Pith. sign in

REVIEW 4 major objections 2 minor 1 cited by

Discovery of a low-density filled-ice phase in nitrogen hydrate at high pressure

T0 review · 4 major / 2 minor · reviewed 2026-08-05 · deepseek-v4-flash

Pith's one-line read Nitrogen hydrate transforms at about 1.8 GPa into a previously unknown orthorhombic filled-ice phase, NH-V, with a density roughly 30% below ice VII and no match to known water frameworks.

desk verdict The abstract announces a plausible new low-density filled-ice phase in nitrogen hydrate, but the attached full text is an unrelated cardiac modeling paper, so the central claim cannot be audited from this record. read the letter →

arxiv 2508.09771 v1 pith:YPVCSMZG submitted 2025-08-13 cond-mat.mtrl-sci cond-mat.other

classification cond-mat.mtrl-scicond-mat.other
keywords nitrogenhydratefilled-icephasehighpressureclathratePnmaneutrondiffractiondiagramplanetaryice
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper maps what happens to nitrogen hydrate when it is compressed to 16 GPa at room temperature, combining neutron diffraction, Raman spectroscopy, and crystal-structure prediction. It reports that above about 1.8 GPa, water and nitrogen form a previously unknown filled-ice phase, designated NH-V, with an orthorhombic Pnma arrangement that fits none of the known water frameworks that host small molecules, such as the methane hydrate structures MH-III and MH-IV. The authors measure its density to be about 30 percent lower than that of stable ice VII, which would make it an unusually open filled-ice structure and would point to water–nitrogen interactions that differ from those of other guests. If correct, the finding extends the known phase behavior of nitrogen hydrates into a new structural family and gives planetary scientists a candidate interior material for nitrogen-rich icy worlds.

What carries the argument

The central object is NH-V, a filled-ice structure: a hydrogen-bonded water framework whose cavities accommodate nitrogen molecules. The identification of NH-V rests on three complementary probes: neutron diffraction to determine the framework, Raman spectroscopy to track the guest and host responses across the phase transitions, and crystal-structure prediction to test whether the proposed topology is energetically accessible. The load-bearing comparison is the roughly 30% density deficit relative to ice VII, which is what marks NH-V as a distinct open framework rather than another dense hydrate phase.

What would settle it

Re-index the diffraction pattern collected above 1.8 GPa against a mixture of sH and sT phases (without adding any new phase) and compare the measured pressure–volume curve to the assumed NH-V stoichiometry; if the pattern fits the mixture with no unassigned reflections, or the density equals that of ice VII once the true water:guest ratio is used, the claim of a new low-density filled-ice phase fails.

Watch

Extended reading notes

Core claim

The paper reports a previously unknown phase of nitrogen hydrate, NH-V, which forms above roughly 1.8 GPa at room temperature and remains stable to at least 16 GPa. The phase has an orthorhombic Pnma structure and belongs to the filled-ice family, meaning nitrogen molecules sit inside cavities of a hydrogen-bonded water framework; however, its diffraction pattern cannot be matched to known filled-ice frameworks such as methane hydrates MH-III and MH-IV. The reported density is about 30% lower than that of ice VII at comparable conditions, which the authors interpret as indicating a distinctively open water network and specific water–nitrogen interactions.

Load-bearing premise

The diffraction and Raman data above 1.8 GPa are interpreted as a single new orthorhombic phase with one fixed nitrogen-to-water ratio; if the sample actually contained a mixture of already-known hydrate phases, or if the refined stoichiometry is wrong, the claimed new structure and its low density compared with ice VII would not hold.

