Publications
2023
Franceschi, Giada; Diebold, Ulrike
Book ChapterIn: vol. 1, pp. 501-511, Encyclopedia of Materials: Electronics, 2023.
Abstract | Links | BibTeX | Tags: P02
@inbook{Franceschi_2023,
title = {Oxide Surfaces},
author = {Giada Franceschi and Ulrike Diebold},
url = {https://doi.org/10.1016/B978-0-12-819728-8.00059-0},
year = {2023},
date = {2023-04-12},
volume = {1},
pages = {501-511},
edition = {Encyclopedia of Materials: Electronics},
abstract = {The atomic details of metal oxide surfaces carry rich and tunable physics that can be exploited for various electronic applications. These details can be unveiled and rationalized through the surface science approach, which relies on single crystalline samples investigated under highly controlled conditions. Tremendous progress has been achieved in understanding and manipulating binary oxide surfaces at the atomic scale, closely followed by current research on multielement oxides. An overview is given through the examples of rutile TiO_{2}(110), SrTiO_{3}(110), and Sr-doped LaMnO_{3}(110), which also highlights the important role of atomic defects and surface reconstructions in determining a material’s macroscopic properties.},
keywords = {P02},
pubstate = {published},
tppubtype = {inbook}
}
The atomic details of metal oxide surfaces carry rich and tunable physics that can be exploited for various electronic applications. These details can be unveiled and rationalized through the surface science approach, which relies on single crystalline samples investigated under highly controlled conditions. Tremendous progress has been achieved in understanding and manipulating binary oxide surfaces at the atomic scale, closely followed by current research on multielement oxides. An overview is given through the examples of rutile TiO2(110), SrTiO3(110), and Sr-doped LaMnO3(110), which also highlights the important role of atomic defects and surface reconstructions in determining a material’s macroscopic properties.
Kraushofer, Florian; Meier, Matthias; Jakub, Zdeněk; Hütner, Johanna; Balajka, Jan; Hulva, Jan; Schmid, Michael; Franchini, Cesare; Diebold, Ulrike; Parkinson, Gareth S.
Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe3O4(111)
Journal ArticleOpen AccessIn: The Journal of Physical Chemistry Letters, vol. 14, no. 13, pp. 3258–3265, 2023.
Abstract | Links | BibTeX | Tags: P02, P04, P07
@article{Kraushofer2023,
title = {Oxygen-Terminated (1 × 1) Reconstruction of Reduced Magnetite Fe_{3}O_{4}(111)},
author = {Florian Kraushofer and Matthias Meier and Zdeněk Jakub and Johanna Hütner and Jan Balajka and Jan Hulva and Michael Schmid and Cesare Franchini and Ulrike Diebold and Gareth S. Parkinson},
doi = {10.1021/acs.jpclett.3c00281},
year = {2023},
date = {2023-03-28},
urldate = {2023-03-28},
journal = {The Journal of Physical Chemistry Letters},
volume = {14},
number = {13},
pages = {3258--3265},
publisher = {American Chemical Society (ACS)},
abstract = {The (111) facet of magnetite (Fe_{3}O_{4}) has been studied extensively by experimental and theoretical methods, but controversy remains regarding the structure of its low-energy surface terminations. Using density functional theory (DFT) computations, we demonstrate three reconstructions that are more favorable than the accepted Feoct2 termination under reducing conditions. All three structures change the coordination of iron in the kagome Feoct1 layer to be tetrahedral. With atomically resolved microscopy techniques, we show that the termination that coexists with the Fetet1 termination consists of tetrahedral iron capped by 3-fold coordinated oxygen atoms. This structure explains the inert nature of the reduced patches.},
keywords = {P02, P04, P07},
pubstate = {published},
tppubtype = {article}
}
The (111) facet of magnetite (Fe3O4) has been studied extensively by experimental and theoretical methods, but controversy remains regarding the structure of its low-energy surface terminations. Using density functional theory (DFT) computations, we demonstrate three reconstructions that are more favorable than the accepted Feoct2 termination under reducing conditions. All three structures change the coordination of iron in the kagome Feoct1 layer to be tetrahedral. With atomically resolved microscopy techniques, we show that the termination that coexists with the Fetet1 termination consists of tetrahedral iron capped by 3-fold coordinated oxygen atoms. This structure explains the inert nature of the reduced patches.
