Department
Fields of Application
Batteries, Data Science / Machine Learning, Electrolysers, Hydrogen, Nanomaterials, Solar Fuels
Publications
23.
M Kouyate, G Ducci, F Felsen, C Kunkel, K Reuter, C Scheurer
Model driven adaptive design with concentration profiles Journal Article
In: Journal of Chemical Physics, vol. 163, no. 22, 2025, ISSN: 0021-9606.
@article{nokey,
title = {Model driven adaptive design with concentration profiles},
author = {M Kouyate and G Ducci and F Felsen and C Kunkel and K Reuter and C Scheurer},
url = {\<Go to ISI\>://WOS:001634651500001},
doi = {10.1063/5.0289751},
issn = {0021-9606},
year = {2025},
date = {2025-12-14},
journal = {Journal of Chemical Physics},
volume = {163},
number = {22},
abstract = {Effective kinetic models of heterogeneous catalytic processes are an indispensable tool for reactor design, optimization, and control. Under the assumption of using functional forms like power laws, model parameters are traditionally fitted to kinetic data measured along local line scans. A local line scan involves systematically varying one individual reaction parameter, such as a reactant concentration or temperature, at a time. This approach typically involves numerous separate kinetic measurements and is susceptible to the uncertainty of these line scans in determining the model's parameters. Here, we explore the use of profile reactors in combination with a fully automated adaptive design approach for an efficient identification of effective kinetic models. Originally developed to provide operando information along the axis of tubular reactors, profile reactors provide a complex line scan that encapsulates kinetic information across all reaction conditions probed along the tube. The proposed Model-Driven Adaptive Design with Profiles algorithm harnesses this extensive dataset to strategically guide the selection of initial reaction conditions for subsequent profile reactor measurements. This approach ensures that each line scan provides maximally complementary information, thereby significantly enhancing the efficiency and accuracy of kinetic model identification.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Effective kinetic models of heterogeneous catalytic processes are an indispensable tool for reactor design, optimization, and control. Under the assumption of using functional forms like power laws, model parameters are traditionally fitted to kinetic data measured along local line scans. A local line scan involves systematically varying one individual reaction parameter, such as a reactant concentration or temperature, at a time. This approach typically involves numerous separate kinetic measurements and is susceptible to the uncertainty of these line scans in determining the model's parameters. Here, we explore the use of profile reactors in combination with a fully automated adaptive design approach for an efficient identification of effective kinetic models. Originally developed to provide operando information along the axis of tubular reactors, profile reactors provide a complex line scan that encapsulates kinetic information across all reaction conditions probed along the tube. The proposed Model-Driven Adaptive Design with Profiles algorithm harnesses this extensive dataset to strategically guide the selection of initial reaction conditions for subsequent profile reactor measurements. This approach ensures that each line scan provides maximally complementary information, thereby significantly enhancing the efficiency and accuracy of kinetic model identification.
22.
L Sandoval-Diaz, T Götsch, D Cruz, M Vuijk, J M Lombardi, M Pietsch, K Dembélé, A Hammud, K Reuter, C Scheurer, A Knop-Gericke, T Lunkenbein
Stabilizing Frustrated Phase Transitions in Selective Oxidation Reactions Journal Article
In: Advanced Materials, 2025, ISSN: 0935-9648.
@article{nokey,
title = {Stabilizing Frustrated Phase Transitions in Selective Oxidation Reactions},
author = {L Sandoval-Diaz and T G\"{o}tsch and D Cruz and M Vuijk and J M Lombardi and M Pietsch and K Demb\'{e}l\'{e} and A Hammud and K Reuter and C Scheurer and A Knop-Gericke and T Lunkenbein},
url = {\<Go to ISI\>://WOS:001621057100001},
doi = {10.1002/adma.202515292},
issn = {0935-9648},
year = {2025},
date = {2025-11-28},
journal = {Advanced Materials},
abstract = {Frustrated phase transitions represent the ideal working state of a heterogeneous catalyst. These states exist within a narrow parameter window, making them difficult to stabilize. Here, it is shown for the selective oxidation of 2-propanol to acetone over Co3O4 spinels that the addition of water extends the stability regime of the relevant frustrated phase transition. This conclusion is based on results obtained from multi-modal experiments, including operando scanning electron microscopy (OSEM), near ambient pressure X-ray photoelectron spectroscopy (NAP-XPS), transmission electron microscopy (TEM), and computer vision analysis. It is found that the most selective state for acetone formation coincides with a dynamic spinel structure that fluctuates through reversible redox processes. At elevated temperatures, this metastable state undergoes a complete phase transition into the rock-salt CoO phase characterized by low acetone selectivity. This process is found to be mediated by the generation of mobile vacancies. The addition of water vapor mitigates vacancy mobility and stabilizes the selective, but thermodynamically frustrated, state. As such, the study conceptualizes a strategy to extend the lifetime of a catalyst during reaction by the adequate addition of a co-reactant.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Frustrated phase transitions represent the ideal working state of a heterogeneous catalyst. These states exist within a narrow parameter window, making them difficult to stabilize. Here, it is shown for the selective oxidation of 2-propanol to acetone over Co3O4 spinels that the addition of water extends the stability regime of the relevant frustrated phase transition. This conclusion is based on results obtained from multi-modal experiments, including operando scanning electron microscopy (OSEM), near ambient pressure X-ray photoelectron spectroscopy (NAP-XPS), transmission electron microscopy (TEM), and computer vision analysis. It is found that the most selective state for acetone formation coincides with a dynamic spinel structure that fluctuates through reversible redox processes. At elevated temperatures, this metastable state undergoes a complete phase transition into the rock-salt CoO phase characterized by low acetone selectivity. This process is found to be mediated by the generation of mobile vacancies. The addition of water vapor mitigates vacancy mobility and stabilizes the selective, but thermodynamically frustrated, state. As such, the study conceptualizes a strategy to extend the lifetime of a catalyst during reaction by the adequate addition of a co-reactant.
21.
A F Harper, S S Köcher, K Reuter, C Scheurer
Performance metrics for tensorial learning: prediction of Li4Ti5O12 nuclear magnetic resonance observables at experimental accuracy Journal Article
In: Journal of Materials Chemistry A, vol. 13, no. 41, pp. 35389-35399, 2025, ISSN: 2050-7488.
