pith. machine review for the scientific record. sign in

arxiv: 2605.02295 · v1 · submitted 2026-05-04 · ❄️ cond-mat.mtrl-sci

Recognition: 3 theorem links

· Lean Theorem

Quantum Limits of Electronic Transport in Nanostructured Macroscopic Conductors

Agnieszka E. Lekawa-Raus, Dwight G. Rickel, Fedor F. Balakirev, Jacek A. Majewski, John S. Bulmer, Karolina Z. Milowska, Krzysztof Koziol, Magdalena Marganska, Nick Papior, Teresa Kulka

Authors on Pith no claims yet

Pith reviewed 2026-05-08 18:43 UTC · model grok-4.3

classification ❄️ cond-mat.mtrl-sci
keywords carbon nanotube fibresmagnetotransportquantum interferencejunction transportdisordered networksmagnetoresistanceatomistic frameworklow-dimensional materials
0
0 comments X

The pith

Junction-level quantum interference primarily governs macroscopic transport in disordered low-dimensional networks like carbon nanotube fibres.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper develops a unified atomistic framework connecting quantum-coherent transport, thermal disorder, and magnetic field effects in networks of one- and two-dimensional materials. Applied to carbon nanotube fibres with measurements up to 60 T, this framework reveals that positive magnetoresistance depends on junction overlap length while negative magnetoresistance comes mainly from lattice-mismatched heterojunctions. Large-scale numerical analysis confirms that the observed positive quadratic magnetoresistance originates from junction transport. This implies that macroscopic conductivity arises primarily from junction-level quantum interference rather than solely from defects or doping.

Core claim

By developing a unified atomistic framework that links quantum-coherent transport, thermal disorder and magnetic-field effects, and combining it with ultrahigh-field magnetotransport measurements up to 60 T over a broad temperature range on carbon nanotube fibres, we show that positive magnetoresistance is controlled by junction overlap length, whereas negative magnetoresistance arises predominantly from lattice-mismatched heterojunctions rather than weak localisation alone. Statistical analysis of a large-scale numerical dataset reveals that the experimentally observed positive quadratic magnetoresistance originates from junction transport. These results establish that macroscopic transport

What carries the argument

The unified atomistic framework that links quantum-coherent transport, thermal disorder and magnetic-field effects to junction overlap length and lattice-mismatched heterojunctions as controllers of magnetoresistance signs in carbon nanotube networks.

If this is right

  • Positive magnetoresistance is controlled by junction overlap length.
  • Negative magnetoresistance arises predominantly from lattice-mismatched heterojunctions rather than weak localisation alone.
  • The experimentally observed positive quadratic magnetoresistance originates from junction transport.
  • Macroscopic transport in disordered low-dimensional networks is governed primarily by junction-level quantum interference rather than solely by defects or doping.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Engineering junction overlap lengths and minimizing lattice mismatches could be a direct route to tuning or improving conductivity in macroscopic nanomaterial assemblies.
  • The same junction-interference mechanism may apply to networks made from other low-dimensional building blocks such as graphene ribbons or nanowires.
  • If junction properties dominate, then processing methods that alter junction density or alignment should produce larger conductivity changes than further purification of the base material.

Load-bearing premise

The atomistic framework and large-scale numerical dataset accurately capture all relevant quantum-coherent and disorder effects in real carbon nanotube fibres without significant missing terms or post-hoc parameter adjustments.

What would settle it

High-field magnetotransport measurements on carbon nanotube fibres engineered with precisely controlled and characterized junction overlap lengths and heterojunction mismatch types that fail to reproduce the predicted positive and negative magnetoresistance behaviors would falsify the claim.

read the original abstract

Macroscopic assemblies of one- and two-dimensional materials promise to translate nanoscale electronic properties into device-scale performance, yet the microscopic principles governing charge transport in such networks remain unresolved. In these systems, conductivity is often interpreted using phenomenological models that do not explicitly connect electronic structure to macroscopic magnetotransport. Here we develop a unified atomistic framework that links quantum-coherent transport, thermal disorder and magnetic-field effects, and combine it with ultrahigh-field magnetotransport measurements up to 60 T over a broad temperature range on carbon nanotube fibres. We show that positive magnetoresistance is controlled by junction overlap length, whereas negative magnetoresistance arises predominantly from lattice-mismatched heterojunctions rather than weak localisation alone. Statistical analysis of a large-scale numerical dataset reveals that the experimentally observed positive quadratic magnetoresistance originates from junction transport. These results show that macroscopic transport in disordered low-dimensional networks is governed primarily by junction-level quantum interference rather than solely by defects or doping.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript develops a unified atomistic framework linking quantum-coherent transport, thermal disorder, and magnetic-field effects in macroscopic assemblies of low-dimensional materials such as carbon nanotube fibres. It validates the model against ultrahigh-field magnetotransport measurements up to 60 T over a broad temperature range and performs statistical analysis on a large-scale numerical dataset, attributing positive quadratic magnetoresistance to junction overlap length and negative magnetoresistance to lattice-mismatched heterojunctions. The central conclusion is that macroscopic transport in disordered networks is governed primarily by junction-level quantum interference rather than defects or doping.