Hijes, Pablo Montero; Espinosa, Jorge R; Vega, Carlos; Dellago, Christoph
Minimum in the pressure dependence of the interfacial free energy between ice Ih and water
Journal ArticleOpen AccessIn: The Journal of Chemical Physics, vol. 158, no. 12, pp. 124503, 2023.
Abstract | Links | BibTeX | Tags: P12
@article{Hijes2023,
title = {Minimum in the pressure dependence of the interfacial free energy between ice Ih and water},
author = {Pablo Montero Hijes and Jorge R Espinosa and Carlos Vega and Christoph Dellago},
doi = {10.1063/5.0140814},
year = {2023},
date = {2023-03-23},
urldate = {2023-03-23},
journal = {The Journal of Chemical Physics},
volume = {158},
number = {12},
pages = {124503},
publisher = {AIP Publishing},
abstract = {Despite the importance of ice nucleation, this process has been barely explored at negative pressures. Here, we study homogeneous ice nucleation in stretched water by means of molecular dynamics seeding simulations using the TIP4P/Ice model. We observe that the critical nucleus size, interfacial free energy, free energy barrier, and nucleation rate barely change between isobars from −2600 to 500 bars when they are represented as a function of supercooling. This allows us to identify universal empirical expressions for homogeneous ice nucleation in the pressure range from −2600 to 500 bars. We show that this universal behavior arises from the pressure dependence of the interfacial free energy, which we compute by means of the mold integration technique, finding a shallow minimum around −2000 bars. Likewise, we show that the change in the interfacial free energy with pressure is proportional to the excess entropy and the slope of the melting line, exhibiting in the latter a reentrant behavior also at the same negative pressure. Finally, we estimate the excess internal energy and the excess entropy of the ice Ih–water interface.},
keywords = {P12},
pubstate = {published},
tppubtype = {article}
}
Despite the importance of ice nucleation, this process has been barely explored at negative pressures. Here, we study homogeneous ice nucleation in stretched water by means of molecular dynamics seeding simulations using the TIP4P/Ice model. We observe that the critical nucleus size, interfacial free energy, free energy barrier, and nucleation rate barely change between isobars from −2600 to 500 bars when they are represented as a function of supercooling. This allows us to identify universal empirical expressions for homogeneous ice nucleation in the pressure range from −2600 to 500 bars. We show that this universal behavior arises from the pressure dependence of the interfacial free energy, which we compute by means of the mold integration technique, finding a shallow minimum around −2000 bars. Likewise, we show that the change in the interfacial free energy with pressure is proportional to the excess entropy and the slope of the melting line, exhibiting in the latter a reentrant behavior also at the same negative pressure. Finally, we estimate the excess internal energy and the excess entropy of the ice Ih–water interface.
Verdi, Carla; Ranalli, Luigi; Franchini, Cesare; Kresse, Georg
Journal ArticleIn: Physical Review Materials, vol. 7, no. 3, pp. l030801, 2023.
Abstract | Links | BibTeX | Tags: P03, P07
@article{Verdi2023,
title = {Quantum paraelectricity and structural phase transitions in strontium titanate beyond density functional theory},
author = {Carla Verdi and Luigi Ranalli and Cesare Franchini and Georg Kresse},
doi = {10.1103/physrevmaterials.7.l030801},
year = {2023},
date = {2023-03-16},
journal = {Physical Review Materials},
volume = {7},
number = {3},
pages = {l030801},
publisher = {American Physical Society (APS)},
abstract = {We demonstrate an approach for calculating temperature-dependent quantum and anharmonic effects with beyond density-functional theory accuracy. By combining machine-learned potentials and the stochastic self-consistent harmonic approximation, we investigate the cubic to tetragonal transition in strontium titanate and show that the paraelectric phase is stabilized by anharmonic quantum fluctuations. We find that a quantitative understanding of the quantum paraelectric behavior requires a higher-level treatment of electronic correlation effects via the random phase approximation. This approach enables detailed studies of emergent properties in strongly anharmonic materials beyond density-functional theory.},
keywords = {P03, P07},
pubstate = {published},
tppubtype = {article}
}
We demonstrate an approach for calculating temperature-dependent quantum and anharmonic effects with beyond density-functional theory accuracy. By combining machine-learned potentials and the stochastic self-consistent harmonic approximation, we investigate the cubic to tetragonal transition in strontium titanate and show that the paraelectric phase is stabilized by anharmonic quantum fluctuations. We find that a quantitative understanding of the quantum paraelectric behavior requires a higher-level treatment of electronic correlation effects via the random phase approximation. This approach enables detailed studies of emergent properties in strongly anharmonic materials beyond density-functional theory.