@article{nokey,
title = {Performance metrics for tensorial learning: prediction of Li4Ti5O12 nuclear magnetic resonance observables at experimental accuracy},
author = {A F Harper and S S K\"{o}cher and K Reuter and C Scheurer},
url = {\<Go to ISI\>://WOS:001582683500001},
doi = {10.1039/d5ta05090a},
issn = {2050-7488},
year = {2025},
date = {2025-10-21},
journal = {Journal of Materials Chemistry A},
volume = {13},
number = {41},
pages = {35389-35399},
abstract = {Predicting observable quantities from first principles calculations is the next frontier within the field of machine learning (ML) for materials modelling. While ML models have shown success for the prediction of scalar properties such as energetics or band gaps, models and performance metrics for the learning of higher order tensor-based observables have not yet been formalized. ML models for experimental observables, including tensorial quantities, are essential for exploiting the full potential of the paradigm shift enabled by machine learned interatomic potentials by mapping the structure-property relationship in an equally efficient way. In this work, we establish performance metrics for accurately predicting the electric field gradient tensor (EFG) underlying nuclear magnetic resonance (NMR) spectroscopy. We further demonstrate the superiority of a tensorial learning approach that fully encodes the corresponding symmetries over a separate scalar learning of individual tensor-derived observables. To this end we establish an extensive EFG dataset representative of real experimental applications and develop performance metrics for model evaluation which directly focus on the targeted NMR observables. Finally, by leveraging the computational efficiency of the ML method employed, we predict quadrupolar observables for 1512 atom models of Li4Ti5O12, a high performance Li-ion battery anode material, which is capable of accurately distinguishing local atomic environments via their NMR observables. This workflow and dataset sets the standard for the next generation of tensorial based learning for spectroscopic observables.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Predicting observable quantities from first principles calculations is the next frontier within the field of machine learning (ML) for materials modelling. While ML models have shown success for the prediction of scalar properties such as energetics or band gaps, models and performance metrics for the learning of higher order tensor-based observables have not yet been formalized. ML models for experimental observables, including tensorial quantities, are essential for exploiting the full potential of the paradigm shift enabled by machine learned interatomic potentials by mapping the structure-property relationship in an equally efficient way. In this work, we establish performance metrics for accurately predicting the electric field gradient tensor (EFG) underlying nuclear magnetic resonance (NMR) spectroscopy. We further demonstrate the superiority of a tensorial learning approach that fully encodes the corresponding symmetries over a separate scalar learning of individual tensor-derived observables. To this end we establish an extensive EFG dataset representative of real experimental applications and develop performance metrics for model evaluation which directly focus on the targeted NMR observables. Finally, by leveraging the computational efficiency of the ML method employed, we predict quadrupolar observables for 1512 atom models of Li4Ti5O12, a high performance Li-ion battery anode material, which is capable of accurately distinguishing local atomic environments via their NMR observables. This workflow and dataset sets the standard for the next generation of tensorial based learning for spectroscopic observables.
20.
A F Harper, T Huss, S S Köcher, C Scheurer
Tracking Li atoms in real-time with ultra-fast NMR simulations Journal Article
In: Faraday Discussions, vol. 255, no. 0, pp. 411-428, 2025, ISSN: 1359-6640.
@article{nokey,
title = {Tracking Li atoms in real-time with ultra-fast NMR simulations},
author = {A F Harper and T Huss and S S K\"{o}cher and C Scheurer},
url = {http://dx.doi.org/10.1039/D4FD00074A},
doi = {10.1039/D4FD00074A},
issn = {1359-6640},
year = {2025},
date = {2025-01-01},
journal = {Faraday Discussions},
volume = {255},
number = {0},
pages = {411-428},
abstract = {We present for the first time a multiscale machine learning approach to jointly simulate atomic structure and dynamics with the corresponding solid state Nuclear Magnetic Resonance (ssNMR) observables. We study the use-case of spin-alignment echo (SAE) NMR for exploring Li-ion diffusion within the solid state electrolyte material Li3PS4 (LPS) by calculating quadrupolar frequencies of 7Li. SAE NMR probes long-range dynamics down to microsecond-timescale hopping processes. Therefore only a few machine learning force field schemes are able to capture the time- and length scales required for accurate comparison with experimental results. By using a new class of machine learning interatomic potentials, known as ultra-fast potentials (UFPs), we are able to efficiently access timescales beyond the microsecond regime. In tandem, we have developed a machine learning model for predicting the full 7Li electric field gradient (EFG) tensors in LPS. By combining the long timescale trajectories from the UFP with our model for 7Li EFG tensors, we are able to extract the autocorrelation function (ACF) for 7Li quadrupolar frequencies during Li diffusion. We extract the decay constants from the ACF for both crystalline β-LPS and amorphous LPS, and find that the predicted Li hopping rates are on the same order of magnitude as those predicted from the Li dynamics. This demonstrates the potential for machine learning to finally make predictions on experimentally relevant timescales and temperatures, and opens a new avenue of NMR crystallography: using machine learning dynamical NMR simulations for accessing polycrystalline and glass ceramic materials.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present for the first time a multiscale machine learning approach to jointly simulate atomic structure and dynamics with the corresponding solid state Nuclear Magnetic Resonance (ssNMR) observables. We study the use-case of spin-alignment echo (SAE) NMR for exploring Li-ion diffusion within the solid state electrolyte material Li3PS4 (LPS) by calculating quadrupolar frequencies of 7Li. SAE NMR probes long-range dynamics down to microsecond-timescale hopping processes. Therefore only a few machine learning force field schemes are able to capture the time- and length scales required for accurate comparison with experimental results. By using a new class of machine learning interatomic potentials, known as ultra-fast potentials (UFPs), we are able to efficiently access timescales beyond the microsecond regime. In tandem, we have developed a machine learning model for predicting the full 7Li electric field gradient (EFG) tensors in LPS. By combining the long timescale trajectories from the UFP with our model for 7Li EFG tensors, we are able to extract the autocorrelation function (ACF) for 7Li quadrupolar frequencies during Li diffusion. We extract the decay constants from the ACF for both crystalline β-LPS and amorphous LPS, and find that the predicted Li hopping rates are on the same order of magnitude as those predicted from the Li dynamics. This demonstrates the potential for machine learning to finally make predictions on experimentally relevant timescales and temperatures, and opens a new avenue of NMR crystallography: using machine learning dynamical NMR simulations for accessing polycrystalline and glass ceramic materials.
19.
C Scheurer, K Reuter
Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis Journal Article
In: Nature Catalysis, vol. 8, no. 1, pp. 13-19, 2025, ISSN: 2520-1158.
@article{nokey,
title = {Role of the human-in-the-loop in emerging self-driving laboratories for heterogeneous catalysis},
author = {C Scheurer and K Reuter},
url = {https://doi.org/10.1038/s41929-024-01275-5},
doi = {10.1038/s41929-024-01275-5},
issn = {2520-1158},
year = {2025},
date = {2025-01-01},
journal = {Nature Catalysis},
volume = {8},
number = {1},
pages = {13-19},
abstract = {Self-driving laboratories (SDLs) represent a cutting-edge convergence of machine learning with laboratory automation. SDLs operate in active learning loops, in which a machine learning algorithm plans experiments that are subsequently executed by increasingly automated (robotic) modules. Here we present our view on emerging SDLs for accelerated discovery and process optimization in heterogeneous catalysis. We argue against the paradigm of full automation and the goal of keeping the human out of the loop. Based on analysis of the involved workflows, we instead conclude that crucial advances will come from establishing fast proxy experiments and re-engineering existing apparatuses and measurement protocols. Industrially relevant use cases will also require humans to be kept in the loop for continuous decision-making. In turn, active learning algorithms will have to be advanced that can flexibly deal with corresponding adaptations of the design space and varying information content and noise in the acquired data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Self-driving laboratories (SDLs) represent a cutting-edge convergence of machine learning with laboratory automation. SDLs operate in active learning loops, in which a machine learning algorithm plans experiments that are subsequently executed by increasingly automated (robotic) modules. Here we present our view on emerging SDLs for accelerated discovery and process optimization in heterogeneous catalysis. We argue against the paradigm of full automation and the goal of keeping the human out of the loop. Based on analysis of the involved workflows, we instead conclude that crucial advances will come from establishing fast proxy experiments and re-engineering existing apparatuses and measurement protocols. Industrially relevant use cases will also require humans to be kept in the loop for continuous decision-making. In turn, active learning algorithms will have to be advanced that can flexibly deal with corresponding adaptations of the design space and varying information content and noise in the acquired data.