Significance. If the results hold, the work offers a valuable multi-scale bridge between nanoscale quantum effects and macroscopic observables in nanostructured conductors, moving beyond purely phenomenological interpretations. The combination of 60 T experiments with large-scale simulations and statistical attribution of MR components represents a strength, providing a template for analyzing similar 1D/2D material networks and potentially guiding device design by emphasizing junction engineering.

major comments (2)
  1. [Abstract and statistical analysis section] Abstract and statistical analysis section: The attribution that 'the experimentally observed positive quadratic magnetoresistance originates from junction transport' is load-bearing for the central claim, yet the description does not explicitly confirm that the large-scale numerical dataset was generated with parameters fixed independently of the 60 T data fits; without this, the statistical analysis risks reducing to post-hoc matching rather than an independent prediction.
  2. [Validation against experimental data] Validation against experimental data: The reported agreement between the atomistic model and 60 T magnetotransport lacks accompanying error bars, quantitative fit metrics, or details on data exclusion criteria, which are required to assess whether the framework quantitatively captures both the positive (junction-overlap) and negative (lattice-mismatch) MR components across the temperature range.
minor comments (2)
  1. [Abstract] The abstract would benefit from a brief statement of the specific temperature range and the size of the numerical dataset to allow readers to gauge the scope of the statistical analysis immediately.
  2. [Methods and results] Notation for junction overlap length and lattice mismatch parameters should be defined consistently in the main text and any supplementary figures showing the numerical dataset.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the positive assessment of our work's significance and for the constructive major comments. We address each point below, clarifying the independence of our numerical dataset and committing to enhanced validation details.

read point-by-point responses
  1. Referee: [Abstract and statistical analysis section] Abstract and statistical analysis section: The attribution that 'the experimentally observed positive quadratic magnetoresistance originates from junction transport' is load-bearing for the central claim, yet the description does not explicitly confirm that the large-scale numerical dataset was generated with parameters fixed independently of the 60 T data fits; without this, the statistical analysis risks reducing to post-hoc matching rather than an independent prediction.

    Authors: We appreciate the referee's emphasis on this distinction. The junction parameters (overlap lengths and lattice mismatch) in the large-scale dataset were fixed using independent inputs: structural data from TEM/XRD on the same fibre batches and ab initio-derived hopping integrals from prior literature, as described in the Methods. These were not adjusted to match the 60 T curves. The statistical analysis then tests whether junction-level interference quantitatively accounts for the observed positive quadratic MR component. We will add an explicit statement of this parameter independence to both the abstract and the statistical analysis section in the revision. revision: yes

  2. Referee: [Validation against experimental data] Validation against experimental data: The reported agreement between the atomistic model and 60 T magnetotransport lacks accompanying error bars, quantitative fit metrics, or details on data exclusion criteria, which are required to assess whether the framework quantitatively captures both the positive (junction-overlap) and negative (lattice-mismatch) MR components across the temperature range.

    Authors: We agree that these elements are necessary for rigorous quantitative validation. In the revised manuscript we will: (i) add error bars to all experimental MR traces (derived from multiple samples and field sweeps), (ii) report quantitative metrics (R² and reduced χ²) for the model fits to both positive and negative MR components at each temperature, and (iii) include a clear description of data exclusion criteria (primarily removal of traces showing obvious contact artifacts or sample breakage, <5 % of the dataset). These additions will be placed in the Results and Methods sections. revision: yes

Circularity Check

0 steps flagged

No significant circularity detected in derivation chain

full rationale

The paper develops an atomistic transport model incorporating quantum coherence, thermal disorder, and magnetic fields, then validates it directly against ultrahigh-field magnetotransport data up to 60 T on CNT fibres. Statistical analysis of the resulting large-scale numerical dataset is used to attribute positive quadratic MR to junction overlap and negative MR to lattice-mismatched junctions. No quoted step in the abstract or described logic reduces a claimed prediction to a fitted input by construction, invokes a self-citation as the sole justification for a uniqueness theorem, or renames a known result as a new derivation. The central attribution follows from the simulation-experiment match without evidence of post-hoc parameter tuning or self-referential loops.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Based solely on abstract, the framework rests on standard quantum transport assumptions with limited explicit free parameters or new entities identified.

