Updated list of AiiDA powered research papers (#60)

A manual search was performed to update the list of papers powered by AiiDA.
After this update, a questionnaire is sent out with the request for people to
communicate any publications that were missed so they can be added by us.

Author: khsrali

docs/sections/science.md

@@ -10,9 +10,82 @@ The AiiDA team conducts an **annual survey** on the [AiiDA mailing list](./maili
 ## AiiDA-powered publications
 
 :::{figure} ../pics/publication-chart.png
-A list of publications containing calculations powered by AiiDA, selected from the [citations of the AiiDA paper](https://scholar.google.com/scholar?cites=10268089832296963062&as_sdt=2005&sciodt=0,5&hl=en).
+A histogram of publications containing calculations powered by AiiDA, selected from the [citations of the AiiDA paper](https://scholar.google.com/scholar?cites=10268089832296963062&as_sdt=2005&sciodt=0,5&hl=en).
 :::
 
+If you use AiiDA in your research and your paper is not listed on this page, feel free to send us an [email](mailto:developers@aiida.net) with the DOI of your paper.
+
+
+### Publications<sup>*</sup> from 2024 (up to March)
+_<sup>*</sup> This is an incomplete list of research papers that utilise AiiDA. Extracted manually from all citations of just these two articles ([Main](https://doi.org/10.1038/s41597-020-00638-4) and [Engine](https://doi.org/10.1016/j.commatsci.2020.110086))_
+
+- H. Saßnick, F. Machado Ferreira De Araujo, J. Edzards, C. Cocchi, [Impact of Ligand Substitution and Metal Node Exchange in the Electronic Properties of Scandium Terephthalate Frameworks](https://doi.org/10.1021/acs.inorgchem.3c03945), _Inorganic Chemistry_ **63,** 2098-2108 (2024).
+- A. Tellez-Mora, X. He, E. Bousquet, L. Wirtz, A. Romero, [Systematic determination of a material’s magnetic ground state from first principles](https://doi.org/10.1038/s41524-024-01202-z), _npj Computational Materials_ **10,** no. 20,  (2024).
+- D. Grassano, N. Marzari, D. Campi, [High-throughput screening of Weyl semimetals](https://doi.org/10.1103/physrevmaterials.8.024201), _Physical Review Materials_ **8,** no. 024201,  (2024).
+- H. Saßnick, C. Cocchi, [Automated analysis of surface facets: the example of cesium telluride](https://doi.org/10.1038/s41524-024-01224-7), _npj Computational Materials_ **10,** no. 38,  (2024).
+
+
+### Publications<sup>*</sup> from 2023
+_<sup>*</sup> This is an incomplete list of research papers that utilise AiiDA. Extracted manually from all citations of just these two articles ([Main](https://doi.org/10.1038/s41597-020-00638-4) and [Engine](https://doi.org/10.1016/j.commatsci.2020.110086))_
+
+- K. Jablonka, A. Rosen, A. Krishnapriyan, B. Smit, [An Ecosystem for Digital Reticular Chemistry](https://doi.org/10.1021/acscentsci.2c01177), _ACS Central Science_ **9,** 563-581 (2023).
+- F. dos Santos, N. Marzari, [Fermi energy determination for advanced smearing techniques](https://doi.org/10.1103/physrevb.107.195122), _Physical Review B_ **107,** no. 195122,  (2023).
+- M. Bonacci, J. Qiao, N. Spallanzani, A. Marrazzo, G. Pizzi, E. Molinari, D. Varsano, A. Ferretti, D. Prezzi, [Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows](https://doi.org/10.1038/s41524-023-01027-2), _npj Computational Materials_ **9,** no. 74,  (2023).
+- B. Mourino, K. Jablonka, A. Ortega‐Guerrero, B. Smit, [In Search of Covalent Organic Framework Photocatalysts: A DFT‐Based Screening Approach](https://doi.org/10.1002/adfm.202301594), _Advanced Functional Materials_ **33,**  (2023).
+- S. Shepherd, G. Tribello, D. Wilkins, [A fully quantum-mechanical treatment for kaolinite](https://doi.org/10.1063/5.0152361), _The Journal of Chemical Physics_ **158,**  (2023).
+- S. Muy, C. Johnston, N. Marzari, [AiiDA-defects: an automated and fully reproducible workflow for the complete characterization of defect chemistry in functional materials](https://doi.org/10.1088/2516-1075/ace014), _Electronic Structure_ **5,** 024009 (2023).