18.
H Türk, X Q Tran, P König, A Hammud, V Vibhu, F-P Schmidt, D Berger, S Selve, V Roddatis, D Abou-Ras, F Girgsdies, Y-T Chan, T Götsch, H Ali, I C Vinke, L G J De Haart, M Lehmann, A Knop-Gericke, K Reuter, R-A Eichel, C Scheurer, T Lunkenbein
Boon and Bane of Local Solid State Chemistry on the Performance of LSM-Based Solid Oxide Electrolysis Cells Journal Article
In: Advanced Energy Materials, vol. n/a, no. n/a, pp. 2405599, 2024, ISSN: 1614-6832.
@article{nokey,
title = {Boon and Bane of Local Solid State Chemistry on the Performance of LSM-Based Solid Oxide Electrolysis Cells},
author = {H T\"{u}rk and X Q Tran and P K\"{o}nig and A Hammud and V Vibhu and F-P Schmidt and D Berger and S Selve and V Roddatis and D Abou-Ras and F Girgsdies and Y-T Chan and T G\"{o}tsch and H Ali and I C Vinke and L G J De Haart and M Lehmann and A Knop-Gericke and K Reuter and R-A Eichel and C Scheurer and T Lunkenbein},
url = {https://doi.org/10.1002/aenm.202405599},
doi = {https://doi.org/10.1002/aenm.202405599},
issn = {1614-6832},
year = {2024},
date = {2024-12-31},
urldate = {2024-12-31},
journal = {Advanced Energy Materials},
volume = {n/a},
number = {n/a},
pages = {2405599},
abstract = {Abstract High-temperature solid oxide cells are highly efficient energy converters. However, their lifetime is limited by rapid deactivation. Little is known about the local, atomic scale transformation that drive this degradation. Here, reaction-induced changes are unraveled at the atomic scale of a solid oxide electrolysis cell (SOEC) operated for 550 h by combining high-resolution scanning transmission electron microscopy with first-principles and force-field-based atomistic simulations. We focus on the structural evolution of lanthanum strontium manganite (LSM)/yttria-stabilized zirconia (YSZ) regions and the corresponding solid?solid interface. It is found that the strong inter-diffusion of cations leads to the additional formation and growth of a multitude of localized structures such as a solid solution of La/Mn, nano-domains of secondary structures or antisite defects in the YSZ, as well as a mixed ion and electron conduction region in the LSM and complexion. These local structures can be likewise beneficial or detrimental to the performance, by either increasing the catalytically active area or by limiting the supply of reactants. The work provides unprecedented atomistic insights into the influence of local solid-state chemistry on the functioning of SOECs and deepens the understanding of the degradation mechanism in SOECs, paving the way towards nanoscopic rational interface design for more efficient and durable cells.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract High-temperature solid oxide cells are highly efficient energy converters. However, their lifetime is limited by rapid deactivation. Little is known about the local, atomic scale transformation that drive this degradation. Here, reaction-induced changes are unraveled at the atomic scale of a solid oxide electrolysis cell (SOEC) operated for 550 h by combining high-resolution scanning transmission electron microscopy with first-principles and force-field-based atomistic simulations. We focus on the structural evolution of lanthanum strontium manganite (LSM)/yttria-stabilized zirconia (YSZ) regions and the corresponding solid?solid interface. It is found that the strong inter-diffusion of cations leads to the additional formation and growth of a multitude of localized structures such as a solid solution of La/Mn, nano-domains of secondary structures or antisite defects in the YSZ, as well as a mixed ion and electron conduction region in the LSM and complexion. These local structures can be likewise beneficial or detrimental to the performance, by either increasing the catalytically active area or by limiting the supply of reactants. The work provides unprecedented atomistic insights into the influence of local solid-state chemistry on the functioning of SOECs and deepens the understanding of the degradation mechanism in SOECs, paving the way towards nanoscopic rational interface design for more efficient and durable cells.
17.
Y Wang, Y-T Chan, T Oshima, V Duppel, S Bette, K Küster, A Gouder, C Scheurer, B V Lotsch
Decoupling of Light and Dark Reactions in a 2D Niobium Tungstate for Light-Induced Charge Storage and On-Demand Hydrogen Evolution Journal Article
In: Journal of the American Chemical Society, vol. 146, no. 37, pp. 25467-25476, 2024, ISSN: 0002-7863.
@article{nokey,
title = {Decoupling of Light and Dark Reactions in a 2D Niobium Tungstate for Light-Induced Charge Storage and On-Demand Hydrogen Evolution},
author = {Y Wang and Y-T Chan and T Oshima and V Duppel and S Bette and K K\"{u}ster and A Gouder and C Scheurer and B V Lotsch},
url = {https://doi.org/10.1021/jacs.4c04140},
doi = {10.1021/jacs.4c04140},
issn = {0002-7863},
year = {2024},
date = {2024-09-18},
journal = {Journal of the American Chemical Society},
volume = {146},
number = {37},
pages = {25467-25476},
abstract = {The direct coupling of light harvesting and charge storage in a single material opens new avenues to light storing devices. Here we demonstrate the decoupling of light and dark reactions in the two-dimensional layered niobium tungstate (TBA)+(NbWO6)− for on-demand hydrogen evolution and solar battery energy storage. Light illumination drives Li+/H+ photointercalation into the (TBA)+(NbWO6)− photoanode, leading to small polaron formation assisted by structural distortions on the WOx sublattice, along with a light-induced decrease in material resistance over 2 orders of magnitude compared to the dark. The photogenerated electrons can be extracted on demand to produce solar hydrogen upon the addition of a Pt catalyst. Alternatively, they can be stored for over 20 h under oxygen-free conditions after 365 nm UV illumination for only 10 min, thus featuring a solar battery anode with promising capacity and long-term stability. The optoionic effects described herein offer new insights to overcome the intermittency of solar irradiation, while inspiring applications at the interface of solar energy conversion and energy storage, including solar batteries, “dark” photocatalysis, solar battolyzers, and photomemory devices.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The direct coupling of light harvesting and charge storage in a single material opens new avenues to light storing devices. Here we demonstrate the decoupling of light and dark reactions in the two-dimensional layered niobium tungstate (TBA)+(NbWO6)− for on-demand hydrogen evolution and solar battery energy storage. Light illumination drives Li+/H+ photointercalation into the (TBA)+(NbWO6)− photoanode, leading to small polaron formation assisted by structural distortions on the WOx sublattice, along with a light-induced decrease in material resistance over 2 orders of magnitude compared to the dark. The photogenerated electrons can be extracted on demand to produce solar hydrogen upon the addition of a Pt catalyst. Alternatively, they can be stored for over 20 h under oxygen-free conditions after 365 nm UV illumination for only 10 min, thus featuring a solar battery anode with promising capacity and long-term stability. The optoionic effects described herein offer new insights to overcome the intermittency of solar irradiation, while inspiring applications at the interface of solar energy conversion and energy storage, including solar batteries, “dark” photocatalysis, solar battolyzers, and photomemory devices.
16.
L Masliuk, K Nam, M W Terban, Y Lee, P Kube, D Delgado, F Girgsdies, K Reuter, R Schlögl, A Trunschke, C Scheurer, M Zobel, T Lunkenbein
Linking Bulk and Surface Structures in Complex Mixed Oxides Journal Article
In: ACS Catalysis, vol. 14, no. 11, pp. 9018-9033, 2024.
