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AMaRaNTA: automated first-principles exchange parameters in 2D magnets
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  • Published: 03 March 2026

AMaRaNTA: automated first-principles exchange parameters in 2D magnets

  • Federico Orlando1,2,
  • Andrea Droghetti2,3,
  • Lorenzo Varrassi4,5,
  • Giuseppe Cuono2,
  • Cesare Franchini4,6,
  • Paolo Barone7,
  • Antimo Marrazzo8,
  • Marco Gibertini9,10,
  • Srdjan Stavrić2,11 &
  • …
  • Silvia Picozzi2,12 

npj Computational Materials , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Chemistry
  • Materials science
  • Mathematics and computing
  • Physics

Abstract

Two-dimensional (2D) magnets host a wide range of exotic magnetic textures, whose low-energy excitations and finite-temperature properties are typically described by effective spin models based on Heisenberg-like Hamiltonians. A key challenge in this framework is the reliable determination, from ab initio calculations, of exchange parameters and their anisotropic components, crucial for stabilising long-range order. Among the strategies proposed for this task, the energy-mapping method, based on total-energy calculations within Density Functional Theory (DFT), is the most widely adopted, but typically requires laborious, multi-step procedures. To overcome this limitation, we introduce AMaRaNTA (Automating Magnetic paRAmeters iN a Tensorial Approach), a computational package that systematically automates the energy-mapping method, through its “four-state” formulation, to extract exchange and anisotropy parameters in 2D magnets. In its current implementation, AMaRaNTA returns the nearest-neighbour exchange tensor, complemented by scalar parameters for second- and third-nearest-neighbour exchange interactions as well as single-ion anisotropy. Together, these provide a minimal yet sufficient set of parameters to capture magnetic frustration and anisotropies, essential for stabilising several observed magnetic states in 2D materials. Applied to a representative subset of the Materials Cloud 2D Structure database, AMaRaNTA demonstrates robust and reproducible screening of magnetic interactions, with clear potential for high-throughput simulations.

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Data availability

The dataset generated and analysed in the current study is available in the Supplementary Materials.

Code availability

The underlying code for this study is publicly available at https://github.com/AMaRaNTA-code/AMaRaNTA.

References

  1. Tsubokawa, I. On the Magnetic Properties of a CrBr3 Single Crystal. J. Phys. Soc. Jpn. 15, 1664–1668 (1960).

    Google Scholar 

  2. Dillon, J. F. & Olson, C. E. Magnetization, Resonance, and Optical Properties of the Ferromagnet CrI3. J. Appl. Phys. 36, 1259–1260 (1965).

    Google Scholar 

  3. Huang, B. et al. Layer-dependent ferromagnetism in a van der Waals crystal down to the monolayer limit. Nature 546, 270–273 (2017).

    Google Scholar 

  4. Gong, C. et al. Discovery of intrinsic ferromagnetism in two-dimensional van der Waals crystals. Nature 546, 265–269 (2017).

    Google Scholar 

  5. Wang, X. et al. Raman spectroscopy of atomically thin two-dimensional magnetic iron phosphorus trisulfide (FePS3) crystals. 2D Mater. 3, 031009 (2016).

    Google Scholar 

  6. Lee, J.-U. et al. Ising-Type Magnetic Ordering in Atomically Thin FePS3. Nano Lett. 16, 7433–7438 (2016).

    Google Scholar 

  7. Gong, C. & Zhang, X. Two-dimensional magnetic crystals and emergent heterostructure devices. Science363 (2019).

  8. Gibertini, M., Koperski, M., Morpurgo, A. F. & Novoselov, K. S. Magnetic 2D materials and heterostructures. Nat. Nanotechnol. 14, 408–419 (2019).

    Google Scholar 

  9. Jiang, X. et al. Recent progress on 2D magnets: Fundamental mechanism, structural design and modification. Appl. Phys. Rev.8 (2021).