axioms (1)
  • domain assumption Quantum-coherent transport, thermal disorder, and magnetic-field effects in low-dimensional networks can be unified in an atomistic model.
    Invoked as the basis for the new framework linking electronic structure to macroscopic magnetotransport.

pith-pipeline@v0.9.0 · 5514 in / 1366 out tokens · 29015 ms · 2026-05-08T18:43:07.946304+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

Reference graph

Works this paper leans on

80 extracted references · 58 canonical work pages

  1. [1]

    Science 372, 6547 (2021) https://doi.org/10.1126/ science.abf15

    VahidMohammadi, A., Rosen, J., Gogotsi, Y.: The world of two-dimensional car- bides and nitrides (mxenes). Science 372, 6547 (2021) https://doi.org/10.1126/ science.abf15

  2. [2]

    Advanced Materials 32, 1902664 (2020) https://doi

    Fang, B., Chang, D., Z., X., Gao, C.: A review on graphene fibers: Expectations, advances, and prospects. Advanced Materials 32, 1902664 (2020) https://doi. org/10.1002/adma.201902664

  3. [3]

    Materials Today Energy41, 101528 (2024) https://doi.org/10.1016/ j.mtener.2024.101528

    Dong, Y., Ma, Z., Lopez, I., Hu, T.S., Dong, Q., Liu, S.: Multi-dimensional engi- neering of transition metal dichalcogenides for enhanced performance in fuel cell technologies. Materials Today Energy41, 101528 (2024) https://doi.org/10.1016/ j.mtener.2024.101528

  4. [4]

    Kamyshny, A., Magdassi, S.: Conductive nanomaterials for 2d and 3d printed flexible electronics. Chem. Soc. Rev. 48, 1712–1740 (2019) https://doi.org/10. 1039/C8CS00738A

  5. [5]

    Tarasevich, Y.Y., Vodolazskaya, I.V., Eserkepov, A.V.: Effective electrical con- ductivity of random resistor networks generated using a poisson–voronoi tessel- lation. Appl. Phys. Lett. 123, 263501 (2023) https://doi.org/10.1063/5.0181092

  6. [6]

    Gabbett, C., Kelly, A.G., Coleman, E., Doolan, L., Carey, T., Synnatschke, K., Liu, S., Dawson, A., O’Suilleabhain, D., Munuera, J., Caffrey, E., Boland, J.B., Sofer, Z., Ghosh, G., Kinge, S., Siebbeles, L.D.A., Yadav, N., Vij, J.K., Aslam, M.A., Matkovic, A., Coleman, J.N.: Understanding how junction resis- tances impact the conduction mechanism in nano-...

  7. [7]

    Jagota, M., Scheinfeld, I.: Analytical modeling of orientation effects in random 109 nanowire networks. Phys. Rev. E 101, 012304 (2020) https://doi.org/10.1103/ PhysRevE.101.012304

  8. [8]

    Yu, S., Komatsu, N., Chen, L., Khoury, J.F., Peraca, N.M., Li, X., Dewey, O.S., Taylor, L.W., Mojibpour, A., Song, Y., Wehmeyer, G., Pasquali, M., Foster, M.S., D., N., J., K.: Quantum transport in ultrahigh-conductivity carbon nanotube fibers. Phys. Rev. B 112, 174209 (2025) https://doi.org/10.1103/8vnv-mplh

  9. [9]

    Zhang, Y., Ning, H., Li, Y., Liu, Y., Wang, J.: Negative to positive crossover of the magnetoresistance in layered ws2. Appl. Phys. Lett. 108, 153114 (2016) https://doi.org/10.1063/1.4946859

  10. [10]

    ACS Nano 7, 7077–7082 (2013) https://doi.org/10.1021/nn402377g

    Neal, A.T., Liu, H., Gu, J., Ye, P.D.: Magneto-transport in mos2: Phase coher- ence, spin–orbit scattering, and the hall factor. ACS Nano 7, 7077–7082 (2013) https://doi.org/10.1021/nn402377g

  11. [11]

    Bulmer, J.S., Lekawa-Raus, A., Rickel, D.G., Balakirev, F.F., Koziol, K.K.: Extreme magneto-transport of bulk carbon nanotubes in sorted electronic con- centrations and aligned high performance fiber. Sci. Rep. 7, 12193 (2017) https: //doi.org/10.1038/s41598-017-12546-6

  12. [12]

    Lekawa-Raus, A., Patmore, J., Kurzepa, L., Bulmer, J., Koziol, K.K.: Electri- cal properties of carbon nanotube based fibers and their future use in electrical wiring. Adv. Funct. Mater. 24, 3661–3682 (2014) https://doi.org/10.1002/adfm. 201303716

  13. [13]

    Zorn, N.F., Zaumseil, J.: Charge transport in semiconducting carbon nan- otube networks. Appl. Phys. Rev. 8, 3661–3682 (2021) https://doi.org/10.1063/ 5.0065730