Editorial extensions

If this is right

  • Above 1.8 GPa at room temperature, nitrogen hydrate exists as the new NH-V phase, not as any known clathrate or filled-ice structure.
  • NH-V persists to at least 16 GPa, so nitrogen hydrates cannot be described solely as a sequence of sI/sII, sH, and sT phases; the filled-ice regime is structurally richer.
  • A nitrogen hydrate that is about 30% less dense than ice VII means the water framework uses space inefficiently, so pressure–volume relations for nitrogen-rich planetary interiors will need to include a distinct low-density component.
  • The observed sequence from sI/sII clathrates to sH and sT and finally to NH-V gives a benchmark set of hydrate phases that crystal-structure prediction methods should be able to reproduce.
  • The existence of NH-V demonstrates that small molecular guests beyond methane can stabilize filled-ice frameworks at high pressure, extending the known structural chemistry of hydrates.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the 30% density deficit is real, NH-V would be an unusually open filled-ice host, making it a test case for how guest molecules influence water-framework topology under pressure; a direct equation-of-state measurement to 16 GPa could check whether NH-V is genuinely more compressible than ice VII.
  • A natural extension would be to apply the same experimental pipeline to oxygen or argon hydrates; discovering similar low-density filled-ice phases would show that the NH-V topology is a generic small-molecule effect, while their absence would single out nitrogen–water interactions as special.
  • The reliance on a single water:guest ratio in the refined structure means that the density comparison to ice VII could be re-tested by neutron contrast experiments or by measuring the guest occupancy directly; a different occupancy would change the density estimate without requiring a new structural assignment.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 2 minor

Summary. The record under review is arXiv:2508.09771, whose abstract announces a high-pressure neutron diffraction, Raman, and crystal-structure-prediction study of nitrogen hydrate up to 16 GPa, culminating in the claimed discovery of a new orthorhombic filled-ice phase NH-V (Pnma) above 1.8 GPa, with a density roughly 30% lower than ice VII. However, the full text supplied in the record is arXiv:2508.09772, an unrelated cardiac symbolic-regression paper titled "Physics-Informed Symbolic Regression for Elasticity Modeling in Cardiac Digital Twins". That full text contains no nitrogen-hydrate experiments, no diffraction or Raman data, no structure-solution details, no refinement tables, and no density calculations. The central phase-discovery claim is therefore not supported by any auditable evidence in this submission.

Significance. If substantiated, a low-density filled-ice phase of nitrogen hydrate stable to 16 GPa would be a notable result for high-pressure clathrate chemistry and planetary science. The claimed Pnma structure, its non-indexability to known ice frameworks, and its unusually low density relative to ice VII are all falsifiable and potentially important. However, the submitted record provides no derivations, no experimental data, no error estimates, no refinement details, no crystal-structure-prediction settings, and no reproducible code or data. No strength of the manuscript can currently be independently assessed because the full text is unrelated to the abstract. The significance of the abstract's claim cannot compensate for the absence of its supporting evidence.

major comments (4)
  1. [Full Text] The supplied full text is arXiv:2508.09772, a cardiac-tissue symbolic-regression paper. It contains no mention of nitrogen hydrate, neutron diffraction, Raman spectroscopy, clathrate phases, or the NH-V structure. Every load-bearing element of the abstract—phase mapping, Pnma assignment, non-indexability to known frameworks, and the 30% density comparison—is asserted without accompanying methods or results. This is not a local presentation issue; the manuscript's central claim is entirely unsupported in the provided record.
  2. [Abstract, NH-V phase assignment] The claim that the new phase "cannot be indexed to any known ice frameworks" and is assigned to Pnma requires diffraction peak positions, indexing tables, space-group determination, and ideally Rietveld/refinement residuals. None are present. Without a peak list or refinement, the single-phase Pnma assignment cannot be checked, and the comparison with MH-III (Imma) and MH-IV (Pmcn) is unverifiable.
  3. [Abstract, density comparison and stoichiometry] The statement that NH-V has a density approximately 30% lower than ice VII depends on the assumed N2:H2O stoichiometry and on the unit-cell volume. The record does not state the stoichiometry, the refined lattice parameters, or the method by which density was computed. If the stoichiometry differs from the assumed value, or if the sample is a mixture of known phases such as sH and sT, the density comparison to ice VII does not follow. The abstract alone cannot rule out these alternatives.
  4. [Full Text / Methods] There is no description of the experimental setup, pressure calibration, sample composition, neutron or Raman measurement conditions, or crystal-structure-prediction methodology. Terms such as CSP are mentioned only in the abstract. Consequently, the stability claim "up to 16 GPa at room temperature" has no associated pressure-temperature protocol, uncertainty, or reproducibility information.
minor comments (2)
  1. [General record consistency] The author list, affiliations, references, and data-availability statements in the full text correspond to the cardiac paper, not to the nitrogen-hydrate abstract. If this is a submission-system misassociation, the record must be corrected before any further review; as presented, the manuscript is internally inconsistent.
  2. [Abstract, phase-boundary wording] The abstract states the new phase appears "above 1.8 GPa" and persists "up to 16 GPa," but does not specify the pressure step size, the number of data points across this range, or the uncertainty in the phase boundary. This is secondary to the missing evidence, but would need to be addressed in a complete manuscript.