@article{nokey,
title = {Linking Bulk and Surface Structures in Complex Mixed Oxides},
author = {L Masliuk and K Nam and M W Terban and Y Lee and P Kube and D Delgado and F Girgsdies and K Reuter and R Schl\"{o}gl and A Trunschke and C Scheurer and M Zobel and T Lunkenbein},
url = {https://doi.org/10.1021/acscatal.3c05230},
doi = {10.1021/acscatal.3c05230},
year = {2024},
date = {2024-06-07},
journal = {ACS Catalysis},
volume = {14},
number = {11},
pages = {9018-9033},
abstract = {The interface between a solid catalyst and the reacting medium plays a crucial role in the function of the material in catalysis. In the present work, we show that the surface termination of isostructural molybdenum\textendashvanadium oxides is strongly linked to the real structure of the bulk. This conclusion is based on comparing (scanning) transmission electron microscopy images with pair distribution function (PDF) data obtained for (Mo,V)Ox and (Mo,V,Te,Nb)Ox. Distance-dependent analyses of the PDF results demonstrate that (Mo,V,Te,Nb)Ox exhibits stronger deviations from the averaged orthorhombic crystal structure than (Mo,V)Ox in the short and intermediate regimes. These deviations are explained by higher structural diversity, which is facilitated by the increased chemical complexity of the quinary oxide and in particular by the presence of Nb. This structural diversity is seemingly important to form intrinsic bulk-like surface terminations that are highly selective in alkane oxidation. More rigid (Mo,V)Ox is characterized by defective surfaces that are more active but less selective for the same reactions. In line with machine learning interatomic potential (MLIP) calculations, we highlight that the surface termination of (Mo,V,Te,Nb)Ox is characterized by a reconfiguration of the pentagonal building blocks, causing a preferential exposure of Nb sites. The presented results foster hypotheses that chemical complexity is superior for the performance of multifunctional catalysts. The underlying principle is not the presence of multiple chemically different surface centers but instead the ability of structural diversity to optimally align and distribute the elements at the surface and, thus, to shape the structural environment around the active sites. This study experimentally evidences the origin of the structure-directing impact of the real structure of the bulk on functional interfaces and encourages the development of efficient surface engineering strategies toward improved high-performance selective oxidation catalysts.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The interface between a solid catalyst and the reacting medium plays a crucial role in the function of the material in catalysis. In the present work, we show that the surface termination of isostructural molybdenum–vanadium oxides is strongly linked to the real structure of the bulk. This conclusion is based on comparing (scanning) transmission electron microscopy images with pair distribution function (PDF) data obtained for (Mo,V)Ox and (Mo,V,Te,Nb)Ox. Distance-dependent analyses of the PDF results demonstrate that (Mo,V,Te,Nb)Ox exhibits stronger deviations from the averaged orthorhombic crystal structure than (Mo,V)Ox in the short and intermediate regimes. These deviations are explained by higher structural diversity, which is facilitated by the increased chemical complexity of the quinary oxide and in particular by the presence of Nb. This structural diversity is seemingly important to form intrinsic bulk-like surface terminations that are highly selective in alkane oxidation. More rigid (Mo,V)Ox is characterized by defective surfaces that are more active but less selective for the same reactions. In line with machine learning interatomic potential (MLIP) calculations, we highlight that the surface termination of (Mo,V,Te,Nb)Ox is characterized by a reconfiguration of the pentagonal building blocks, causing a preferential exposure of Nb sites. The presented results foster hypotheses that chemical complexity is superior for the performance of multifunctional catalysts. The underlying principle is not the presence of multiple chemically different surface centers but instead the ability of structural diversity to optimally align and distribute the elements at the surface and, thus, to shape the structural environment around the active sites. This study experimentally evidences the origin of the structure-directing impact of the real structure of the bulk on functional interfaces and encourages the development of efficient surface engineering strategies toward improved high-performance selective oxidation catalysts.
15.
J Valenzuela Reina, F Civaia, A F Harper, C Scheurer, S S Köcher
The EFG Rosetta Stone: translating between DFT calculations and solid state NMR experiments Journal Article
In: Faraday Discussions, 2024, ISSN: 1359-6640.
@article{nokey,
title = {The EFG Rosetta Stone: translating between DFT calculations and solid state NMR experiments},
author = {J Valenzuela Reina and F Civaia and A F Harper and C Scheurer and S S K\"{o}cher},
url = {http://dx.doi.org/10.1039/D4FD00075G},
doi = {10.1039/D4FD00075G},
issn = {1359-6640},
year = {2024},
date = {2024-05-13},
journal = {Faraday Discussions},
abstract = {We present a comprehensive study on the best practices for integrating first principles simulations in experimental quadrupolar solid-state nuclear magnetic resonance (SS-NMR), exploiting the synergies between theory and experiment for achieving the optimal interpretation of both. Most high performance materials (HPMs), such as battery electrodes, exhibit complex SS-NMR spectra due to dynamic effects or amorphous phases. NMR crystallography for such challenging materials requires reliable, accurate, efficient computational methods for calculating NMR observables from first principles for the transfer between theoretical material structure models and the interpretation of their experimental SS-NMR spectra. NMR-active nuclei within HPMs are routinely probed by their chemical shielding anisotropy (CSA). However, several nuclear isotopes of interest, e.g.7Li and 27Al, have a nuclear quadrupole and experience additional interactions with the surrounding electric field gradient (EFG). The quadrupolar interaction is a valuable source of information about atomistic structure, and in particular, local symmetry, complementing the CSA. As such, there is a range of different methods and codes to choose from for calculating EFGs, from all-electron to plane wave methods. We benchmark the accuracy of different simulation strategies for computing the EFG tensor of quadrupolar nuclei with plane wave density functional theory (DFT) and study the impact of the material structure as well as the details of the simulation strategy. Especially for small nuclei with few electrons, such as 7Li, we show that the choice of physical approximations and simulation parameters has a large effect on the transferability of the simulation results. To the best of our knowledge, we present the first comprehensive reference scale and literature survey for 7Li quadrupolar couplings. The results allow us to establish practical guidelines for developing the best simulation strategy for correlating DFT to experimental data extracting the maximum benefit and information from both, thereby advancing further research into HPMs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We present a comprehensive study on the best practices for integrating first principles simulations in experimental quadrupolar solid-state nuclear magnetic resonance (SS-NMR), exploiting the synergies between theory and experiment for achieving the optimal interpretation of both. Most high performance materials (HPMs), such as battery electrodes, exhibit complex SS-NMR spectra due to dynamic effects or amorphous phases. NMR crystallography for such challenging materials requires reliable, accurate, efficient computational methods for calculating NMR observables from first principles for the transfer between theoretical material structure models and the interpretation of their experimental SS-NMR spectra. NMR-active nuclei within HPMs are routinely probed by their chemical shielding anisotropy (CSA). However, several nuclear isotopes of interest, e.g.7Li and 27Al, have a nuclear quadrupole and experience additional interactions with the surrounding electric field gradient (EFG). The quadrupolar interaction is a valuable source of information about atomistic structure, and in particular, local symmetry, complementing the CSA. As such, there is a range of different methods and codes to choose from for calculating EFGs, from all-electron to plane wave methods. We benchmark the accuracy of different simulation strategies for computing the EFG tensor of quadrupolar nuclei with plane wave density functional theory (DFT) and study the impact of the material structure as well as the details of the simulation strategy. Especially for small nuclei with few electrons, such as 7Li, we show that the choice of physical approximations and simulation parameters has a large effect on the transferability of the simulation results. To the best of our knowledge, we present the first comprehensive reference scale and literature survey for 7Li quadrupolar couplings. The results allow us to establish practical guidelines for developing the best simulation strategy for correlating DFT to experimental data extracting the maximum benefit and information from both, thereby advancing further research into HPMs.