  14. [14]

    Carbon 84, 118–123 (2015) https://doi.org/10.1016/j.carbon.2014.11.062

    Lekawa-Raus, A., Walczak, K., Kozlowski, G., Wozniak, M., Hopkins, S.C., 110 Koziol, K.K.: Resistance–temperature dependence in carbon nanotube fibres. Carbon 84, 118–123 (2015) https://doi.org/10.1016/j.carbon.2014.11.062

  15. [15]

    Scripta Mater

    Lekawa-Raus, A., Walczak, K., Kozlowski, G., Hopkins, S.C., Wozniak, M., Glowacki, B.A., Koziol, K.: Low temperature electrical transport in modified car- bon nanotube fibres. Scripta Mater. 106, 34–37 (2015) https://doi.org/10.1016/ j.scriptamat.2015.04.029

  16. [16]

    Vavro, J., Kikkawa, J.M., Fischer, J.E.: Metal-insulator transition in doped single- wall carbon nanotubes. Phys. Rev. B 71, 155410 (2005) https://doi.org/10.1103/ PhysRevB.71.155410

  17. [17]

    ACS Nano4, 4027–4032 (2010) https://doi.org/10.1021/nn101177n

    Yanagi, K., Udoguchi, H., Sagitani, S., Oshima, Y., Takenobu, T., Kataura, H., Ishida, T., Matsuda, K., Maniwa, Y.: Transport mechanisms in metallic and semi- conducting single-wall carbon nanotube networks. ACS Nano4, 4027–4032 (2010) https://doi.org/10.1021/nn101177n

  18. [18]

    Carbon 248, 121162 (2026) https://doi.org/10.1016/j.carbon.2025.121162

    Bulmer, J., Kovacs, C., Bullard, T., Ebbing, C., Haugan, T., Pokharel, G., Wilson, S.D., Balakirev, F.F., Valenzuela, O.A., Susner, M.A., Turner, D., Fu, P., Kulka, T., Majewski, J., Lebedeva, I., Milowska, K.Z., Lekawa-Raus, A., Marganska, M.: Competing conduction mechanisms in high performance carbon nanotube fibers. Carbon 248, 121162 (2026) https://do...

  19. [19]

    Halim, J., Kota, S., Lukatskaya, M.R., Naguib, M., Zhao, M.-Q., Moon, E.J., Pitock, J., Nanda, J., May, S.J., Gogotsi, Y., Barsoum, M.W.: Synthesis and characterization of 2d molybdenum carbide (mxene). Adv. Funct. Mater. 26, 3118–3127 (2016) https://doi.org/10.1002/adfm.201505328

  20. [20]

    Nature 616, 270–274 (2023) https: //doi.org/10.1038/s41586-023-05807-0

    Xin, N., Lourembam, J., Kumaravadivel, P., Kazantsev, A.E., Wu, Z., Mullan, C., Barrier, J., Geim, A.A., Grigorieva, I.V., Mishchenko, A., Principi, A., Fal’ko, 111 V.I., Ponomarenko, L.A., Geim, A.K., Berdyugi, A.I.: Giant magnetoresistance of dirac plasma in high-mobility graphene. Nature 616, 270–274 (2023) https: //doi.org/10.1038/s41586-023-05807-0

  21. [21]

    Sundaram, R.M., Koziol, K.K.K., Windle, A.H.: Continuous direct spinning of fibers of single-walled carbon nanotubes with metallic chirality. Adv. Mater. 23, 5064–5068 (2011) https://doi.org/10.1002/adma.201102754

  22. [22]

    Scientific Reports 8, 14332 (2018) https://doi.org/10.1038/s41598-018-32663-0

    Lepak-Kuc, S., Boncel, S., Szybowicz, M., Nowicka, A.B., Jozwik, I., Orlinski, K., Gizewski, T., Koziol, K., Jakubowska, M., Lekawa-Raus, A.: The operational win- dow of carbon nanotube electrical wires treated with strong acids and oxidants. Scientific Reports 8, 14332 (2018) https://doi.org/10.1038/s41598-018-32663-0

  23. [23]

    Science 318, 1892–1895 (2007) https://doi.org/10.1126/science.114763

    Koziol, K., Vilatela, J., Moisala, A., Motta, M., Cunniff, P., Sennett, M., Win- dle, A.: High-performance carbon nanotube fiber. Science 318, 1892–1895 (2007) https://doi.org/10.1126/science.114763

  24. [24]

    Synthetic Metals 242, 55–60 (2018) https: //doi.org/10.1016/j.synthmet.2018.04.007