Pramhaas, Verena; Unterhalt, Holger; Freund, Hans-Joachim; Rupprechter, Günther
Journal ArticleIn: Angewandte Chemie - International Edition, vol. 62, no. 19, 2023.
Abstract | Links | BibTeX | Tags: P08
@article{Pramhaas2023,
title = {Polarization-Dependent Sum-Frequency-Generation Spectroscopy for In Situ Tracking of Nanoparticle Morphology},
author = {Verena Pramhaas and Holger Unterhalt and Hans-Joachim Freund and Günther Rupprechter},
doi = {10.1002/anie.202300230},
year = {2023},
date = {2023-03-08},
journal = {Angewandte Chemie - International Edition},
volume = {62},
number = {19},
publisher = {Wiley},
abstract = {The surface structure of oxide-supported metal nanoparticles can be determined via characteristic vibrations of adsorbed probe molecules such as CO. Usually, spectroscopic studies focus on peak position and intensity, which are related to binding geometries and number of adsorption sites, respectively. Employing two differently prepared model catalysts, it is demonstrated that polarization-dependent sum-frequency-generation (SFG) spectroscopy reveals the average surface structure and shape of the nanoparticles. SFG results for different particle sizes and morphologies are compared to direct real-space structure analysis by TEM and STM. The described feature of SFG could be used to monitor particle restructuring in situ and may be a valuable tool for operando catalysis.},
keywords = {P08},
pubstate = {published},
tppubtype = {article}
}
The surface structure of oxide-supported metal nanoparticles can be determined via characteristic vibrations of adsorbed probe molecules such as CO. Usually, spectroscopic studies focus on peak position and intensity, which are related to binding geometries and number of adsorption sites, respectively. Employing two differently prepared model catalysts, it is demonstrated that polarization-dependent sum-frequency-generation (SFG) spectroscopy reveals the average surface structure and shape of the nanoparticles. SFG results for different particle sizes and morphologies are compared to direct real-space structure analysis by TEM and STM. The described feature of SFG could be used to monitor particle restructuring in situ and may be a valuable tool for operando catalysis.
Ranalli, Luigi; Verdi, Carla; Monacelli, Lorenzo; Kresse, Georg; Calandra, Matteo; Franchini, Cesare
Journal ArticleOpen AccessIn: Advanced Quantum Technology, vol. 6, iss. 4, 2023.
Abstract | Links | BibTeX | Tags: P03, P07
@article{Ranalli2023,
title = {Temperature-dependent anharmonic phonons in quantum paraelectric KTaO_{3} by first principles and machine-learned force fields},
author = {Luigi Ranalli and Carla Verdi and Lorenzo Monacelli and Georg Kresse and Matteo Calandra and Cesare Franchini},
doi = {10.1002/qute.202200131},
year = {2023},
date = {2023-02-22},
urldate = {2023-02-22},
journal = {Advanced Quantum Technology},
volume = {6},
issue = {4},
abstract = {Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties and designing new functionalities. This work examines the quantum paraelectric state, an elusive state of matter characterized by the smooth saturation of the ferroelectric instability at low temperature due to quantum fluctuations associated with anharmonic phonon effects. The temperature-dependent evolution of the soft ferroelectric phonon mode in the quantum paraelectric KTaO_{3} in the range 0–300 K is modeled by combining density functional theory (DFT) calculations with the stochastic self-consistent harmonic approximation assisted by an on-the-fly machine-learned force field. The calculated data show that including anharmonic terms is essential to stabilize the spurious imaginary ferroelectric phonon predicted by DFT in the harmonic approximation, in agreement with experiments. Augmenting the DFT workflow with machine-learned force fields allows for efficient stochastic sampling of the configuration space using large supercells in a wide temperature range, inaccessible to conventional ab initio protocols. This work proposes a robust computational workflow capable of accounting for collective behaviors involving different degrees of freedom and occurring at large time/length scales, paving the way for precise modeling and control of quantum effects in materials.},
keywords = {P03, P07},
pubstate = {published},
tppubtype = {article}
}
Understanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties and designing new functionalities. This work examines the quantum paraelectric state, an elusive state of matter characterized by the smooth saturation of the ferroelectric instability at low temperature due to quantum fluctuations associated with anharmonic phonon effects. The temperature-dependent evolution of the soft ferroelectric phonon mode in the quantum paraelectric KTaO3 in the range 0–300 K is modeled by combining density functional theory (DFT) calculations with the stochastic self-consistent harmonic approximation assisted by an on-the-fly machine-learned force field. The calculated data show that including anharmonic terms is essential to stabilize the spurious imaginary ferroelectric phonon predicted by DFT in the harmonic approximation, in agreement with experiments. Augmenting the DFT workflow with machine-learned force fields allows for efficient stochastic sampling of the configuration space using large supercells in a wide temperature range, inaccessible to conventional ab initio protocols. This work proposes a robust computational workflow capable of accounting for collective behaviors involving different degrees of freedom and occurring at large time/length scales, paving the way for precise modeling and control of quantum effects in materials.