+- D. Campi, N. Mounet, M. Gibertini, G. Pizzi, N. Marzari, [Expansion of the Materials Cloud 2D Database](https://doi.org/10.1021/acsnano.2c11510), _ACS Nano_ **17,** 11268-11278 (2023).
+- D. Li, H. Wang, K. Li, B. Zhu, K. Jiang, D. Backes, L. Veiga, J. Shi, P. Roy, M. Xiao, A. Chen, Q. Jia, T. Lee, S. Dhesi, D. Scanlon, J. MacManus-Driscoll, P. van Aken, K. Zhang, W. Li, [Emergent and robust ferromagnetic-insulating state in highly strained ferroelastic LaCoO3 thin films](https://doi.org/10.1038/s41467-023-39369-6), _Nature Communications_ **14,** no. 3638,  (2023).
+- S. Ghosh, P. Rüßmann, Y. Mokrousov, F. Freimuth, A. Kosma, [Perspective on spin–orbit torque, topology, and reciprocal and real-space spin textures in magnetic materials and heterostructures](https://doi.org/10.1063/5.0149849), _Journal of Applied Physics_ **133,**  (2023).
+- J. Cen, B. Zhu, D. Scanlon, [Exploring battery cathode materials in the Li-Ni-O phase diagrams using structure prediction](https://doi.org/10.1088/2515-7655/acdd9c), _Journal of Physics: Energy_ **5,** 035005 (2023).
+- F. Yao, V. Multian, Z. Wang, N. Ubrig, J. Teyssier, F. Wu, E. Giannini, M. Gibertini, I. Gutiérrez-Lezama, A. Morpurgo, [Multiple antiferromagnetic phases and magnetic anisotropy in exfoliated CrBr3 multilayers](https://doi.org/10.1038/s41467-023-40723-x), _Nature Communications_ **14,** no. 4969,  (2023).
+- J. Železný, Y. Yahagi, C. Gomez-Olivella, Y. Zhang, Y. Sun, [High-throughput study of the anomalous Hall effect](https://doi.org/10.1038/s41524-023-01113-5), _npj Computational Materials_ **9,** no. 151,  (2023).
+- M. Vogler, J. Busk, H. Hajiyani, P. Jørgensen, N. Safaei, I. Castelli, F. Ramirez, J. Carlsson, G. Pizzi, S. Clark, F. Hanke, A. Bhowmik, H. Stein, [Brokering between tenants for an international materials acceleration platform](https://doi.org/10.1016/j.matt.2023.07.016), _Matter_ **6,** 2647-2665 (2023).
+- D. Grassano, D. Campi, A. Marrazzo, N. Marzari, [Complementary screening for quantum spin Hall insulators in two-dimensional exfoliable materials](https://doi.org/10.1103/physrevmaterials.7.094202), _Physical Review Materials_ **7,** no. 094202,  (2023).
+- L. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. Koch, M. Kühbach, A. Ladines, P. Lambrix, M. Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, M. Scheffler, [Shared metadata for data-centric materials science](https://doi.org/10.1038/s41597-023-02501-8), _Scientific Data_ **10,** no. 626,  (2023).
+- P. Henkel, J. Li, G. Grandhi, P. Vivo, P. Rinke, [Screening Mixed-Metal Sn<sub>2</sub>M(III)Ch<sub>2</sub>X<sub>3</sub> Chalcohalides for Photovoltaic Applications](https://doi.org/10.1021/acs.chemmater.3c01629), _Chemistry of Materials_ **35,** 7761-7769 (2023).
+- J. Qiao, G. Pizzi, N. Marzari, [Automated mixing of maximally localized Wannier functions into target manifolds](https://doi.org/10.1038/s41524-023-01147-9), _npj Computational Materials_ **9,** no. 206,  (2023).
+- Q. Chen, M. Di Giovannantonio, K. Eimre, J. Urgel, P. Ruffieux, C. Pignedoli, K. Müllen, R. Fasel, A. Narita, [On‐Surface Interchain Coupling and Skeletal Rearrangement of Indenofluorene Polymers](https://doi.org/10.1002/macp.202300345), _Macromolecular Chemistry and Physics_ **224,**  (2023).
+- E. Bosoni, L. Beal, M. Bercx, P. Blaha, S. Blügel, J. Bröder, M. Callsen, S. Cottenier, A. Degomme, V. Dikan, K. Eimre, E. Flage-Larsen, M. Fornari, A. Garcia, L. Genovese, M. Giantomassi, S. Huber, H. Janssen, G. Kastlunger, M. Krack, G. Kresse, T. Kühne, K. Lejaeghere, G. Madsen, M. Marsman, N. Marzari, G. Michalicek, H. Mirhosseini, T. Müller, G. Petretto, C. Pickard, S. Poncé, G. Rignanese, O. Rubel, T. Ruh, M. Sluydts, D. Vanpoucke, S. Vijay, M. Wolloch, D. Wortmann, A. Yakutovich, J. Yu, A. Zadoks, B. Zhu, G. Pizzi, [How to verify the precision of density-functional-theory implementations via reproducible and universal workflows](https://doi.org/10.1038/s42254-023-00655-3), _Nature Reviews Physics_ **6,** 45-58 (2023).