  10. Wang, Q. H. et al. The Magnetic Genome of Two-Dimensional van der Waals Materials. ACS Nano 16, 6960–7079 (2022).

    Google Scholar 

  11. Song, T. et al. Giant tunneling magnetoresistance in spin-filter van der Waals heterostructures. Science 360, 1214–1218 (2018).

    Google Scholar 

  12. Wang, Z. et al. Tunneling Spin Valves Based on Fe3GeTe2/hBN/Fe3GeTe2 van der Waals Heterostructures. Nano Lett. 18, 4303–4308 (2018).

    Google Scholar 

  13. Zhang, B., Lu, P., Tabrizian, R., Feng, P. X.-L. & Wu, Y. 2D Magnetic heterostructures: spintronics and quantum future. npj Spintronics 2, 1–10 (2024).

    Google Scholar 

  14. Deng, Y. et al. Gate-tunable room-temperature ferromagnetism in two-dimensional Fe3GeTe2. Nature 563, 94–99 (2018).

    Google Scholar 

  15. Zhang, G. et al. Above-room-temperature strong intrinsic ferromagnetism in 2D van der Waals Fe3GaTe2 with large perpendicular magnetic anisotropy. Nat. Commun. 13, 1–8 (2022).

    Google Scholar 

  16. Chen, Z., Yang, Y., Ying, T. & Guo, J. -g High-Tc Ferromagnetic Semiconductor in Thinned 3D Ising Ferromagnetic Metal Fe3GaTe2. Nano Lett. 24, 993–1000 (2024).

    Google Scholar 

  17. Mermin, N. D. & Wagner, H. Absence of Ferromagnetism or Antiferromagnetism in One- or Two-Dimensional Isotropic Heisenberg Models. Phys. Rev. Lett. 17, 1133–1136 (1966).

    Google Scholar 

  18. Irkhin, V. Y., Katanin, A. A. & Katsnelson, M. I. Self-consistent spin-wave theory of layered Heisenberg magnets. Phys. Rev. B 60, 1082–1099 (1999).

    Google Scholar 

  19. Lado, J. L. & Fernández-Rossier, J. On the origin of magnetic anisotropy in two dimensional CrI3. 2D Mater. 4, 035002 (2017).

    Google Scholar 

  20. Sødequist, J. & Olsen, T. Two-dimensional altermagnets from high throughput computational screening: Symmetry requirements, chiral magnons, and spin-orbit effects. Appl. Phys. Lett. 124, 182409 (2024).

    Google Scholar 

  21. Dzyaloshinsky, I. A thermodynamic theory of “weak” ferromagnetism of antiferromagnetics. J. Phys. Chem. Solids 4, 241–255 (1958).

    Google Scholar 

  22. Moriya, T. Anisotropic Superexchange Interaction and Weak Ferromagnetism. Phys. Rev. 120, 91–98 (1960).

    Google Scholar 

  23. Milivojević, M., Orozović, M., Picozzi, S., Gmitra, M. & Stavrić, S. Interplay of altermagnetism and weak ferromagnetism in two-dimensional RuF4. 2D Mater. 11, 035025 (2024).

    Google Scholar 

  24. Rößler, U. K., Bogdanov, A. N. & Pfleiderer, C. Spontaneous skyrmion ground states in magnetic metals. Nature 442, 797–801 (2006).

    Google Scholar 

  25. Yi, S. D., Onoda, S., Nagaosa, N. & Han, J. H. Skyrmions and anomalous Hall effect in a Dzyaloshinskii-Moriya spiral magnet. Phys. Rev. B 80, 054416 (2009).

    Google Scholar 

  26. Heinze, S. et al. Spontaneous atomic-scale magnetic skyrmion lattice in two dimensions. Nat. Phys. 7, 713–718 (2011).