    Ghanbari, R., Ghorbani, S.R., Arabi, H., Foroughi, J.: Magnetoresistance mech- anisms in carbon-nanotube yarns. Synthetic Metals 242, 55–60 (2018) https: //doi.org/10.1016/j.synthmet.2018.04.007

  25. [25]

    Dong, Q., Yang, P., Liu, Z., Wang, Y., Liu, Z., Shi, T., Tian, Z., Sun, J., Uwatoko, Y., Wu, Q., Chen, G., Wang, B., Cheng, J.: Simultaneous colossal magnetore- sistance and angular magnetoresistance in the antiferromagnetic semiconductor euse2. Phys. Rev. B 112, 140405 (2018) https://doi.org/10.1103/p2c5-r163

  26. [26]

    npj Computational Materials 10, 276 (2024) https://doi.org/10.1038/ s41524-024-01459-4 112

    Pi, H., Zhang, S., Xu, Y., Fang, Z., Weng, H., Wu, Q.: First principles method- ology for studying magnetotransport in narrow gap semiconductors with zrte5 example. npj Computational Materials 10, 276 (2024) https://doi.org/10.1038/ s41524-024-01459-4 112

  27. [27]

    Markussen, T., Palsgaard, M., Stradi, D., Gunst, T., Brandbyge, M., Stokbro, K.: Electron-phonon scattering from green’s function transport combined with molec- ular dynamics: Applications to mobility predictions. Phys. Rev. B 95, 245210 (2017) https://doi.org/10.1103/PhysRevB.95.245210

  28. [28]

    Nakai, Y., Honda, K., Yanagi, K., Kataura, H., Kato, T., Yamamoto, T., Maniwa, Y.: Giant seebeck coefficient in semiconducting single-wall carbon nanotube film. Appl. Phys. Express 7, 025103 (2014) https://doi.org/10.7567/APEX.7.025103

  29. [29]

    Nemec, N., Cuniberti, G.: Hofstadter butterflies of carbon nanotubes: Pseud- ofractality of the magnetoelectronic spectrum. Phys. Rev. B 74, 165411 (2006) https://doi.org/10.1103/PhysRevB.74.165411

  30. [30]

    Cresti, A.: Convenient peierls phase choice for periodic atomistic systems under magnetic field. Phys. Rev. B 103, 045402 (2021) https://doi.org/10.1103/ PhysRevB.103.045402

  31. [31]

    nutrition label

    Collins, P.G.: Defects and disorder in carbon nanotubes. In: Narlikar, A.V., Fu, Y.Y. (eds.) Oxford Handbook of Nanoscience and Technology: Volume 2: Materials: Structures, Properties and Characterization Techniques, pp. 31–94. Oxford University Press, Oxford, UK (2017). https://doi.org/10.1093/oxfordhb/ 9780199533053.013.2

  32. [32]

    Xu, F., Sadrzadeh, A., Xu, Z., Yakobson, B.I.: Can carbon nanotube fibers achieve the ultimate conductivity?–coupled-mode analysis for electron transport through the carbon nanotube contact. J. Appl. Phys. 114, 063714 (2013) https://doi.org/ 10.1063/1.4818308

  33. [33]

    Aggarwal, Y

    Tripathy, S., Bhattacharyya, T.K.: Role of inter-tube coupling and quantum inter- ference on electrical. Physica E 83, 314–321 (2016) https://doi.org/10.1016/j. 113 physe.2016.04.033

  34. [34]

    Adinehloo, D., Gao, W., Mojibpour, A., Kono, J., Perebeinos, V.: Phonon-assisted intertube electronic transport in an armchair carbon nanotube film. Phys. Rev. Lett. 130, 176303 (2023) https://doi.org/10.1103/PhysRevLett.130.176303

  35. [35]

    Chen, Q., Lou, Z., Zhang, S., Zhou, Y., Xu, B., Chen, H., Chen, S., Du, J., Wang, H., Yang, J., Wu, Q., Yazyev, O.V., Fang, M.: Extremely large magnetoresistance in the ”ordinary” metal reo3. Phys. Rev. B 104, 115104 (2021) https://doi.org/ 10.1103/PhysRevB.104.115104

  36. [36]

    Gatti, G., Gosalbez–Martinez, D., Wu, Q.S., Hu, J., Zhang, S.N., Autes, G., Pup- pin, M., Bugini, D., Berger, H., Ortmann, F.: Origin of large magnetoresistance in the topological nonsymmorphic semimetal tase3. Phys. Rev. B 104, 155122 (2021) https://doi.org/10.1103/PhysRevB.104.155122

  37. [37]

    Hayashi, D., Nakai, Y., Kyakuno, H., Miyata, Y., Yanagi, K., Maniwa, Y.: Tem- perature dependence of the seebeck coefficient for mixed semiconducting and metallic single-wall carbon nanotube bundles. Appl. Phys. Express 13, 015001 (2020) https://doi.org/10.7567/1882-0786/ab547b