Circularity Check

0 steps flagged · score 0.0 of 10

No circular derivation in the abstract; the supplied full text is an unrelated paper, so no circular step can be exhibited.

full rationale

The only in-scope text that corresponds to the claimed nitrogen-hydrate study is the abstract. The abstract reports an empirical phase diagram derived from neutron diffraction, Raman spectroscopy, and crystal structure prediction. No equation or derivation is given that would allow a claim such as 'X is derived from Y while X is defined in terms of Y.' The key assertions—a new Pnma filled-ice phase NH-V, the inability to index it to known ice frameworks, and a density about 30% lower than ice VII—are presented as experimental findings benchmarked against external standards, not as consequences of a fitted parameter renamed as a prediction. There are no self-citations in the abstract and no uniqueness theorem is invoked. The full text attached to this record is arXiv:2508.09772, a cardiac symbolic-regression paper with different authors and content; it contains no nitrogen-hydrate data, refinements, or equations. This mismatch means the derivation chain cannot be audited from the supplied record, but a missing or mismatched full text is a support/integrity problem, not circularity. Under the hard rule that circularity may only be flagged when the paper itself exhibits the specific reduction, no circular step can be identified. Score 0.

Assumptions & free parameters 1 free parameters · 3 assumptions · 1 invented entities

The ledger cannot be properly audited because the supplied full text is a different paper (arXiv:2508.09772). The entries below are the minimal assumptions visible in the abstract; a full review of the actual manuscript would add Rietveld parameters, pressure calibration, and composition constraints.

free parameters (1)
  • N2:H2O stoichiometry of NH-V
    The density comparison to ice VII depends on the water:guest ratio in the Pnma cell; this ratio is not stated in the abstract and is typically refined against neutron data.
assumptions (3)
  • domain assumption The high-pressure neutron diffraction and Raman measurements probe the equilibrium bulk phase of nitrogen hydrate, so the reported phase sequence reflects thermodynamic stability rather than kinetic trapping.
    Stated implicitly in the abstract's phase diagram claim; not verifiable from the abstract alone.
  • domain assumption Crystal structure prediction explores the relevant configuration space of N2-H2O, so the absence of a match to known frameworks (MH-III, MH-IV) indicates a genuinely new structure.
    The abstract uses the non-indexability to justify novelty; this assumes the CSP search and the framework database are complete.
  • domain assumption The density comparison to ice VII assumes a correct stoichiometry for NH-V and correct lattice parameters from the Pnma refinement.
    A 30% density deficit is only meaningful if the unit cell content is fixed correctly; full text would document the refinement.
invented entities (1)
  • NH-V phase
    purpose: Names the new orthorhombic Pnma filled-ice structure claimed to appear above 1.8 GPa
    The phase is the central claimed discovery; the abstract provides no independent falsifiable handle (e.g., predicted distinctive diffraction peaks at specific d-spacings or predicted equation of state) outside the paper's own data.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Discovery of a low-density filled-ice phase in nitrogen hydrate at high pressure." pith.science (2026). https://pith.science/paper/YPVCSMZG

@misc{pith2026250809771,
  author       = {Pith},
  title        = {Pith review of: Discovery of a low-density filled-ice phase in nitrogen hydrate at high pressure},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YPVCSMZG}},
  note         = {Machine review of arXiv:2508.09771}
}
read the original abstract

We map the high-pressure phase diagram of nitrogen hydrate up to 16 GPa at room temperature by combining neutron diffraction, Raman spectroscopy, and crystal structure prediction. We reveal a rich sequence of structural transformations, from sI/sII clathrates to hexagonal (sH) and tetragonal (sT) phases, culminating in a previously unknown orthorhombic filled-ice structure above 1.8 GPa in the Pnma space group, which we designate as NH-V. This new phase cannot be indexed to any known ice frameworks - such as the high-pressure methane hydrates MH-III (Imma) or MH-IV (Pmcn) - and exhibits a density approximately 30% lower than that of stable ice VII, pointing to distinctive water-nitrogen interactions. Our results refine the understanding of nitrogen hydrate behavior under extreme conditions and demonstrate the propensity of nitrogen and water to form stable filled-ice structures up to 16 GPa, with important implications for planetary science.