    Google Scholar 

  27. Liu, Y., Yang, B., Guo, X., Picozzi, S. & Yan, Y. Modulation of skyrmion helicity by competition between Dzyaloshinskii-Moriya interaction and magnetic frustration. Phys. Rev. B 109, 094431 (2024).

    Google Scholar 

  28. Zhang, Y. et al. Emergence of skyrmionium in a two-dimensional CrGe(Se, Te)3 Janus monolayer. Phys. Rev. B 102, 241107 (2020).

    Google Scholar 

  29. Xu, C. et al. Topological spin texture in Janus monolayers of the chromium trihalides Cr(I, X)3. Phys. Rev. B 101, 060404 (2020).

    Google Scholar 

  30. Ga, Y. et al. Anisotropic Dzyaloshinskii-Moriya interaction protected by D2d crystal symmetry in two-dimensional ternary compounds. npj Comput. Mater. 8, 1–7 (2022).

    Google Scholar 

  31. Cui, Q. et al. Anisotropic Dzyaloshinskii–Moriya Interaction and Topological Magnetism in Two-Dimensional Magnets Protected by xn–P4m2-hwc Crystal Symmetry. Nano Lett. 22, 2334–2341 (2022).

    Google Scholar 

  32. Liang, J. et al. Very large Dzyaloshinskii-Moriya interaction in two-dimensional Janus manganese dichalcogenides and its application to realize skyrmion states. Phys. Rev. B 101, 184401 (2020).

    Google Scholar 

  33. Moessner, R. & Chalker, J. T. Low-temperature properties of classical geometrically frustrated antiferromagnets. Phys. Rev. B 58, 12049–12062 (1998).

    Google Scholar 

  34. Ramirez, A. P. Strongly Geometrically Frustrated Magnets. Annu. Rev. Mater. Res. 453–480 (1994).

  35. Balents, L. Spin liquids in frustrated magnets. Nature 464, 199–208 (2010).

    Google Scholar 

  36. McGuire, M. A. Crystal and Magnetic Structures in Layered, Transition Metal Dihalides and Trihalides. Crystals 7, 121 (2017).

    Google Scholar 

  37. Rastelli, E., Tassi, A. & Reatto, L. Non-simple magnetic order for simple Hamiltonians. Physica B+C 97, 1–24 (1979).

    Google Scholar 

  38. Schmidt, B. & Thalmeier, P. Frustrated two dimensional quantum magnets. Phys. Rep. 703, 1–59 (2017).

    Google Scholar 

  39. Chakrabartty, D. et al. Role of Competing Magnetic Exchange on Non-Collinear to Collinear Magnetic Ordering and Skyrmion Stabilization in Centrosymmetric Hexagonal Magnets. ACS Nano 19, 3614–3623 (2025).

    Google Scholar 

  40. Amoroso, D., Barone, P. & Picozzi, S. Spontaneous skyrmionic lattice from anisotropic symmetric exchange in a Ni-halide monolayer. Nat. Commun. 11, 1–9 (2020).

    Google Scholar 

  41. Cheong, S.-W. & Mostovoy, M. Multiferroics: a magnetic twist for ferroelectricity. Nat. Mater. 6, 13–20 (2007).

    Google Scholar 

  42. Tokura, Y. & Seki, S. Multiferroics with Spiral Spin Orders. Adv. Mater. 22, 1554–1565 (2010).

    Google Scholar 

  43. Fumega, A. O. & Lado, J. L. Microscopic origin of multiferroic order in monolayer NiI2. 2D Mater. 9, 025010 (2022).

    Google Scholar 

  44. Song, Q. et al. Evidence for a single-layer van der Waals multiferroic. Nature 602, 601–605 (2022).

    Google Scholar 

  45. Kohn, W. Nobel Lecture: Electronic structure of matter—wave functions and density functionals. Rev. Mod. Phys. 71, 1253–1266 (1999).