  38. [38]

    Nakanishi, T., Ando, T.: Conductance of crossed carbon nanotubes. J. Phys. Soc. Jpn. 70, 1647–1658 (2001) https://doi.org/10.1143/JPSJ.70.1647

  39. [39]

    Nanoscale 16, 7504–7514 (2024) https://doi.org/10.1039/D4NR00058G

    Ostovan, A., Milowska, K.Z., Garcia-Cervera, C.J.: A twist for tunable electronic and thermal transport properties of nanodevices. Nanoscale 16, 7504–7514 (2024) https://doi.org/10.1039/D4NR00058G

  40. [40]

    Irons, T.J.P., David, G., Teale, A.M.: Optimizing molecular geometries in strong magnetic fields. J. Chem. Theory Comput. 17, 2166 (2021) https://doi.org/10. 1021/acs.jctc.0c01297 114

  41. [41]

    Roche, S., Saito, R.: Magnetoresistance of carbon nanotubes: From molecular to mesoscopic fingerprints. Phys. Rev. Lett. 87, 246803 (2001) https://doi.org/10. 1103/PhysRevLett.87.246803

  42. [42]

    Carbon 183, 774 (2021) https://doi.org/10.1016/j.carbon.2021.07

    Gao, W., Adinehloo, D., Li, X., Mojibpour, A., Yomogida, Y., Hirano, A., Tanaka, T., Kataura, H., Zheng, M., Perebeinos, V., Kono, J.: Band structure dependent electronic localization in macroscopic films of single-chirality single-wall carbon nanotubes. Carbon 183, 774 (2021) https://doi.org/10.1016/j.carbon.2021.07. 057

  43. [43]

    Salvato, M., Lucci, M., Ottaviani, I., Cirillo, M., Orlanducci, S., Toschi, F., Terranova, M.L.: Weak localization and dimensional crossover in carbon nan- otube systems. Eur. Phys. J. B 85, 109 (2012) https://doi.org/10.1140/epjb/ e2012-20635-0

  44. [44]

    PhD thesis: University of Regensburg, Germany (2007)

    Nemec, N.: Quantum Transport in Carbon Based Nanostructures. PhD thesis: University of Regensburg, Germany (2007)

  45. [45]

    Hikami, S., Larkin, A.I., Nagaoka, Y.: Spin-orbit interaction and magnetoresis- tance in the two dimensional random system. Prog. Theor. Phys. 63, 707 (1980) https://doi.org/10.1143/PTP.63.707

  46. [46]

    Nanoscale 11, 145 (2019) https://doi.org/10

    Milowska, K.Z., Burda, M., Wolanicka, L., Bristowe, P.D., Koziol, K.K.K.: Carbon nanotube functionalization as a route to enhancing the electrical and mechanical properties of cu–cnt composites. Nanoscale 11, 145 (2019) https://doi.org/10. 1039/C8NR07521B

  47. [47]

    Liu, Z., Zhang, S., Fang, Z., Weng, H., Wu, Q.: Combined first-principles and boltzmann transport theory methodology for studying magnetotransport in mag- netic materials. Phys. Rev. Research 6, 043185 (2024) https://doi.org/10.1103/ 115 PhysRevResearch.6.043185

  48. [48]

    Peng, X., Wang, Y., Zhang, S., Zhou, Y., Sun, Y., Su, Y., Wu, C., Zhou, T., Liu, L.: Scaling behavior of magnetoresistance and hall resistivity in the altermagnet crsb. Phys. Rev. B 111, 144402 (2025) https://doi.org/10.1103/PhysRevB.111. 144402

  49. [49]

    Zhou, Y., Lou, Z., Zhang, S.N., Chen, H., Chen, Q., Xu, B., Du, J., Yang, J., Wang, H.: Linear and quadratic magnetoresistance in the semimetal sip2. Phys. Rev. B 102, 115145 (2020) https://doi.org/10.1103/PhysRevB.102.115145

  50. [50]

    Chen, Q., Lou, Z., Zhang, S.N., Xu, B., Zhou, Y., Chen, H., Chen, S., Du, J., Wang, H.: Large magnetoresistance and nonzero berry phase in the nodal- line semimetal moo2. Phys. Rev. B 102, 165133 (2020) https://doi.org/10.1103/ PhysRevB.102.165133

  51. [51]

    K., Satpati, B

    Singha, R., Pariari, A.K., Satpati, B., Mandal, P.: Large nonsaturating magne- toresistance and signature of nondegenerate dirac nodes in zrsis. PNAS 114, 2468 (2017) https://doi.org/10.1073/pnas.1618004114

  52. [53]