+- P. Rüßmann, M. Bahari, S. Blügel, B. Trauzettel, [Interorbital Cooper pairing at finite energies in Rashba surface states](https://doi.org/10.1103/physrevresearch.5.043181), _Physical Review Research_ **5,** no. 043181,  (2023).
+- Q. Yang, I. Surin, J. Geiger, H. Eliasson, M. Agrachev, V. Kondratenko, A. Zanina, F. Krumeich, G. Jeschke, R. Erni, E. Kondratenko, N. López, J. Pérez-Ramírez, [Lattice-Stabilized Chromium Atoms on Ceria for N<sub>2</sub>O Synthesis](https://doi.org/10.1021/acscatal.3c04463), _ACS Catalysis_ **13,** 15977-15990 (2023).
+- P. Si, A. Jayanth, O. Andreussi, [Soft‐sphere continuum solvation models for nonaqueous solvents](https://doi.org/10.1002/jcc.27254), _Journal of Computational Chemistry_ **45,** 719-737 (2023).
+- X. Wei, A. Jalil, P. Rüßmann, Y. Ando, D. Grützmacher, S. Blügel, J. Mayer, [Atomic Diffusion-Induced Polarization and Superconductivity in Topological Insulator-Based Heterostructures](https://doi.org/10.1021/acsnano.3c08601), _ACS Nano_ **18,** 571-580 (2023).
+- G. Gebreyesus, L. Bastonero, M. Kotiuga, N. Marzari, I. Timrov, [Understanding the role of Hubbard corrections in the rhombohedral phase of BaTiO<sub>3<sub>](https://doi.org/10.1103/physrevb.108.235171), _Physical Review B_ **108,** no. 235171,  (2023).
+
+
+### Publications<sup>*</sup> from 2022
+_<sup>*</sup> This is an incomplete list of research papers that utilise AiiDA. Extracted manually from all citations of just these two articles ([Main](https://doi.org/10.1038/s41597-020-00638-4) and [Engine](https://doi.org/10.1016/j.commatsci.2020.110086))_
+
+- M. Schmitt, T. Denneulin, A. Kovács, T. Saunderson, P. Rüßmann, A. Shahee, T. Scholz, A. Tavabi, M. Gradhand, P. Mavropoulos, B. Lotsch, R. Dunin-Borkowski, Y. Mokrousov, S. Blügel, M. Kläui, [Skyrmionic spin structures in layered Fe5GeTe2 up to room temperature](https://doi.org/10.1038/s42005-022-01031-w), _Communications Physics_ **5,** no. 254,  (2022).
+- L. Gigli, M. Veit, M. Kotiuga, G. Pizzi, N. Marzari, M. Ceriotti, [Thermodynamics and dielectric response of BaTiO3 by data-driven modeling](https://doi.org/10.1038/s41524-022-00845-0), _npj Computational Materials_ **8,** no. 209,  (2022).
+- V. Borisov, Q. Xu, N. Ntallis, R. Clulow, V. Shtender, J. Cedervall, M. Sahlberg, K. Wikfeldt, D. Thonig, M. Pereiro, A. Bergman, A. Delin, O. Eriksson, [Tuning skyrmions in B20 compounds by 4d and 5d doping](https://doi.org/10.1103/physrevmaterials.6.084401), _Physical Review Materials_ **6,** no. 084401,  (2022).
+- T. Hsu, T. Pham, N. Keilbart, S. Weitzner, J. Chapman, P. Xiao, S. Qiu, X. Chen, B. Wood, [Efficient and interpretable graph network representation for angle-dependent properties applied to optical spectroscopy](https://doi.org/10.1038/s41524-022-00841-4), _npj Computational Materials_ **8,** no. 151,  (2022).
+- W. Xu, K. Reuter, M. Andersen, [Predicting binding motifs of complex adsorbates using machine learning with a physics-inspired graph representation](https://doi.org/10.1038/s43588-022-00280-7), _Nature Computational Science_ **2,** 443-450 (2022).
+- S. Vijay, G. Kastlunger, K. Chan, J. Nørskov, [Limits to scaling relations between adsorption energies?](https://doi.org/10.1063/5.0096625), _The Journal of Chemical Physics_ **156,**  (2022).
+- D. Marchand, W. Curtin, [Machine learning for metallurgy IV: A neural network potential for Al-Cu-Mg and Al-Cu-Mg-Zn](https://doi.org/10.1103/physrevmaterials.6.053803), _Physical Review Materials_ **6,** no. 053803,  (2022).
+- A. Lund, G. Manohara, A. Song, K. Jablonka, C. Ireland, L. Cheah, B. Smit, S. Garcia, J. Reimer, [Characterization of Chemisorbed Species and Active Adsorption Sites in Mg–Al Mixed Metal Oxides for High-Temperature CO<sub>2</sub> Capture](https://doi.org/10.1021/acs.chemmater.1c03101), _Chemistry of Materials_ **34,** 3893-3901 (2022).