    Google Scholar 

  46. Oroszlány, L., Ferrer, J., Deák, A., Udvardi, L. & Szunyogh, L. Exchange interactions from a nonorthogonal basis set: From bulk ferromagnets to the magnetism in low-dimensional graphene systems. Phys. Rev. B 99, 224412 (2019).

    Google Scholar 

  47. Korotin, D.mM., Mazurenko, V. V., Anisimov, V. I. & Streltsov, S. V. Calculation of exchange constants of the Heisenberg model in plane-wave-based methods using the Green’s function approach. Phys. Rev. B 91, 224405 (2015).

    Google Scholar 

  48. He, X., Helbig, N., Verstraete, M. J. & Bousquet, E. TB2J: A python package for computing magnetic interaction parameters. Comput. Phys. Commun. 264, 107938 (2021).

    Google Scholar 

  49. Martínez-Carracedo, G. et al. Relativistic magnetic interactions from nonorthogonal basis sets. Phys. Rev. B 108, 214418 (2023).

    Google Scholar 

  50. Zimmermann, B. et al. Comparison of first-principles methods to extract magnetic parameters in ultrathin films: Co/Pt(111). Phys. Rev. B 99, 214426 (2019).

    Google Scholar 

  51. Noodleman, L. Valence bond description of antiferromagnetic coupling in transition metal dimers. J. Chem. Phys. 74, 5737–5743 (1981).

    Google Scholar 

  52. Liechtenstein, A. I., Katsnelson, M. I., Antropov, V. P. & Gubanov, V. A. Local spin density functional approach to the theory of exchange interactions in ferromagnetic metals and alloys. J. Magn. Magn. Mater. 67, 65–74 (1987).

    Google Scholar 

  53. Szilva, A. et al. Quantitative theory of magnetic interactions in solids. Rev. Mod. Phys. 95, 035004 (2023).

    Google Scholar 

  54. Sandratskii, L. M. & Guletskii, P. G. Symmetrised method for the calculation of the band structure of noncollinear magnets. J. Phys. F: Met. Phys. 16, L43 (1986).

    Google Scholar 

  55. Sandratskii, L. M. Symmetry analysis of electronic states for crystals with spiral magnetic order. I. General properties. J. Phys.: Condens. Matter 3, 8565 (1991).

    Google Scholar 

  56. Mounet, N. et al. Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds. Nat. Nanotechnol. 13, 246–252 (2018).

    Google Scholar 

  57. Haastrup, S. et al. The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals. 2D Mater. 5, 042002 (2018).

    Google Scholar 

  58. Torelli, D., Moustafa, H., Jacobsen, K. W. & Olsen, T. High-throughput computational screening for two-dimensional magnetic materials based on experimental databases of three-dimensional compounds. npj Comput. Mater. 6, 1–12 (2020).

    Google Scholar 

  59. Gjerding, M. N. et al. Recent progress of the Computational 2D Materials Database (C2DB). 2D Mater. 8, 044002 (2021).

    Google Scholar 

  60. Sødequist, J. & Olsen, T. Type II multiferroic order in two-dimensional transition metal halides from first principles spin-spiral calculations. 2D Mater. 10, 035016 (2023).

    Google Scholar 

  61. Xiang, H., Lee, C., Koo, H.-J., Gong, X. & Whangbo, M.-H. Magnetic properties and energy-mapping analysis. Dalton Trans. 42, 823–853 (2012).

    Google Scholar 

  62. Li, X. et al. Spin Hamiltonians in Magnets: Theories and Computations. Molecules 26, 803 (2021).

    Google Scholar 

  63. Xiang, H. J., Kan, E. J., Wei, S.-H., Whangbo, M.-H. & Gong, X. G. Predicting the spin-lattice order of frustrated systems from first principles. Phys. Rev. B 84, 224429 (2011).

    Google Scholar 

  64. Xu, C., Feng, J., Xiang, H. & Bellaiche, L. Interplay between Kitaev interaction and single ion anisotropy in ferromagnetic CrI3 and CrGeTe3 monolayers. npj Comput. Mater. 4, 1–6 (2018).