14.
L Sandoval-Diaz, D Cruz, M Vuijk, G Ducci, M Hävecker, W Jiang, M Plodinec, A Hammud, D Ivanov, T Götsch, K Reuter, R Schlögl, C Scheurer, A Knop-Gericke, T Lunkenbein
Metastable nickel–oxygen species modulate rate oscillations during dry reforming of methane Journal Article
In: Nature Catalysis, vol. 7, no. 2, pp. 161-171, 2024, ISSN: 2520-1158.
@article{nokey,
title = {Metastable nickel\textendashoxygen species modulate rate oscillations during dry reforming of methane},
author = {L Sandoval-Diaz and D Cruz and M Vuijk and G Ducci and M H\"{a}vecker and W Jiang and M Plodinec and A Hammud and D Ivanov and T G\"{o}tsch and K Reuter and R Schl\"{o}gl and C Scheurer and A Knop-Gericke and T Lunkenbein},
url = {https://doi.org/10.1038/s41929-023-01090-4},
doi = {10.1038/s41929-023-01090-4},
issn = {2520-1158},
year = {2024},
date = {2024-02-01},
journal = {Nature Catalysis},
volume = {7},
number = {2},
pages = {161-171},
abstract = {When a heterogeneous catalyst is active, it forms metastable structures that constantly transform into each other. These structures contribute differently to the catalytic function. Here we show the role of different metastable oxygen species on a Ni catalyst during dry reforming of methane by combining environmental scanning electron microscopy, near ambient pressure X-ray photoelectron spectroscopy, on-line product detection and computer vision. We highlight the critical role of dissociative CO2 adsorption in regulating the oxygen content of the catalyst and in CH4 activation. We also discover rate oscillations during dry reforming of methane resulting from the sequential transformation of metastable oxygen species that exhibit different catalytic properties: atomic surface oxygen, subsurface oxygen and bulk NiOx. The imaging approach allowed the localization of fluctuating surface regions that correlated directly with catalytic activity. The study highlights the importance of metastability and operando analytics in catalysis science and provides impetus towards the design of catalytic systems.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
When a heterogeneous catalyst is active, it forms metastable structures that constantly transform into each other. These structures contribute differently to the catalytic function. Here we show the role of different metastable oxygen species on a Ni catalyst during dry reforming of methane by combining environmental scanning electron microscopy, near ambient pressure X-ray photoelectron spectroscopy, on-line product detection and computer vision. We highlight the critical role of dissociative CO2 adsorption in regulating the oxygen content of the catalyst and in CH4 activation. We also discover rate oscillations during dry reforming of methane resulting from the sequential transformation of metastable oxygen species that exhibit different catalytic properties: atomic surface oxygen, subsurface oxygen and bulk NiOx. The imaging approach allowed the localization of fluctuating surface regions that correlated directly with catalytic activity. The study highlights the importance of metastability and operando analytics in catalysis science and provides impetus towards the design of catalytic systems.
13.
C G Staacke, T Huss, J T Margraf, K Reuter, C Scheurer
Tackling Structural Complexity in Li2S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials Journal Article
In: Nanomaterials, vol. 12, no. 17, 2022, ISSN: 2079-4991.
@article{nokey,
title = {Tackling Structural Complexity in Li2S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials},
author = {C G Staacke and T Huss and J T Margraf and K Reuter and C Scheurer},
doi = {10.3390/nano12172950},
issn = {2079-4991},
year = {2022},
date = {2022-08-26},
urldate = {2022-08-26},
journal = {Nanomaterials},
volume = {12},
number = {17},
abstract = {The lithium thiophosphate (LPS) material class provides promising candidates for solid-state electrolytes (SSEs) in lithium ion batteries due to high lithium ion conductivities, non-critical elements, and low material cost. LPS materials are characterized by complex thiophosphate microchemistry and structural disorder influencing the material performance. To overcome the length and time scale restrictions of ab initio calculations to industrially applicable LPS materials, we develop a near-universal machine-learning interatomic potential for the LPS material class. The trained Gaussian Approximation Potential (GAP) can likewise describe crystal and glassy materials and different P-S connectivities PmSn. We apply the GAP surrogate model to probe lithium ion conductivity and the influence of thiophosphate subunits on the latter. The materials studied are crystals (modifications of Li3PS4 and Li7P3S11), and glasses of the xLi2S\textendash(100 \textendash x)P2S5 type (x = 67, 70 and 75). The obtained material properties are well aligned with experimental findings and we underscore the role of anion dynamics on lithium ion conductivity in glassy LPS. The GAP surrogate approach allows for a variety of extensions and transferability to other SSEs.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The lithium thiophosphate (LPS) material class provides promising candidates for solid-state electrolytes (SSEs) in lithium ion batteries due to high lithium ion conductivities, non-critical elements, and low material cost. LPS materials are characterized by complex thiophosphate microchemistry and structural disorder influencing the material performance. To overcome the length and time scale restrictions of ab initio calculations to industrially applicable LPS materials, we develop a near-universal machine-learning interatomic potential for the LPS material class. The trained Gaussian Approximation Potential (GAP) can likewise describe crystal and glassy materials and different P-S connectivities PmSn. We apply the GAP surrogate model to probe lithium ion conductivity and the influence of thiophosphate subunits on the latter. The materials studied are crystals (modifications of Li3PS4 and Li7P3S11), and glasses of the xLi2S–(100 – x)P2S5 type (x = 67, 70 and 75). The obtained material properties are well aligned with experimental findings and we underscore the role of anion dynamics on lithium ion conductivity in glassy LPS. The GAP surrogate approach allows for a variety of extensions and transferability to other SSEs.
12.
S Stegmaier, K Reuter, C Scheurer
Exploiting Nanoscale Complexion in LATP Solid-State Electrolyte via Interfacial Mg2+ Doping Journal Article
In: Nanomaterials, vol. 12, no. 17, pp. 2912, 2022, ISSN: 2079-4991.
@article{nokey,
title = {Exploiting Nanoscale Complexion in LATP Solid-State Electrolyte via Interfacial Mg2+ Doping},
author = {S Stegmaier and K Reuter and C Scheurer},
url = {https://www.mdpi.com/2079-4991/12/17/2912},
issn = {2079-4991},
year = {2022},
date = {2022-08-24},
journal = {Nanomaterials},
volume = {12},
number = {17},
pages = {2912},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
11.
H Türk, T Götsch, F-P Schmidt, A Hammud, D Ivanov, L G J De Haart, I Vinke, R-A Eichel, R Schlögl, K Reuter, A Knop-Gericke, T Lunkenbein, C Scheurer
Sr Surface Enrichment in Solid Oxide Cells - Approaching the Limits of EDX Analysis by Multivariate Statistical Analysis and Simulations Journal Article
In: ChemCatChem, vol. n/a, no. n/a, 2022, ISSN: 1867-3880.