+- D. Li, B. Zhu, D. Backes, L. Veiga, T. Lee, H. Wang, Q. He, P. Roy, J. Zhang, J. Shi, A. Chen, P. van Aken, Q. Jia, S. Dhesi, D. Scanlon, K. Zhang, W. Li, [Manipulating the metal-to-insulator transition and magnetic properties in manganite thin films via epitaxial strain](https://doi.org/10.1103/physrevb.105.165426), _Physical Review B_ **105,** no. 165426,  (2022).
+- M. Betti, E. Placidi, C. Izzo, E. Blundo, A. Polimeni, M. Sbroscia, J. Avila, P. Dudin, K. Hu, Y. Ito, D. Prezzi, M. Bonacci, E. Molinari, C. Mariani, [Gap Opening in Double-Sided Highly Hydrogenated Free-Standing Graphene](https://doi.org/10.1021/acs.nanolett.2c00162), _Nano Letters_ **22,** 2971-2977 (2022).
+- H. Yang, N. Bansal, P. Rüßmann, M. Hoffmann, L. Zhang, D. Go, Q. Li, A. Haghighirad, K. Sen, S. Blügel, M. Le Tacon, Y. Mokrousov, W. Wulfhekel, [Magnetic domain walls of the van der Waals material Fe<sub>3</sub>GeTe<sub>2</sub>](https://doi.org/10.1088/2053-1583/ac5d0e), _2D Materials_ **9,** 025022 (2022).
+- P. Rüßmann, S. Blügel, [Density functional Bogoliubov-de Gennes analysis of superconducting Nb and Nb(110) surfaces](https://doi.org/10.1103/physrevb.105.125143), _Physical Review B_ **105,** no. 125143,  (2022).
+- M. Kotiuga, S. Halilov, B. Kozinsky, M. Fornari, N. Marzari, G. Pizzi, [Microscopic picture of paraelectric perovskites from structural prototypes](https://doi.org/10.1103/physrevresearch.4.l012042), _Physical Review Research_ **4,** no. L012042,  (2022).
+- M. Bonacci, M. Zanfrognini, E. Molinari, A. Ruini, M. Caldas, A. Ferretti, D. Varsano, [Excitonic effects in graphene-like C<sub>3</sub>n](https://doi.org/10.1103/physrevmaterials.6.034009), _Physical Review Materials_ **6,** no. 034009,  (2022).
+- H. Saßnick, C. Cocchi, [Exploring cesium–tellurium phase space via high-throughput calculations beyond semi-local density-functional theory](https://doi.org/10.1063/5.0082710), _The Journal of Chemical Physics_ **156,**  (2022).
+- Y. Wang, S. Kavanagh, I. Burgués-Ceballos, A. Walsh, D. Scanlon, G. Konstantatos, [Cation disorder engineering yields AgBiS2 nanocrystals with enhanced optical absorption for efficient ultrathin solar cells](https://doi.org/10.1038/s41566-021-00950-4), _Nature Photonics_ **16,** 235-241 (2022).
+- B. Zhu, D. Scanlon, [Predicting Lithium Iron Oxysulfides for Battery Cathodes](https://doi.org/10.1021/acsaem.1c03094), _ACS Applied Energy Materials_ **5,** 575-584 (2022).
+
+
+### Publications<sup>*</sup> from 2021
+_<sup>*</sup> This is an incomplete list of research papers that utilise AiiDA. Extracted manually from all citations of just these two articles ([Main](https://doi.org/10.1038/s41597-020-00638-4) and [Engine](https://doi.org/10.1016/j.commatsci.2020.110086))_
+
+- S. Vijay, H. Kristoffersen, Y. Katayama, Y. Shao-Horn, I. Chorkendorff, B. Seger, K. Chan, [How to extract adsorption energies, adsorbate–adsorbate interaction parameters and saturation coverages from temperature programmed desorption experiments](https://doi.org/10.1039/d1cp01992a), _Physical Chemistry Chemical Physics_ **23,** 24396-24402 (2021).
+- R. Goodall, B. Zhu, J. MacManus‐Driscoll, A. Lee, [Materials Informatics Reveals Unexplored Structure Space in Cuprate Superconductors](https://doi.org/10.1002/adfm.202104696), _Advanced Functional Materials_ **31,**  (2021).
+- C. Cocchi, H. Saßnick, [Ab Initio Quantum-Mechanical Predictions of Semiconducting Photocathode Materials](https://doi.org/10.3390/mi12091002), _Micromachines_ **12,** 1002 (2021).
+- A. Jain, D. Marchand, A. Glensk, M. Ceriotti, W. Curtin, [Machine learning for metallurgy III: A neural network potential for Al-Mg-Si](https://doi.org/10.1103/physrevmaterials.5.053805), _Physical Review Materials_ **5,** no. 053805,  (2021).
+- T. Sohier, M. Gibertini, M. Verstraete, [Remote free-carrier screening to boost the mobility of Fröhlich-limited two-dimensional semiconductors](https://doi.org/10.1103/physrevmaterials.5.024004), _Physical Review Materials_ **5,** no. 024004,  (2021).
+
+
 ### Publications from 2020
 