Discussion (0). Sign in to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Free energy differences and coexistence of clathrate structures II and H via lattice-switch Monte Carlo

    physics.chem-ph 2026-04 unverdicted novelty 7.0 of 10

    A lattice-switch Monte Carlo technique with thermodynamic integration in a fluctuating-guest ensemble calculates coexistence pressures between clathrate structures II and H that agree with experimental data for argon ...

Reference graph

Works this paper leans on

67 extracted references · 67 canonical work pages · cited by 1 Pith paper

  1. [1]

    Corral-Acero, J.�� ���The ‘Digital Twin’ to enable the vision of precision cardiology.�������� ����� ������� ���4556–4564 (2020)

  2. [2]

    & Grau, V

    Li, L., Camps, J., Rodriguez, B. & Grau, V. Solving the inverse problem of electrocardiography for cardiac digital twins: A survey.���� ������� �� ���������� ��������������316–336 (2024). 27

  3. [3]

    Coorey, G.�� ���The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field.��� ������� ����������126 (2022)

  4. [4]

    Sel, K.�� ���Building digital twins for cardiovascular health: from principles to clinical impact.������� �� ��� �������� ����� ��������������e031981 (2024)

  5. [5]

    & Sch ¨olkopf, B

    Von Luxburg, U. & Sch ¨olkopf, B. in�������� �� ��� ������� �� �����651–706 (Elsevier, 2011)

  6. [6]

    G., Rypdal, K

    Lunde, I. G., Rypdal, K. B., Van Linthout, S., Diez, J. & Gonz ´alez, A. Myocardial fibrosis from the perspective of the extracellular matrix: mechanisms to clinical impact.������ �������(2024)

  7. [7]

    Balaban, G.�� ���In vivo estimation of elastic heterogeneity in an infarcted human heart.������������ ��� �������� �� �����������������1317–1329 (2018)

  8. [8]

    R., Seiler, C

    Mandinov, L., Eberli, F. R., Seiler, C. & Hess, O. M. Diastolic heart failure.�������������� �����������813– 825 (2000)

Show all 67 references
  1. [9]

    Holzapfel, G. A. & Ogden, R. W. Constitutive modelling of passive myocardium: a structurally based framework for material characterization.������������� ������������ �� ��� ����� ������� �� ������������� �������� ��� ����������� ������������3445–3475 (2009)

  2. [10]

    & Hunter, P

    Schmid, H., Nash, M., Young, A. & Hunter, P. Myocardial material parameter estimation—a comparative study for simple shear.������� �� ������������� ���������������742–750 (2006)

  3. [11]

    D., Holmes, J

    Costa, K. D., Holmes, J. W. & McCulloch, A. D. Modelling cardiac mechanical properties in three dimensions. ������������� ������������ �� ��� ����� ������� �� ������� ������ �� ������������� �������� ��� ����������� ������������1233–1250 (2001)

  4. [12]

    Hunter, P. J. Computational electromechanics of the heart.������������� ������� �� ��� ������345–407 (1997)

  5. [13]

    C., Strumpf, R

    Yin, F. C., Strumpf, R. K., Chew, P. H. & Zeger, S. L. Quantification of the mechanical properties of noncontracting canine myocardium under simultaneous biaxial loading.������� �� ���������������577–589 (1987)

  6. [14]

    contains independent measurements from four regions of the heart (sub-endocardium, mid-myocardium, sub- epicardium, and mid-septum) of two specimens. This information is reflected in the�������column of Supplementary Table 1, with the Novak equibiaxial dataset containing eight...