Liu, Peitao; Wang, Jiantao; Avargues, Noah; Verdi, Carla; Singraber, Andreas; Karsai, Ferenc; Chen, Xing-Qiu; Kresse, Georg
Journal ArticleIn: Physical Review Letters, vol. 130, no. 7, pp. 078001, 2023.
Abstract | Links | BibTeX | Tags: P03
@article{Liu2023,
title = {Combining Machine Learning and Many-Body Calculations: Coverage-Dependent Adsorption of CO on Rh(111)},
author = {Peitao Liu and Jiantao Wang and Noah Avargues and Carla Verdi and Andreas Singraber and Ferenc Karsai and Xing-Qiu Chen and Georg Kresse},
doi = {10.1103/physrevlett.130.078001},
year = {2023},
date = {2023-02-17},
urldate = {2023-02-01},
journal = {Physical Review Letters},
volume = {130},
number = {7},
pages = {078001},
publisher = {American Physical Society (APS)},
abstract = {Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges to theoretical modeling. Pretty much all existing density functionals fail to accurately describe surface energies and CO adsorption site preference as well as adsorption energies simultaneously. Although the random phase approximation (RPA) cures these density functional theory failures, its large computational cost makes it prohibitive to study the CO adsorption for any but the simplest ordered cases. Here, we address these challenges by developing a machine-learned force field (MLFF) with near RPA accuracy for the prediction of coverage-dependent adsorption of CO on the Rh(111) surface through an efficient on-the-fly active learning procedure and a Δ-machine learning approach. We show that the RPA-derived MLFF is capable to accurately predict the Rh(111) surface energy and CO adsorption site preference as well as adsorption energies at different coverages that are all in good agreement with experiments. Moreover, the coverage-dependent ground-state adsorption patterns and adsorption saturation coverage are identified.},
keywords = {P03},
pubstate = {published},
tppubtype = {article}
}
Adsorption of carbon monoxide (CO) on transition-metal surfaces is a prototypical process in surface sciences and catalysis. Despite its simplicity, it has posed great challenges to theoretical modeling. Pretty much all existing density functionals fail to accurately describe surface energies and CO adsorption site preference as well as adsorption energies simultaneously. Although the random phase approximation (RPA) cures these density functional theory failures, its large computational cost makes it prohibitive to study the CO adsorption for any but the simplest ordered cases. Here, we address these challenges by developing a machine-learned force field (MLFF) with near RPA accuracy for the prediction of coverage-dependent adsorption of CO on the Rh(111) surface through an efficient on-the-fly active learning procedure and a Δ-machine learning approach. We show that the RPA-derived MLFF is capable to accurately predict the Rh(111) surface energy and CO adsorption site preference as well as adsorption energies at different coverages that are all in good agreement with experiments. Moreover, the coverage-dependent ground-state adsorption patterns and adsorption saturation coverage are identified.
Raab, Maximilian; Zeininger, Johannes; Suchorski, Yuri; Tokuda, Keita; Rupprechter, Günther
Emergence of chaos in a compartmentalized catalytic reaction nanosystem
Journal ArticleOpen AccessIn: Nature Communications, vol. 14, pp. 736–745, 2023.