@article{nokey,
title = {Sr Surface Enrichment in Solid Oxide Cells - Approaching the Limits of EDX Analysis by Multivariate Statistical Analysis and Simulations},
author = {H T\"{u}rk and T G\"{o}tsch and F-P Schmidt and A Hammud and D Ivanov and L G J De Haart and I Vinke and R-A Eichel and R Schl\"{o}gl and K Reuter and A Knop-Gericke and T Lunkenbein and C Scheurer},
url = {https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cctc.202200300},
doi = {https://doi.org/10.1002/cctc.202200300},
issn = {1867-3880},
year = {2022},
date = {2022-07-08},
journal = {ChemCatChem},
volume = {n/a},
number = {n/a},
abstract = {In solid oxide cells, Sr segregation has been correlated with degradation. Yet, the atomistic mechanism remains unknown. Here we begin to localize the origin of Sr surface nucleation by combining force field based simulations, energy dispersive X-ray spectroscopy (EDX) and multi-variate statistical analysis. We find increased ion mobility in the complexion between yttria-stabilized zirconia and strontium-doped lanthanum manganite. Furthermore, we developed a robust and automated routine to detect localized nucleation seeds of Sr at the complexion/vacuum interface. This hints at a mechanism originating at the complexion and requires in-depths studies at the atomistic level, where the developed routine can be beneficial for analysing large hyperspectral EDX datasets.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In solid oxide cells, Sr segregation has been correlated with degradation. Yet, the atomistic mechanism remains unknown. Here we begin to localize the origin of Sr surface nucleation by combining force field based simulations, energy dispersive X-ray spectroscopy (EDX) and multi-variate statistical analysis. We find increased ion mobility in the complexion between yttria-stabilized zirconia and strontium-doped lanthanum manganite. Furthermore, we developed a robust and automated routine to detect localized nucleation seeds of Sr at the complexion/vacuum interface. This hints at a mechanism originating at the complexion and requires in-depths studies at the atomistic level, where the developed routine can be beneficial for analysing large hyperspectral EDX datasets.
10.
C G Staacke, H H Heenen, C Scheurer, G Csányi, K Reuter, J T Margraf
On the Role of Long-Range Electrostatics in Machine-Learned Interatomic Potentials for Complex Battery Materials Journal Article
In: ACS Applied Energy Materials, vol. 4, no. 11, pp. 12562-12569, 2021.
@article{nokey,
title = {On the Role of Long-Range Electrostatics in Machine-Learned Interatomic Potentials for Complex Battery Materials},
author = {C G Staacke and H H Heenen and C Scheurer and G Cs\'{a}nyi and K Reuter and J T Margraf},
url = {https://doi.org/10.1021/acsaem.1c02363},
doi = {10.1021/acsaem.1c02363},
year = {2021},
date = {2021-11-22},
journal = {ACS Applied Energy Materials},
volume = {4},
number = {11},
pages = {12562-12569},
abstract = {Modeling complex energy materials such as solid-state electrolytes (SSEs) realistically at the atomistic level strains the capabilities of state-of-the-art theoretical approaches. On one hand, the system sizes and simulation time scales required are prohibitive for first-principles methods such as the density functional theory. On the other hand, parameterizations for empirical potentials are often not available, and these potentials may ultimately lack the desired predictive accuracy. Fortunately, modern machine learning (ML) potentials are increasingly able to bridge this gap, promising first-principles accuracy at a much reduced computational cost. However, the local nature of these ML potentials typically means that long-range contributions arising, for example, from electrostatic interactions are neglected. Clearly, such interactions can be large in polar materials such as electrolytes, however. Herein, we investigate the effect that the locality assumption of ML potentials has on lithium mobility and defect formation energies in the SSE Li7P3S11. We find that neglecting long-range electrostatics is unproblematic for the description of lithium transport in the isotropic bulk. In contrast, (field-dependent) defect formation energies are only adequately captured by a hybrid potential combining ML and a physical model of electrostatic interactions. Broader implications for ML-based modeling of energy materials are discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Modeling complex energy materials such as solid-state electrolytes (SSEs) realistically at the atomistic level strains the capabilities of state-of-the-art theoretical approaches. On one hand, the system sizes and simulation time scales required are prohibitive for first-principles methods such as the density functional theory. On the other hand, parameterizations for empirical potentials are often not available, and these potentials may ultimately lack the desired predictive accuracy. Fortunately, modern machine learning (ML) potentials are increasingly able to bridge this gap, promising first-principles accuracy at a much reduced computational cost. However, the local nature of these ML potentials typically means that long-range contributions arising, for example, from electrostatic interactions are neglected. Clearly, such interactions can be large in polar materials such as electrolytes, however. Herein, we investigate the effect that the locality assumption of ML potentials has on lithium mobility and defect formation energies in the SSE Li7P3S11. We find that neglecting long-range electrostatics is unproblematic for the description of lithium transport in the isotropic bulk. In contrast, (field-dependent) defect formation energies are only adequately captured by a hybrid potential combining ML and a physical model of electrostatic interactions. Broader implications for ML-based modeling of energy materials are discussed.
9.
S Anniés, C Panosetti, M Voronenko, D Mauth, C Rahe, C Scheurer
In: Materials, vol. 14, no. 21, pp. 6633, 2021, ISSN: 1996-1944.
@article{nokey,
title = {Accessing Structural, Electronic, Transport and Mesoscale Properties of Li-GICs via a Complete DFTB Model with Machine-Learned Repulsion Potential},
author = {S Anni\'{e}s and C Panosetti and M Voronenko and D Mauth and C Rahe and C Scheurer},
url = {https://www.mdpi.com/1996-1944/14/21/6633},
issn = {1996-1944},
year = {2021},
date = {2021-11-03},
journal = {Materials},
volume = {14},
number = {21},
pages = {6633},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
8.
H Türk, F-P Schmidt, T Götsch, F Girgsdies, A Hammud, D Ivanov, I C Vinke, L G J De Haart, R-A Eichel, K Reuter, R Schlögl, A Knop-Gericke, C Scheurer, T Lunkenbein
Complexions at the Electrolyte/Electrode Interface in Solid Oxide Cells Journal Article
In: Advanced Materials Interfaces, vol. 8, no. 18, pp. 2100967, 2021, ISSN: 2196-7350.