  7. [15]

    P., Yin, F

    Novak, V. P., Yin, F. & Humphrey, J. Regional mechanical properties of passive myocardium.������� �� ���������������403–412 (1994)

  8. [16]

    Sommer, G.�� ���Biomechanical properties and microstructure of human ventricular myocardium.���� ����������������172–192 (2015)

  9. [17]

    H., Young, A

    Dokos, S., Smaill, B. H., Young, A. A. & LeGrice, I. J. Shear properties of passive ventricular myocardium. �������� ������� �� ���������������� ��� ����������� ��������������H2650–H2659 (2002)

  10. [18]

    W.�� ���Development of an in vivo method for determining material properties of passive myocardium

    Remme, E. W.�� ���Development of an in vivo method for determining material properties of passive myocardium. ������� �� ���������������669–678 (2004)

  11. [19]

    Hadjicharalambous, M.�� ���Analysis of passive cardiac constitutive laws for parameter estimation using 3D tagged MRI.������������ ��� �������� �� �����������������807–828 (2015)

  12. [20]

    ������������ ��� �������� �� �����������������971–988 (2017)

    Nasopoulou, A.�� ���Improved identifiability of myocardial material parameters by an energy-based cost function. ������������ ��� �������� �� �����������������971–988 (2017)

  13. [21]

    Krishnamurthy, A.�� ���Patient-specific models of cardiac biomechanics.������� �� ������������� ������� ����4–21 (2013)

  14. [22]

    Sack, K. L.�� ���Construction and validation of subject-specific biventricular finite-element models of healthy and failing swine hearts from high-resolution DT-MRI.��������� �� ������������539 (2018)

  15. [23]

    Marx, L.�� ���Robust and efficient fixed-point algorithm for the inverse elastostatic problem to identify myocardial passive material parameters and the unloaded reference configuration.������� �� ������������� ����������� ����: 10902716 (Aug. 2022)

  16. [24]

    Y., Takayama, H

    Shi, L., Chen, I. Y., Takayama, H. & Vedula, V. An optimization framework to personalize passive cardiac mechanics.�������� ������� �� ������� ��������� ��� ���������������117401 (2024)

  17. [25]

    & Mont ´ans, F

    Latorre, M. & Mont ´ans, F. J. WYPiWYG hyperelasticity without inversion formula: Application to passive ventricular myocardium.��������� � ��������������47–58 (2017)

  18. [26]

    Martonov ´a, D.�� ���Automated model discovery for human cardiac tissue: discovering the best model and parameters.�������� ������� �� ������� ��������� ��� ���������������117078 (2024)

  19. [27]

    Martonov ´a, D., Leyendecker, S., Holzapfel, G. A. & Kuhl, E. Discovering dispersion: How robust is auto- mated model discovery for human myocardial tissue? D. Martonov ´a et al.������������ ��� �������� �� ���������������1–15 (2025)

  20. [28]

    G¨ ultekin, O.�� ���A Physics-Informed Neural Network Model for the Anisotropic Hyperelasticity of the Human Passive Myocardium.������������� ������� ��� ��������� ������� �� ���������������e70067 (2025). 28

  21. [29]

    Moon, H.�� ���Physics-informed neural network-based discovery of hyperelastic constitutive models from extremely scarce data.�������� ������� �� ������� ��������� ��� ���������������118258 (2025)

  22. [30]

    Ludwicki, K.�� ���in������������� ����������� ������ ������ ������ ����� ������� �������1–17 (Springer Nature Switzerland Cham, 2023)

  23. [31]

    A.��������� ����� ���������� � ��������� �������� ��� ����������� �������(Kluwer Academic Publishers Dordrecht, 2002)

    Holzapfel, G. A.��������� ����� ���������� � ��������� �������� ��� ����������� �������(Kluwer Academic Publishers Dordrecht, 2002)

  24. [32]

    Klotz, S.�� ���Single-beat estimation of end-diastolic pressure-volume relationship: a novel method with potential for noninvasive application.�������� ������� �� ���������������� ��� ����������� ��������������H403– H412 (2006)

  25. [33]

    Finsberg, H.�� ���Efficient estimation of personalized biventricular mechanical function employing gradient- based optimization.������������� ������� ��� ��������� ������� �� ���������� ��������������e2982 (2018)

  26. [34]