Abstract | Links | BibTeX | Tags: P08
@article{Raab2023,
title = {Emergence of chaos in a compartmentalized catalytic reaction nanosystem},
author = {Maximilian Raab and Johannes Zeininger and Yuri Suchorski and Keita Tokuda and Günther Rupprechter},
doi = {10.1038/s41467-023-36434-y},
year = {2023},
date = {2023-02-10},
urldate = {2023-02-01},
journal = {Nature Communications},
volume = {14},
pages = {736--745},
publisher = {Springer Science and Business Media LLC},
abstract = {In compartmentalized systems, chemical reactions may proceed in differing ways even in adjacent compartments. In compartmentalized nanosystems, the reaction behaviour may deviate from that observed on the macro- or mesoscale. In situ studies of processes in such nanosystems meet severe experimental challenges, often leaving the field to theoretical simulations. Here, a rhodium nanocrystal surface consisting of different nm-sized nanofacets is used as a model of a compartmentalized reaction nanosystem. Using field emission microscopy, different reaction modes are observed, including a transition to spatio-temporal chaos. The transitions between different modes are caused by variations of the hydrogen pressure modifying the strength of diffusive coupling between individual nanofacets. Microkinetic simulations, performed for a network of 52 coupled oscillators, reveal the origins of the different reaction modes. Since diffusive coupling is characteristic for many living and non-living compartmentalized systems, the current findings may be relevant for a wide class of reaction systems.},
keywords = {P08},
pubstate = {published},
tppubtype = {article}
}
In compartmentalized systems, chemical reactions may proceed in differing ways even in adjacent compartments. In compartmentalized nanosystems, the reaction behaviour may deviate from that observed on the macro- or mesoscale. In situ studies of processes in such nanosystems meet severe experimental challenges, often leaving the field to theoretical simulations. Here, a rhodium nanocrystal surface consisting of different nm-sized nanofacets is used as a model of a compartmentalized reaction nanosystem. Using field emission microscopy, different reaction modes are observed, including a transition to spatio-temporal chaos. The transitions between different modes are caused by variations of the hydrogen pressure modifying the strength of diffusive coupling between individual nanofacets. Microkinetic simulations, performed for a network of 52 coupled oscillators, reveal the origins of the different reaction modes. Since diffusive coupling is characteristic for many living and non-living compartmentalized systems, the current findings may be relevant for a wide class of reaction systems.
Maqbool, Qaisar; Yigit, Nevzat; Stöger-Pollach, Michael; Ruello, Maria Letizia; Tittarelli, Francesca; Rupprechter, Günther
Operando monitoring of a room temperature nanocomposite methanol sensor
Journal ArticleOpen AccessIn: Catalysis Science & Technology, vol. 13, iss. 3, pp. 624–636, 2023.
Abstract | Links | BibTeX | Tags: P08
@article{Maqbool2023,
title = {\textit{Operando} monitoring of a room temperature nanocomposite methanol sensor},
author = {Qaisar Maqbool and Nevzat Yigit and Michael Stöger-Pollach and Maria Letizia Ruello and Francesca Tittarelli and Günther Rupprechter},
doi = {10.1039/d2cy01395a},
year = {2023},
date = {2023-02-07},
urldate = {2023-02-07},
journal = {Catalysis Science & Technology},
volume = {13},
issue = {3},
pages = {624--636},
publisher = {Royal Society of Chemistry (RSC)},
abstract = {The sensing of volatile organic compounds by composites containing metal oxide semiconductors is typically explained via adsorption–desorption and surface electrochemical reactions changing the sensor's resistance. The analysis of molecular processes on chemiresistive gas sensors is often based on indirect evidence, whereas \textit{in situ} or \textit{operando} studies monitoring the gas/surface interactions enable a direct insight. Here we report a cross-disciplinary approach employing spectroscopy of working sensors to investigate room temperature methanol detection, contrasting well-characterized nanocomposite (TiO_{2}@rGO-NC) and reduced-graphene oxide (rGO) sensors. Methanol interactions with the sensors were examined by (quasi) \textit{operando}-DRIFTS and \textit{in situ}-ATR-FTIR spectroscopy, the first paralleled by simultaneous measurements of resistance. The sensing mechanism was also studied by mass spectroscopy (MS), revealing the surface electrochemical reactions. The \textit{operando} and \textit{in situ} spectroscopy techniques demonstrated that the sensing mechanism on the nanocomposite relies on the combined effect of methanol reversible physisorption and irreversible chemisorption, sensor modification over time, and electron/O_{2} depletion–restoration due to a surface electrochemical reaction forming CO_{2} and H_{2}O.},
keywords = {P08},
pubstate = {published},
tppubtype = {article}
}
The sensing of volatile organic compounds by composites containing metal oxide semiconductors is typically explained via adsorption–desorption and surface electrochemical reactions changing the sensor's resistance. The analysis of molecular processes on chemiresistive gas sensors is often based on indirect evidence, whereas in situ or operando studies monitoring the gas/surface interactions enable a direct insight. Here we report a cross-disciplinary approach employing spectroscopy of working sensors to investigate room temperature methanol detection, contrasting well-characterized nanocomposite (TiO2@rGO-NC) and reduced-graphene oxide (rGO) sensors. Methanol interactions with the sensors were examined by (quasi) operando-DRIFTS and in situ-ATR-FTIR spectroscopy, the first paralleled by simultaneous measurements of resistance. The sensing mechanism was also studied by mass spectroscopy (MS), revealing the surface electrochemical reactions. The operando and in situ spectroscopy techniques demonstrated that the sensing mechanism on the nanocomposite relies on the combined effect of methanol reversible physisorption and irreversible chemisorption, sensor modification over time, and electron/O2 depletion–restoration due to a surface electrochemical reaction forming CO2 and H2O.