@article{nokey,
title = {Complexions at the Electrolyte/Electrode Interface in Solid Oxide Cells},
author = {H T\"{u}rk and F-P Schmidt and T G\"{o}tsch and F Girgsdies and A Hammud and D Ivanov and I C Vinke and L G J De Haart and R-A Eichel and K Reuter and R Schl\"{o}gl and A Knop-Gericke and C Scheurer and T Lunkenbein},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/admi.202100967},
doi = {https://doi.org/10.1002/admi.202100967},
issn = {2196-7350},
year = {2021},
date = {2021-08-21},
journal = {Advanced Materials Interfaces},
volume = {8},
number = {18},
pages = {2100967},
abstract = {Abstract Rapid deactivation presently limits a wide spread use of high-temperature solid oxide cells (SOCs) as otherwise highly efficient chemical energy converters. With deactivation triggered by the ongoing conversion reactions, an atomic-scale understanding of the active triple-phase boundary between electrolyte, electrode, and gas phase is essential to increase cell performance. Here, a multi-method approach is used comprising transmission electron microscopy and first-principles calculations and molecular simulations to untangle the atomic arrangement of the prototypical SOC interface between a lanthanum strontium manganite (LSM) anode and a yttria-stabilized zirconia (YSZ) electrolyte in the as-prepared state after sintering. An interlayer of self-limited width with partial amorphization and strong compositional gradient is identified, thus exhibiting the characteristics of a complexion that is stabilized by the confinement between two bulk phases. This offers a new perspective to understand the function of SOCs at the atomic scale. Moreover, it opens up a hitherto unrealized design space to tune the conversion efficiency.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Rapid deactivation presently limits a wide spread use of high-temperature solid oxide cells (SOCs) as otherwise highly efficient chemical energy converters. With deactivation triggered by the ongoing conversion reactions, an atomic-scale understanding of the active triple-phase boundary between electrolyte, electrode, and gas phase is essential to increase cell performance. Here, a multi-method approach is used comprising transmission electron microscopy and first-principles calculations and molecular simulations to untangle the atomic arrangement of the prototypical SOC interface between a lanthanum strontium manganite (LSM) anode and a yttria-stabilized zirconia (YSZ) electrolyte in the as-prepared state after sintering. An interlayer of self-limited width with partial amorphization and strong compositional gradient is identified, thus exhibiting the characteristics of a complexion that is stabilized by the confinement between two bulk phases. This offers a new perspective to understand the function of SOCs at the atomic scale. Moreover, it opens up a hitherto unrealized design space to tune the conversion efficiency.
7.
M Kick, C Scheurer, H Oberhofer
Polaron-Assisted Charge Transport in Li-Ion Battery Anode Materials Journal Article
In: ACS Applied Energy Materials, 2021.
@article{,
title = {Polaron-Assisted Charge Transport in Li-Ion Battery Anode Materials},
author = {M Kick and C Scheurer and H Oberhofer},
url = {https://doi.org/10.1021/acsaem.1c01767},
doi = {10.1021/acsaem.1c01767},
year = {2021},
date = {2021-08-04},
journal = {ACS Applied Energy Materials},
abstract = {Lithium-ion batteries are without a doubt a key technology in the coming energy revolution. It is thus all the more surprising that one of the more prevalent Li battery anode materials, reduced lithium titanium oxide (LTO, Li4Ti5O12), is still poorly understood on a microscopic level. While recent theoretical and experimental evidence suggests that a polaron hopping mechanism is responsible for the increased electronic conductivity of reduced LTO, no such explanation exists for the concurrent improvements to the ionic mobility. In this computational study, we show that the presence of polaronic Ti3+ centers can indeed lead to a significant lowering of Li hopping barriers in both bulk and surface reduced LTO. For the latter, we find a reduced barrier height of roughly 40 meV compared to that of our pristine reference. This is in accordance with experimental findings showing that lithium-ion diffusion in reduced LTO is twice as high as that for pristine LTO. Finally, we show that\textemdashin accordance with experimental observations\textemdashpolaron formation upon lithiation of LTO leads to a similar behavior. Altogether, our analysis hints at a correlated movement of Li ions and polarons, highlighting LTO’s potential for rational defect engineering.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lithium-ion batteries are without a doubt a key technology in the coming energy revolution. It is thus all the more surprising that one of the more prevalent Li battery anode materials, reduced lithium titanium oxide (LTO, Li4Ti5O12), is still poorly understood on a microscopic level. While recent theoretical and experimental evidence suggests that a polaron hopping mechanism is responsible for the increased electronic conductivity of reduced LTO, no such explanation exists for the concurrent improvements to the ionic mobility. In this computational study, we show that the presence of polaronic Ti3+ centers can indeed lead to a significant lowering of Li hopping barriers in both bulk and surface reduced LTO. For the latter, we find a reduced barrier height of roughly 40 meV compared to that of our pristine reference. This is in accordance with experimental findings showing that lithium-ion diffusion in reduced LTO is twice as high as that for pristine LTO. Finally, we show that—in accordance with experimental observations—polaron formation upon lithiation of LTO leads to a similar behavior. Altogether, our analysis hints at a correlated movement of Li ions and polarons, highlighting LTO’s potential for rational defect engineering.
6.
T Götsch, H Tuerk, F-P Schmidt, I Vinke, De L B Haart, R Schlögl, K Reuter, R-A Eichel, A Knop-Gericke, C Scheurer
Visualizing the Atomic Structure Between YSZ and LSM: An Interface Stabilized by Complexions? Journal Article
In: ECS Transactions, vol. 103, no. 1, pp. 1331, 2021, ISSN: 1938-5862.
@article{,
title = {Visualizing the Atomic Structure Between YSZ and LSM: An Interface Stabilized by Complexions?},
author = {T G\"{o}tsch and H Tuerk and F-P Schmidt and I Vinke and De L B Haart and R Schl\"{o}gl and K Reuter and R-A Eichel and A Knop-Gericke and C Scheurer},
issn = {1938-5862},
year = {2021},
date = {2021-07-12},
urldate = {2021-07-12},
journal = {ECS Transactions},
volume = {103},
number = {1},
pages = {1331},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
5.
S Stegmaier, R Schierholz, I Povstugar, J Barthel, S P Rittmeyer, S Yu, S Wengert, S Rostami, H Kungl, K Reuter, R-A Eichel, C Scheurer
Nano-Scale Complexions Facilitate Li Dendrite-Free Operation in LATP Solid-State Electrolyte Journal Article
In: Advanced Energy Materials, vol. n/a, no. n/a, pp. 2100707, 2021, ISSN: 1614-6832.
@article{,
title = {Nano-Scale Complexions Facilitate Li Dendrite-Free Operation in LATP Solid-State Electrolyte},
author = {S Stegmaier and R Schierholz and I Povstugar and J Barthel and S P Rittmeyer and S Yu and S Wengert and S Rostami and H Kungl and K Reuter and R-A Eichel and C Scheurer},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/aenm.202100707},
doi = {https://doi.org/10.1002/aenm.202100707},
issn = {1614-6832},
year = {2021},
date = {2021-05-28},
journal = {Advanced Energy Materials},
volume = {n/a},
number = {n/a},
pages = {2100707},
abstract = {Abstract Dendrite formation and growth remains a major obstacle toward high-performance all solid-state batteries using Li metal anodes. The ceramic Li(1+x)Al(x)Ti(2−x)(PO4)3 (LATP) solid-state electrolyte shows a higher than expected stability against electrochemical decomposition despite a bulk electronic conductivity that exceeds a recently postulated threshold for dendrite-free operation. Here, transmission electron microscopy, atom probe tomography, and first-principles based simulations are combined to establish atomistic structural models of glass-amorphous LATP grain boundaries. These models reveal a nanometer-thin complexion layer that encapsulates the crystalline grains. The distinct composition of this complexion constitutes a sizable electronic impedance. Rather than fulfilling macroscopic bulk measures of ionic and electronic conduction, LATP might thus gain the capability to suppress dendrite nucleation by sufficient local separation of charge carriers at the nanoscale.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Dendrite formation and growth remains a major obstacle toward high-performance all solid-state batteries using Li metal anodes. The ceramic Li(1+x)Al(x)Ti(2−x)(PO4)3 (LATP) solid-state electrolyte shows a higher than expected stability against electrochemical decomposition despite a bulk electronic conductivity that exceeds a recently postulated threshold for dendrite-free operation. Here, transmission electron microscopy, atom probe tomography, and first-principles based simulations are combined to establish atomistic structural models of glass-amorphous LATP grain boundaries. These models reveal a nanometer-thin complexion layer that encapsulates the crystalline grains. The distinct composition of this complexion constitutes a sizable electronic impedance. Rather than fulfilling macroscopic bulk measures of ionic and electronic conduction, LATP might thus gain the capability to suppress dendrite nucleation by sufficient local separation of charge carriers at the nanoscale.