    Aliev, R. R. & Panfilov, A. V. A simple two-variable model of cardiac excitation.������ �������� � ���������� 293–301 (1996)

  27. [35]

    Mitchell, C. C. & Schaeffer, D. G. A two-current model for the dynamics of cardiac membrane.�������� �� ������������ ����������767–793 (2003)

  28. [36]

    & Itskov, M

    Abdusalamov, R., Hillg ¨artner, M. & Itskov, M. Automatic generation of interpretable hyperelastic material models by symbolic regression.������������� ������� ��� ��������� ������� �� ���������������2093–2104 (2023)

  29. [37]

    & Wang, X

    Hou, J., Chen, X., Wu, T., Kuhl, E. & Wang, X. Automated data-driven discovery of material models based on symbolic regression: A case study on the human brain cortex.���� �����������������276–296 (2024)

  30. [38]

    ������������ ��� �������� �� �����������������1213–1232 (2019)

    Guan, D.�� ���On the AIC-based model reduction for the general Holzapfel–Ogden myocardial constitutive law. ������������ ��� �������� �� �����������������1213–1232 (2019)

  31. [39]

    Hadjicharalambous, M.�� ���Investigating the reference domain influence in personalised models of car- diac mechanics: Effect of unloaded geometry on cardiac biomechanics.������������ ��� �������� �� �����������������1579–1597 (2021)

  32. [40]

    & Gao, H

    Lazarus, A., Dalton, D., Husmeier, D. & Gao, H. Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics.������������ ��� �������� �� �����������������953–982 (2022)

  33. [41]

    Mojsejenko, D.�� ���Estimating passive mechanical properties in a myocardial infarction using MRI and finite element simulations.������������ ��� �������� �� �����������������633–647 (2015)

  34. [42]

    Hadjicharalambous, M.�� ���Non-invasive model-based assessment of passive left-ventricular myocardial stiffness in healthy subjects and in patients with non-ischemic dilated cardiomyopathy.������ �� ���������� ��������������605–618 (2017)

  35. [43]

    C., Lovell, N

    Ahmad Bakir, A., Al Abed, A., Stevens, M. C., Lovell, N. H. & Dokos, S. A multiphysics biventricular cardiac model: Simulations with a left-ventricular assist device.��������� �� ������������1259 (2018)

  36. [44]

    W., Costa, C

    Lee, A. W., Costa, C. M., Strocchi, M., Rinaldi, C. A. & Niederer, S. A. Computational modeling for cardiac resynchronization therapy.������� �� �������������� ������������� �����������92–108 (2018)

  37. [45]

    Priego, L.�� ���Integration of Electrophysiological and Mechanical Biomarkers in Cardiac Risk Assessment Models.�������� ������� ��� �������� �� ������������108896 (2025)

  38. [46]

    A., Niestrawska, J

    Holzapfel, G. A., Niestrawska, J. A., Ogden, R. W., Reinisch, A. J. & Schriefl, A. J. Modelling non-symmetric collagen fibre dispersion in arterial walls.������� �� ��� ����� ������� ������������20150188 (2015)

  39. [47]

    & Tsoukalas, G

    Papandrinopoulou, D., Tzouda, V. & Tsoukalas, G. Lung compliance and chronic obstructive pulmonary disease. ��������� �������������542769 (2012)

  40. [48]

    B., Ward, B., Gallup, L

    Fahmy, Y., Trabia, M. B., Ward, B., Gallup, L. & Froehlich, M. Development of an Anisotropic Hyperelastic Material Model for Porcine Colorectal Tissues.�����������������64 (2024)

  41. [49]

    A., Budday, S., Holzapfel, G

    Mihai, L. A., Budday, S., Holzapfel, G. A., Kuhl, E. & Goriely, A. A family of hyperelastic models for human brain tissue.������� �� ��� ��������� ��� ������� �� ����������60–79 (2017)

  42. [50]

    https: //onlinelibrary.wiley.com/doi/abs/10.1002/nme.70067 (2025)

    G¨ ultekin, O.�� ���A Physics-Informed Neural Network Model for the Anisotropic Hyperelasticity of the Human Passive Myocardium.������������� ������� ��� ��������� ������� �� ���������������e70067. https: //onlinelibrary.wiley.com/doi/abs/10.1002/nme.70067 (2025)