    Google Scholar 

  65. Xu, C. et al. Possible Kitaev Quantum Spin Liquid State in 2D Materials with S = 3/2. Phys. Rev. Lett. 124, 087205 (2020).

    Google Scholar 

  66. Huber, S. P. et al. AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance. Sci. Data 7, 1–18 (2020).

    Google Scholar 

  67. Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993).

    Google Scholar 

  68. Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996).

    Google Scholar 

  69. Campi, D., Mounet, N., Gibertini, M., Pizzi, G. & Marzari, N. Expansion of the Materials Cloud 2D Database. ACS Nano 17, 11268–11278 (2023).

    Google Scholar 

  70. Kitaev, A. Anyons in an exactly solved model and beyond. Ann. Phys. 321, 2–111 (2006).

    Google Scholar 

  71. Rau, J. G., Lee, E. K.-H. & Kee, H.-Y. Generic Spin Model for the Honeycomb Iridates beyond the Kitaev Limit. Phys. Rev. Lett. 112, 077204 (2014).

    Google Scholar 

  72. Menichetti, G., Calandra, M. & Polini, M. Electronic structure and magnetic properties of few-layer Cr2Ge2Te6: the key role of nonlocal electron–electron interaction effects. 2D Mater. 6, 045042 (2019).

    Google Scholar 

  73. Uhrin, M., Huber, S. P., Yu, J., Marzari, N. & Pizzi, G. Workflows in AiiDA: Engineering a high-throughput, event-based engine for robust and modular computational workflows. Comput. Mater. Sci. 187, 110086 (2021).

    Google Scholar 

  74. Larsen, A. H. et al. The atomic simulation environment — a Python library for working with atoms. J. Phys.: Condens. Matter 29, 273002 (2017).

    Google Scholar 

  75. Zhuang, H. L., Xie, Y., Kent, P. R. C. & Ganesh, P. Computational discovery of ferromagnetic semiconducting single-layer CrSnTe3. Phys. Rev. B 92, 035407 (2015).

    Google Scholar 

  76. Chittari, B. L. et al. Electronic and magnetic properties of single-layer MPX3 metal phosphorous trichalcogenides. Phys. Rev. B 94, 184428 (2016).

    Google Scholar 

  77. Yang, K., Ning, Y., Ma, Y., Zhou, Y. & Wu, H. Contrasting magnetism in VPS3 and CrI3 monolayers with the common honeycomb S = 3/2 spin lattice. Phys. Rev. B 111, 134421 (2025).

    Google Scholar 

  78. Liu, C. et al. Probing the Néel-Type Antiferromagnetic Order and Coherent Magnon–Exciton Coupling in Van Der Waals VPS3. Adv. Mater. 35, 2300247 (2023).

    Google Scholar 

  79. Riedl, K. et al. Microscopic origin of magnetism in monolayer 3d transition metal dihalides. Phys. Rev. B 106, 035156 (2022).

    Google Scholar 

  80. Gu, Y. et al. Ni-based transition metal trichalcogenide monolayer: A strongly correlated quadruple-layer graphene. Phys. Rev. B 100, 165405 (2019).

    Google Scholar 

  81. Bazazzadeh, N. et al. Symmetry enhanced spin-Nernst effect in honeycomb antiferromagnetic transition metal trichalcogenide monolayers. Phys. Rev. B 103, 014425 (2021).

    Google Scholar 

  82. Basnet, R. et al. Controlling magnetic exchange and anisotropy by nonmagnetic ligand substitution in layered MPX3 (M = Ni, Mn; X = S, Se). Phys. Rev. Res. 4, 023256 (2022).

    Google Scholar 

  83. Peng, C. et al. Kitaev physics in the two-dimensional magnet NiPSe3. Phys. Rev. Res. 6, 033206 (2024).

    Google Scholar 

  84. Yang, J. et al. Zigzag antiferromagnetic property of two-dimensional NiPX3 (X = S/Se) monolayers in their pristine structure and Janus phase. RSC Adv. 15, 23115–23123 (2025).