4.
C Griesser, H Li, E-M Wernig, D Winkler, Shakibi N Nia, T Mairegger, T Götsch, T Schachinger, A Steiger-Thirsfeld, S Penner, D Wielend, D A Egger, C Scheurer, K Reuter, J Kunze-Liebhäuser
True Nature of the Transition-Metal Carbide/Liquid Interface Determines Its Reactivity Journal Article
In: ACS Catalysis, pp. 4920-4928, 2021.
@article{,
title = {True Nature of the Transition-Metal Carbide/Liquid Interface Determines Its Reactivity},
author = {C Griesser and H Li and E-M Wernig and D Winkler and Shakibi N Nia and T Mairegger and T G\"{o}tsch and T Schachinger and A Steiger-Thirsfeld and S Penner and D Wielend and D A Egger and C Scheurer and K Reuter and J Kunze-Liebh\"{a}user},
url = {https://pubs.acs.org/doi/abs/10.1021/acscatal.1c00415},
doi = {10.1021/acscatal.1c00415},
year = {2021},
date = {2021-04-07},
urldate = {2021-04-07},
journal = {ACS Catalysis},
pages = {4920-4928},
abstract = {Compound materials, such as transition-metal (TM) carbides, are anticipated to be effective electrocatalysts for the carbon dioxide reduction reaction (CO2RR) to useful chemicals. This expectation is nurtured by density functional theory (DFT) predictions of a break of key adsorption energy scaling relations that limit CO2RR at parent TMs. Here, we evaluate these prospects for hexagonal Mo2C in aqueous electrolytes in a multimethod experiment and theory approach. We find that surface oxide formation completely suppresses the CO2 activation. The oxides are stable down to potentials as low as −1.9 V versus the standard hydrogen electrode, and solely the hydrogen evolution reaction (HER) is found to be active. This generally points to the absolute imperative of recognizing the true interface establishing under operando conditions in computational screening of catalyst materials. When protected from ambient air and used in nonaqueous electrolyte, Mo2C indeed shows CO2RR activity.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Compound materials, such as transition-metal (TM) carbides, are anticipated to be effective electrocatalysts for the carbon dioxide reduction reaction (CO2RR) to useful chemicals. This expectation is nurtured by density functional theory (DFT) predictions of a break of key adsorption energy scaling relations that limit CO2RR at parent TMs. Here, we evaluate these prospects for hexagonal Mo2C in aqueous electrolytes in a multimethod experiment and theory approach. We find that surface oxide formation completely suppresses the CO2 activation. The oxides are stable down to potentials as low as −1.9 V versus the standard hydrogen electrode, and solely the hydrogen evolution reaction (HER) is found to be active. This generally points to the absolute imperative of recognizing the true interface establishing under operando conditions in computational screening of catalyst materials. When protected from ambient air and used in nonaqueous electrolyte, Mo2C indeed shows CO2RR activity.
3.
M Kick, C Scheurer, H Oberhofer
Formation and stability of small polarons at the lithium-terminated Li4Ti5O12 (LTO) (111) surface Journal Article
In: The Journal of Chemical Physics, vol. 153, no. 14, pp. 144701, 2020.
@article{,
title = {Formation and stability of small polarons at the lithium-terminated Li4Ti5O12 (LTO) (111) surface},
author = {M Kick and C Scheurer and H Oberhofer},
url = {https://aip.scitation.org/doi/abs/10.1063/5.0021443},
doi = {10.1063/5.0021443},
year = {2020},
date = {2020-10-08},
journal = {The Journal of Chemical Physics},
volume = {153},
number = {14},
pages = {144701},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2.
M Kick, C Grosu, M Schuderer, C Scheurer, H Oberhofer
Mobile Small Polarons Qualitatively Explain Conductivity in Lithium Titanium Oxide Battery Electrodes Journal Article
In: Journal of Physical Chemistry Letters, vol. 11, no. 7, pp. 2535-2540, 2020, ISSN: 1948-7185.
@article{,
title = {Mobile Small Polarons Qualitatively Explain Conductivity in Lithium Titanium Oxide Battery Electrodes},
author = {M Kick and C Grosu and M Schuderer and C Scheurer and H Oberhofer},
url = {\<Go to ISI\>://WOS:000526348400022},
doi = {10.1021/acs.jpclett.0c00568},
issn = {1948-7185},
year = {2020},
date = {2020-03-12},
journal = {Journal of Physical Chemistry Letters},
volume = {11},
number = {7},
pages = {2535-2540},
abstract = {Lithium titanium oxide Li4Ti5O12 is an intriguing anode material promising particularly long-life batteries, due to its remarkable phase stability during (dis)charging of the cell. However, its usage is limited by its low intrinsic electronic conductivity. Introducing oxygen vacancies can be one method for overcoming this drawback, possibly by altering the charge carrier transport mechanism. We use Hubbard corrected density functional theory to show that polaronic states in combination with a possible hopping mechanism can play a crucial role in the experimentally observed increase in electronic conductivity. To gauge polaronic charge mobility, we compute the relative stabilities of different localization patterns and estimate polaron hopping barrier heights.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Lithium titanium oxide Li4Ti5O12 is an intriguing anode material promising particularly long-life batteries, due to its remarkable phase stability during (dis)charging of the cell. However, its usage is limited by its low intrinsic electronic conductivity. Introducing oxygen vacancies can be one method for overcoming this drawback, possibly by altering the charge carrier transport mechanism. We use Hubbard corrected density functional theory to show that polaronic states in combination with a possible hopping mechanism can play a crucial role in the experimentally observed increase in electronic conductivity. To gauge polaronic charge mobility, we compute the relative stabilities of different localization patterns and estimate polaron hopping barrier heights.
1.
S Laha, Y Lee, F Podjaski, D Weber, V Duppel, L M Schoop, F Pielnhofer, C Scheurer, K Muller, U Starke, K Reuter, B V Lotsch
Ruthenium Oxide Nanosheets for Enhanced Oxygen Evolution Catalysis in Acidic Medium Journal Article
In: Advanced Energy Materials, vol. 9, no. 15, 2019, ISSN: 1614-6832.
@article{,
title = {Ruthenium Oxide Nanosheets for Enhanced Oxygen Evolution Catalysis in Acidic Medium},
author = {S Laha and Y Lee and F Podjaski and D Weber and V Duppel and L M Schoop and F Pielnhofer and C Scheurer and K Muller and U Starke and K Reuter and B V Lotsch},
url = {\<Go to ISI\>://WOS:000465464500007},
doi = {10.1002/aenm.201803795},
issn = {1614-6832},
year = {2019},
date = {2019-02-21},
journal = {Advanced Energy Materials},
volume = {9},
number = {15},
keywords = {},
pubstate = {published},
tppubtype = {article}
}