 - M. Hope, B. Zhang, B. Zhu, D. M. Halat, J. L. MacManus-Driscoll, C. P. Grey, [Probing Interfaces in Complex Oxide Heterostructures via 17O Solid State NMR Spectroscopy](https://doi.org/10.26434/chemrxiv.12288332.v1), _ChemRxiv, Preprint_ (2020).
@@ -84,4 +157,4 @@ A list of publications containing calculations powered by AiiDA, selected from t
 - G. Pizzi, M. Gibertini, E. Dib, N. Marzari, G. Iannaccone, G. Fiori, [Performance of arsenene and antimonene double-gate MOSFETs from first principles](http://doi.org/10.1038/ncomms12585), _Nature Communications_ **7** (2016).
 - M. Gibertini, G. Pizzi, N. Marzari, [Engineering polar discontinuities in honeycomb lattices](http://doi.org/10.1038/ncomms6157), _Nature Communications_ **5** (2014).
 
-Last updated: **March 2021**
+Last updated: **March 2024**

docs/sections/testimonials.md

@@ -35,6 +35,9 @@ researcher at National Institute for Materials Science (NIMS), Japan**
 Literature references
 ---------------------
 
+**Malcolm Sim; The Dynamic Orchestration of Self-Driving Laboratories. Master's thesis, University of Toronto, 2024.** [Availabe from](https://tspace.library.utoronto.ca/bitstream/1807/138140/2/Sim_Malcolm_202403_MSc_thesis.pdf)
+> \[…\] To tackle the computational challenges and ensure reproducibility, ChemOS 2.0 embraces the integration of the AiiDA software package. AiiDA plays a critical role in automating data transfers between the user’s local environment and the high-performance supercomputing cluster. […\] Additionally, AiiDA is prepared for distributed computing, enabling efficient utilization of computational resources.
+
 **Foscato, M.; Jensen, V. R. Automated in Silico Design of Homogeneous Catalysts. ACS Catal. 2020, 10 (3), 2354–2377.** [10.1021/acscatal.9b04952](https://doi.org/10.1021/acscatal.9b04952)
 
 > \[…\] Such reuse and repurposing may be realized by making sure that workflow managers such as AiiDA, QMflows, AFlow, Signac, and FireWorks prepare job summaries in standardized data formats used by the community repositories. The most detailed management control is currently offered by AiiDA which keeps track of the complete history, including information on methods, input parameters, computer, postprocessing tools, and dependencies, leading to a computational result, thereby mapping the complete data provenance necessary to ensure reproducibility and repurposing. \[…\]