    Google Scholar 

  85. Autieri, C. et al. Limited Ferromagnetic Interactions in Monolayers of MPS3 (M = Mn and Ni). J. Phys. Chem. C 126, 6791–6802 (2022).

    Google Scholar 

  86. Olsen, T. Magnetic anisotropy and exchange interactions of two-dimensional FePS3, NiPS3 and MnPS3 from first principles calculations. J. Phys. D: Appl. Phys. 54, 314001 (2021).

    Google Scholar 

  87. Zhang, D. et al. Topological Axion States in the Magnetic Insulator MnBi2Te4 with the Quantized Magnetoelectric Effect. Phys. Rev. Lett. 122, 206401 (2019).

    Google Scholar 

  88. Li, Y., Jiang, Z., Li, J., Xu, S. & Duan, W. Magnetic anisotropy of the two-dimensional ferromagnetic insulator MnBi2Te4. Phys. Rev. B 100, 134438 (2019).

    Google Scholar 

  89. Otrokov, M. M. et al. Prediction and observation of an antiferromagnetic topological insulator. Nature 576, 416–422 (2019).

    Google Scholar 

  90. Li, B. et al. Competing Magnetic Interactions in the Antiferromagnetic Topological Insulator MnBi2Te4. Phys. Rev. Lett. 124, 167204 (2020).

    Google Scholar 

  91. Yang, B., Han, X. & Picozzi, S. Emergence of topological bimerons in monolayer CrSBr. Phys. Rev. Mater. 9, 064003 (2025).

    Google Scholar 

  92. Kruse, M. et al. Two-dimensional ferroelectrics from high throughput computational screening. npj Comput. Mater. 9, 1–11 (2023).

    Google Scholar 

  93. Priessnitz, J. & Legut, D. OstravaJ: a tool for calculating magnetic exchange interactions via DFT. arXiv: 2501.08251 (2025).

  94. Wan, G. et al. Sym4state.jl: An efficient computation package for magnetic materials. Comput. Phys. Commun. 303, 109283 (2024).

    Google Scholar 

  95. Lou, F. et al. PASP: Property analysis and simulation package for materials. J. Chem. Phys. 154, 114103 (2021).

    Google Scholar 

  96. Wang, B. et al. Prediction of a two-dimensional high-TC f-electron ferromagnetic semiconductor. Mater. Horiz. 7, 1623–1630 (2020).

    Google Scholar 

  97. Liu, Q. et al. Surprising pressure-induced magnetic transformations from helimagnetic order to antiferromagnetic state in NiI2. Nat. Commun. 16, 1–8 (2025).

    Google Scholar 

  98. Orozović, M., Šoškić, B. N., Picozzi, S., Šljivančanin, Ž & Stavrić, S. Hole doping as an efficient route to increase the Curie temperature in monolayer CrI3. 2D Mater. 12, 045025 (2025).

    Google Scholar 

  99. Abuawwad, N., Dias, M.dS., Abusara, H. & Lounis, S. CrTe2 as a two-dimensional material for topological magnetism in complex heterobilayers. Phys. Rev. B 108, 094409 (2023).

    Google Scholar 

  100. Ni, J. Y. et al. Giant Biquadratic Exchange in 2D Magnets and Its Role in Stabilizing Ferromagnetism of NiCl2 Monolayers. Phys. Rev. Lett. 127, 247204 (2021).

    Google Scholar 

  101. Li, X. et al. Realistic Spin Model for Multiferroic NiI2. Phys. Rev. Lett. 131, 036701 (2023).

    Google Scholar 

  102. Xiang, H. J., Kan, E. J., Zhang, Y., Whangbo, M.-H. & Gong, X. G. General Theory for the Ferroelectric Polarization Induced by Spin-Spiral Order. Phys. Rev. Lett. 107, 157202 (2011).