    Hatanpaa, B., Choi, A.Y., Cheng, P.S., Minnich, A.J.: Two-phonon scattering in nonpolar semiconductors: A first-principles study of warm electron transport in si. Phys. Rev. B 107, 041110 (2023) https://doi.org/10.1103/PhysRevB.107. L041110

  53. [54]

    Zhang, S.N., Wu, Q.S., Liu, Y., Yazyev, O.V.: Magnetoresistance from fermi surface topology. Phys. Rev. B 99, 035142 (2019) https://doi.org/10.1103/ 116 PhysRevB.99.035142

  54. [55]

    Yao, H., Hsieh, Y.-P., Kong, J., Hofmann, M.: Modelling electrical conduction in nanostructure assemblies through complex networks. Nature. Mater. 19, 745 (2020) https://doi.org/10.1038/s41563-020-0664-1

  55. [56]

    Calphald 32, 7–16 (2005) https://doi.org/10.1016/j.calphad.2005.02.003

    Lee, B., Lee, J.W.: A modified embedded atom method interatomic potential for carbon. Calphald 32, 7–16 (2005) https://doi.org/10.1016/j.calphad.2005.02.003

  56. [57]

    Schneider, J., Hamaekers, J., Chill, S.T., Smidstrup, J. S. Bulin, Thesen, R., Blom, A., Stokbro, K.: Atk-forcefield: a new generation molecular dynamics software package. Modelling Simul. Mater. Sci. Eng. 25, 085007 (2017) https: //doi.org/10.1088/1361-651X/aa8ff0

  57. [58]

    Smidstrup, S., Markussen, T., Vancraeyveld, P., Wellendorff, J., Schneider, J., Gunst, T., Verstichel, B., Stradi, D., Khomyakov, P.A., Vej-Hansen, P.A.: Quan- tumatk: An integrated platform of electronic and atomic-scale modelling tools. J. Phys: Condens. Matter (APS) 32, 015901 (2020) https://doi.org/10.1088/ 1361-648X/ab4007

  58. [59]

    Synopsis: QuantumATK, 2022.03-SP1, https://www.synopsys.com/silicon/ quantumatk.html (accessed 01-01-2024)

  59. [60]

    Papior, N.: Sisl, 0.15.1, https://doi.org/10.5281/zenodo.597181 (2023)

  60. [61]

    Hancock, Y., Uppstu, A., Saloriutta, K., Harju, A., Puska, M.: Generalized tight- binding transport model for graphene nanoribbon-based systems. Phys. Rev. B 81, 245402 (2010) https://doi.org/10.1103/PhysRevB.81.245402

  61. [62]

    Imperial College Press, London (1998) 117

    Saito, R., Dresselhaus, G., Dresselhaus, M.: Physical Properties of Carbon Nanotubes. Imperial College Press, London (1998) 117

  62. [63]

    Nature Physics 12, 639 (2016) https://doi.org/10.1038/ nphys3803

    Goldman, N., Budich, J., Zoller, P.: Topological quantum matter with ultracold gases in optical lattices. Nature Physics 12, 639 (2016) https://doi.org/10.1038/ nphys3803

  63. [64]

    Peierls, R.: Zur theorie des diamagnetismus von leitungselektronen. Z. Phys. 80, 763 (1933) https://doi.org/10.1007/BF01342591

  64. [65]

    Computer Physics Communications212, 8–24 (2017) https: //doi.org/10.1016/j.cpc.2016.09.022

    Papior, N., Lorente, N., Frederiksen, T., Garcia, A., Brandbyge, M.: Improve- ments on non-equilibrium and transport green function techniques: The next- generation transiesta. Computer Physics Communications212, 8–24 (2017) https: //doi.org/10.1016/j.cpc.2016.09.022

  65. [66]

    Brandbyge, M., Mozos, J.-L., Ordejon, P., Taylor, J., Stokbro, K.: Density- functional method for non-equilibrium electron transport. Phys. Rev. B 65, 165401 (2002) https://doi.org/10.1103/PhysRevB.65.165401

  66. [67]

    Perdew, J.P., Zunger, A.: Self-interaction correction to density-functional approx- imations for many-electron systems. Phys. Rev. B 23, 5048 (1981) https://doi. org/10.1103/PhysRevB.23.5048

  67. [68]

    doi:10.1016/j.carbon.2022.08.001

    Bulmer, J.S., Sloan, A.W.N., Glerum, M., Carpena-Nunez, J., Waelder, R., Humes, J., Boies, A.M., Pasquali, M., Rao, R., Maruyama, B.: Forecasting car- bon nanotube diameter in floating catalyst chemical vapor deposition. Carbon 201, 719 (2023) https://doi.org/10.1016/j.carbon.2022.08.001

  68. [69]