  43. [51]

    Pfaller, M. R.�� ���The importance of the pericardium for cardiac biomechanics: from physiology to computational modeling: MR Pfaller et al.������������ ��� �������� �� �����������������503–529 (2019)

  44. [52]

    Ball, J. M. Convexity conditions and existence theorems in nonlinear elasticity.������� ��� �������� ��������� ��� �����������337–403 (1976). 29

  45. [53]

    Campostrini, G.�� ���Generation, functional analysis and applications of isogenic three-dimensional self- aggregating cardiac microtissues from human pluripotent stem cells.������ ������������2213–2256 (2021)

  46. [54]

    & Hunter, P

    Smaill, B. & Hunter, P. in������ �� ������ ������������� ����������� ��� ��������� �������� �� ������� �������� 1–29 (Springer, 1991)

  47. [55]

    L., Rosenblatt, M., T¨onsing, C

    Wieland, F.-G., Hauber, A. L., Rosenblatt, M., T¨onsing, C. & Timmer, J. On structural and practical identifiability. ������� ������� �� ������� ����������60–69 (2021)

  48. [56]

    Raue, A.�� ���Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood.�����������������1923–1929 (2009)

  49. [57]

    & Timmer, J

    Kreutz, C., Raue, A. & Timmer, J. Likelihood based observability analysis and confidence intervals for predictions of dynamic models.��� ������� ���������1–9 (2012)

  50. [58]

    D., Blake, R

    Bayer, J. D., Blake, R. C., Plank, G. & Trayanova, N. A. A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models.������ �� ���������� ��������������2243–2254 (2012)

  51. [59]

    Yeoh, O. H. Some forms of the strain energy function for rubber.������ ��������� ��� �������������754–771 (1993)

  52. [60]

    McEvoy, E., Holzapfel, G. A. & McGarry, P. Compressibility and anisotropy of the ventricular myocardium: experimental analysis and microstructural modeling.������� �� ������������� ���������������081004 (2018)

  53. [61]

    Alnæs, M.�� ���The FEniCS project version 1.5.������� �� ��������� ���������(2015)

  54. [62]

    K., Genet, M

    Rausch, M. K., Genet, M. & Humphrey, J. D. An augmented iterative method for identifying a stress-free reference configuration in image-based biomechanical modeling.������� �� ���������������227–231 (2017)

  55. [63]

    & Han, L

    Gao, F. & Han, L. Implementing the Nelder-Mead simplex algorithm with adaptive parameters.������������� ������������ ��� ���������������259–277 (2012)

  56. [64]

    Nash, S. G. Newton-type minimization via the Lanczos method.���� ������� �� ��������� �����������770– 788 (1984)

  57. [65]

    S., Sundnes, J

    Balaban, G., Alnæs, M. S., Sundnes, J. & Rognes, M. E. Adjoint multi-start-based estimation of cardiac hyper- elastic material parameters using shear data.������������ ��� �������� �� �����������������1509–1521 (2016)

  58. [66]

    https://figshare.com/articles/dataset/Raw data/29544404

    Ohnemus, S.�� ��� ��� ����July 2025. https://figshare.com/articles/dataset/Raw data/29544404. 30 � ������������� ����������� ��� �������������� �� ��� �������� ���������� �� ��� ������ ������ To interpret the material parameters in the two CHESRA SEFs, we considered how the pa...

  59. [67]

    4)( ˜�8��+� 4+� 5 ˜�4�+( ˜�8� � �3+ ˜�8� �)(� 1 ˜�1 ˜�5�+� 2)) 39 (� 14+� 15+ ˜�1+ ˜�5�)( ˜�8� �( ˜�8� �+� 2+ �4 ˜�4�(� 3+ ˜�4�)+(� 5 ˜�1+� 6+� 7( ˜�8� �+ ˜�5�))exp( ˜�8��))+� 1+� 13(� 10 ˜�1+� 11+ �12( ˜�8� �+ ˜�5�))+� 9 ˜�4�(� 8+ ˜�4�)) 60 Shear (Dokos 2002) (� 1 �2 ˜�1+(� 3...

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.