    Google Scholar 

  103. Edström, A., Barone, P., Picozzi, S. & Stengel, M. Magnetoelectricity of topological solitons in 2D magnets. npj Comput. Mater. 11, 295 (2025).

    Google Scholar 

  104. Cococcioni, M. & de Gironcoli, S. Linear response approach to the calculation of the effective interaction parameters in the LDA+U method. Phys. Rev. B 71, 035105 (2005).

    Google Scholar 

  105. Aryasetiawan, F., Karlsson, K., Jepsen, O. & Schönberger, U. Calculations of Hubbard U from first-principles. Phys. Rev. B 74, 125106 (2006).

    Google Scholar 

  106. Archer, T. et al. Exchange interactions and magnetic phases of transition metal oxides: Benchmarking advanced ab initio methods. Phys. Rev. B 84, 115114 (2011).

    Google Scholar 

  107. Desmarais, J. K., Flament, J.-P. & Erba, A. Spin-orbit coupling from a two-component self-consistent approach. II. Non-collinear density functional theories. J. Chem. Phys. 151, 074108 (2019).

    Google Scholar 

  108. Blöchl, P. E. Projector augmented-wave method. Phys. Rev. B 50, 17953–17979 (1994).

    Google Scholar 

  109. Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999).

    Google Scholar 

  110. Liechtenstein, A. I., Anisimov, V. I. & Zaanen, J. Density-functional theory and strong interactions: Orbital ordering in Mott-Hubbard insulators. Phys. Rev. B 52, R5467–R5470 (1995).

    Google Scholar 

  111. Lançon, D., Ewings, R. A., Guidi, T., Formisano, F. & Wildes, A. R. Magnetic exchange parameters and anisotropy of the quasi-two-dimensional antiferromagnet NiPS3. Phys. Rev. B 98, 134414 (2018).

    Google Scholar 

  112. Musari, A. A. & Kratzer, P. Lattice dynamics, elastic, magnetic, thermodynamic and thermoelectric properties of the two-dimensional semiconductors MPSe3 (M = Cd, Fe and NI): a first-principles study. Mater. Res. Express 9, 106302 (2022).

    Google Scholar 

  113. Sun, H. et al. Coexistence of zigzag antiferromagnetic order and superconductivity in compressed NiPSe3. Materials Today Physics 36, 101188 (2023).

    Google Scholar 

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Acknowledgements

The authors acknowledge (in alphabetical order) Jakob Baumsteiger, Guido Menichetti, Lei Qiao, Alessandro Stroppa, and Cesare Tresca for useful discussions. The necessary structure files for the dataset generation were provided as a courtesy by Davide Campi. The work was funded by the European Union—NextGenerationEU, through the ICSC-Centro Nazionale di Ricerca in High-Performance Computing, Big Data and Quantum Computing (Grant No. CN00000013, CUP J93C22000540006, PNRR Investimento M4.C2.1.4). A.M. and M.G. acknowledge partial support from the PRIN Project “Simultaneous electrical control of spin and valley polarisation in van der Waals magnetic materials” (SECSY–CUP Grant Nos. E53D23001700006 and J53D23001400001, PNRR Investimento M4.C2.1.1), which is funded by the European Union—NextGenerationEU. S.P. acknowledges partial support from the PRIN Project “SORBET—Spin-orbit effects in two-dimensional magnets” (IT-MIUR Grant No. 2022ZY8HJY) within NextGenerationEU. S.P., A.D. and G.C. acknowledge partial support from PNRR Partenariato PE4 “National Quantum Science and Technology Institute” (NQSTI) project PE0000023 (CUP B53C22004180005), the CANVAS project (CUP B53C22005670005), funded by the Italian Ministry of the Environment and the Energy Security and the National Innovation Ecosystem VITALITY (Grant No. ECS00000041, CUP B43C22000470005). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them. S.S. acknowledges financial support from the Vinča Institute, provided by the Ministry of Science, Technological Development, and Innovation of the Republic of Serbia. S.S., P.B., A.D., G.C. and S.P. acknowledge additional funding from the Ministry of Foreign Affairs of Italy and the Ministry of Science, Technological Development, and Innovation of Serbia through the bilateral project “Van der Waals Heterostructures for Altermagnetic Spintronic”, realised under the executive programme for scientific and technological cooperation between the two countries.We acknowledge the CINECA award under the ISCRA initiative (project ISCRA-B HP10BA00W3), for the availability of high-performance computing resources and support.