Corrias, Marco; Papa, Lorenzo; Sokolovíc, Igor; Birschitzky, Viktor; Gorfer, Alexander; Setvin, Martin; Schmid, Michael; Diebold, Ulrike; Reticcioli, Michele; Franchini, Cesare
Automated Real-Space Lattice Extraction for Atomic Force Microscopy Images
Journal ArticleOpen AccessIn: Machine Learning: Science and Technology, vol. 4, pp. 015015, 2023.
Abstract | Links | BibTeX | Tags: P02, P07
@article{Corrias2023,
title = {Automated Real-Space Lattice Extraction for Atomic Force Microscopy Images},
author = {Marco Corrias and Lorenzo Papa and Igor Sokolovíc and Viktor Birschitzky and Alexander Gorfer and Martin Setvin and Michael Schmid and Ulrike Diebold and Michele Reticcioli and Cesare Franchini},
doi = {10.1088/2632-2153/acb5e0},
year = {2023},
date = {2023-01-24},
urldate = {2023-01-24},
journal = {Machine Learning: Science and Technology},
volume = {4},
pages = {015015},
abstract = {Analyzing atomically resolved images is a time-consuming process requiring solid experience and substantial human intervention. In addition, the acquired images contain a large amount of information such as crystal structure, presence and distribution of defects, and formation of domains, which need to be resolved to understand a material's surface structure. Therefore, machine learning techniques have been applied in scanning probe and electron microscopies during the last years, aiming for automatized and efficient image analysis. This work introduces a free and open source tool (AiSurf: Automated Identification of Surface Images) developed to inspect atomically resolved images via Scale-Invariant Feature Transform (SIFT) and Clustering Algorithms (CA). AiSurf extracts primitive lattice vectors, unit cells, and structural distortions from the original image, with no pre-assumption on the lattice and minimal user intervention. The method is applied to various atomically resolved non-contact atomic force microscopy (AFM) images of selected surfaces with different levels of complexity: anatase TiO_{2}(101), oxygen deficient rutile TiO_{2}(110) with and without CO adsorbates, SrTiO_{3}(001) with Sr vacancies and graphene with C vacancies. The code delivers excellent results and is tested against atom misclassification and artifacts, thereby facilitating the interpretation of scanning probe microscopy images.},
keywords = {P02, P07},
pubstate = {published},
tppubtype = {article}
}
Analyzing atomically resolved images is a time-consuming process requiring solid experience and substantial human intervention. In addition, the acquired images contain a large amount of information such as crystal structure, presence and distribution of defects, and formation of domains, which need to be resolved to understand a material's surface structure. Therefore, machine learning techniques have been applied in scanning probe and electron microscopies during the last years, aiming for automatized and efficient image analysis. This work introduces a free and open source tool (AiSurf: Automated Identification of Surface Images) developed to inspect atomically resolved images via Scale-Invariant Feature Transform (SIFT) and Clustering Algorithms (CA). AiSurf extracts primitive lattice vectors, unit cells, and structural distortions from the original image, with no pre-assumption on the lattice and minimal user intervention. The method is applied to various atomically resolved non-contact atomic force microscopy (AFM) images of selected surfaces with different levels of complexity: anatase TiO2(101), oxygen deficient rutile TiO2(110) with and without CO adsorbates, SrTiO3(001) with Sr vacancies and graphene with C vacancies. The code delivers excellent results and is tested against atom misclassification and artifacts, thereby facilitating the interpretation of scanning probe microscopy images.