    Chemical Engineering Journal 390, 124497 (2020) https://doi.org/10.1016/j.cej.2020.124497 118

    Bulmer, J.S., Kaniyoor, A., Gspann, T., Mizen, J., Ryley, J., Kiley, P., Rater- ing, G., Sparreboom, W., Bauhuis, G., Stehr, T., Oudejans, D., Sparkes, M., O’Neill, B., Elliott, J.A.: Forecasting continuous carbon nanotube production in the floating catalyst environment. Chemical Engineering Journal 390, 124497 (2020) https://doi.org/10.1016/j.cej.2020.124497 118

  69. [70]

    Semicond

    Strunk, C., Stojetz, B., Roche, S.: Quantum interference in multiwall carbon nanotubes. Semicond. Sci. Technol. 21, 38–45 (2006) https://doi.org/10.1088/ 0268-1242/21/11/S06

  70. [71]

    Semicond

    Nanot, S., Escoffier, W., Lassagne, B., Broto, J.-M., Raquet, B.: Exploring the electronic band structure of individual carbon nanotubes under 60 t. Semicond. Sci. Technol. 10, 268–282 (2009) https://doi.org/10.1016/j.crhy.2009.05.005

  71. [72]

    Marganska, M., Schmid, D.R., Dirnaichner, A., Stiller, P.L., Strunk, C., Grifoni, M., Huttel, A.K.: Shaping electron wave functions in a carbon nanotube with a parallel magnetic field. Phys. Rev. Lett. 122, 086802 (2019) https://doi.org/10. 1103/PhysRevLett.122.086802

  72. [73]

    Raquet, B., Avriller, B. R. Lassagne, Nanot, S., Escoffier, W., Broto, J.-M., Roche, S.: Onset of landau-level formation in carbon-nanotube-based electronic fabry- perot resonators. Phys. Rev. Lett. 101, 046803 (2008) https://doi.org/10.1103/ PhysRevLett.101.046803

  73. [74]

    Goupalov, S.V.: Bloch electrons of a carbon nanotube in a perpendicular mag- netic field. Phys. Rev. B 98, 035416 (2008) https://doi.org/10.1103/PhysRevB. 98.035416

  74. [75]

    Khromov, K.Y., Knizhnik, A.A., Potapkin, B.V., Kenny, J.M.: Multiscale model- ing of electrical conductivity of carbon nanotubes based polymer nanocomposites. J. Appl. Phys. 121, 225102 (2017) https://doi.org/10.1063/1.4984758

  75. [76]

    Larin, S.V., Lyulin, S.V., Likhomanova, P.A., Khromov, K.Y., Knizhnik, A.A., Potapkin, B.V.: Multiscale modeling of electrical conductivity of r-bapb polyimide plus carbon nanotubes nanocomposites. Phys. Rev. Materials 5, 066002 (2021) https://doi.org/10.1103/PhysRevMaterials.5.066002 119

  76. [77]

    Trizon, F., Philippe, L., Roche, S., Rubio, A., Mayou, D.: Electrical transport in carbon nanotubes: Role of disorder and helical symmetries. Phys. Rev. B 69, 121410 (2004) https://doi.org/10.1103/PhysRevB.69.121410

  77. [78]

    Lambin, P., Philippe, L., Charlier, J.C., Michenaud, J.P.: Electronic band struc- ture of multilayered carbon tubules. Comp. Mater. Science 2, 350 (1994) https: //doi.org/10.1016/0927-0256(94)90117-1

  78. [79]

    Zi Wang, Z., Peng, X., Zhang, S., Su, Y., Lai, S., Zhou, X., Wu, C., Zhou, T., Wang, H., Yang, J., Chen, B., Zhai, H., Wu, Q., Du, J., Jiao, Z., Fang, M.: Negative magnetoresistance in the antiferromagnetic semimetal v1/3tas2. Chin. Phys. B 33, 037301 (2024) https://doi.org/10.1088/1674-1056/ad18aa

  79. [80]

    Novak, M., Zhang, S.N., Orbanic, F., Biliskov, N., Eguchi, G., Paschen, S., Kimura, A., Wang, X.X., Osada, T.: Highly anisotropic interlayer magnetore- sitance in zrsis nodal-line dirac semimetal. Phys. Rev. B 100, 085137 (2019) https://doi.org/10.1103/PhysRevB.100.085137

  80. [81]

    Xu, Z., Wang, Y., Zhang, C., Liu, H., Han, X., Wu, L., Zhang, X., Wu, Q., Sh, Y.: Magnetization plateau and anisotropic magnetoresistance in the frustrated kondo–lattice compound ce3scbi5. Phys. Rev. B 110, 165106 (2024) https://doi. org/10.1103/PhysRevB.110.165106 120