Author information

Authors and Affiliations

  1. Physics Department - Politecnico di Milano, p.za Leonardo da Vinci 32, 20133, Milan, Italy

    Federico Orlando

  2. Consiglio Nazionale delle Ricerche CNR-SPIN, c/o Universitá degli Studi “G. D’Annunzio”, 66100, Chieti, Italy

    Federico Orlando, Andrea Droghetti, Giuseppe Cuono, Srdjan Stavrić & Silvia Picozzi

  3. Department of Molecular Sciences and Nanosystems, Ca’ Foscari University of Venice, via Torino 155, 30170, Mestre-Venice, Italy

    Andrea Droghetti

  4. Dipartimento di Fisica e Astronomia, Universitá di Bologna, 40127, Bologna, Italy

    Lorenzo Varrassi & Cesare Franchini

  5. CINECA National Supercomputing Center, Casalecchio di Reno, I-40033, Bologna, Italy

    Lorenzo Varrassi

  6. University of Vienna, Faculty of Physics and Center for Computational Materials Science, Kolingasse 14-16, Vienna, Austria

    Cesare Franchini

  7. Consiglio Nazionale delle Ricerche CNR-SPIN, Area della Ricerca di Tor Vergata, 00133, Rome, Italy

    Paolo Barone

  8. Scuola Internazionale Superiore di Studi Avanzati (SISSA), 34136, Trieste, Italy

    Antimo Marrazzo

  9. Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Universitá di Modena e Reggio Emilia, Via Campi 213/a, 41125, Modena, Italy

    Marco Gibertini

  10. Centro S3, Istituto Nanoscienze-CNR, Via Campi 213/a, 41125, Modena, Italy

    Marco Gibertini

  11. Vinča Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, P. O. Box 522, RS-11001, Belgrade, Serbia

    Srdjan Stavrić

  12. Department of Materials Science, University of Milan - Bicocca, 20125, Milan, Italy

    Silvia Picozzi

Authors
  1. Federico Orlando
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  2. Andrea Droghetti
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  3. Lorenzo Varrassi
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  4. Giuseppe Cuono
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  5. Cesare Franchini
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  6. Paolo Barone
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  7. Antimo Marrazzo
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  8. Marco Gibertini
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  9. Srdjan Stavrić
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  10. Silvia Picozzi
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Contributions

F.O. software preparation, execution, supervision, data analysis, writing—original draft; A.D. execution, supervision, writing—original draft; L.V., C.F. software preparation; G.C. execution; P.B. supervision; A.M., M.G. conceptualisation, supervision; S.S. conceptualisation, software preparation; S.P. conceptualisation, supervision. All authors participated in the revision and editing of the manuscript and approved the final version.

Corresponding author

Correspondence to Federico Orlando.

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Competing interests

The authors declare no competing interests.

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Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Cite this article

Orlando, F., Droghetti, A., Varrassi, L. et al. AMaRaNTA: automated first-principles exchange parameters in 2D magnets. npj Comput Mater (2026). https://doi.org/10.1038/s41524-026-01968-4

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  • Received: 12 September 2025

  • Accepted: 11 January 2026

  • Published: 03 March 2026

  • DOI: https://doi.org/10.1038/s41524-026-01968-4

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