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REVIEW 5 major objections 6 minor 81 references

An accelerated simulation method reproduces cascade defect kinetics and maps aluminum's high-dose damage into three regimes.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-08-01 04:59 UTC pith:GSLZKYLA

load-bearing objection A well-documented method-acceleration study whose high-dose conclusions rest on one unvalidated extrapolation; worth peer review, but only with a high-dose benchmark added. the 5 major comments →

arxiv 2607.22364 v1 pith:GSLZKYLA submitted 2026-07-24 cond-mat.mtrl-sci

Mechanisms of Microstructural Evolution and Degradation in Aluminum under High-Damage Irradiation

Alhassan S. Issaka , Sadie Wicks , Vishal Yadav , Assel Aitkaliyeva , Michael R. Tonks , Simon R. Phillpot This is my paper
classification cond-mat.mtrl-sci PACS 61.80.-x61.72.Lk
keywords aluminumradiation damagemolecular dynamicsiterative kinetic approachstacking fault tetrahedraFrank loopsShockley partialsirradiation hardening
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper sets out to show that the Iterative Kinetic Approach (IKA), which replaces the expensive ballistic stage of each collision cascade with fast random insertion of calibrated Frenkel pairs, reproduces the defect kinetics of full cascade-overlap molecular dynamics while requiring far less computation. Using IKA, the authors push simulated single-crystal aluminum to 0.175 displacements per atom (dpa), about three times the damage accessible to explicit cascade simulations. From those runs they identify three regimes of microstructural evolution: recombination-driven annihilation up to about 0.03 dpa, accumulation-dominated growth from 0.03 to 0.09 dpa, and sink-controlled absorption beyond 0.09 dpa. They further argue that Frank loops dissociate into Shockley partials and stair-rod loops, nucleating stacking-fault tetrahedra (SFTs), and that the resulting defect mix explains irradiation hardening that saturates near 2.4–2.5 GPa. If correct, the paper makes high-dose atomistic radiation-damage studies tractable and gives a mechanistic narrative connecting atomic defects to mechanical degradation in aluminum.

Core claim

The central claim is that the Iterative Kinetic Approach (IKA), which replaces each explicit collision cascade with a calibrated random insertion of 45 Frenkel pairs followed by a 35 ps relaxation, reproduces the essential defect kinetics and spatial defect topology of full cascade-overlap molecular dynamics in single-crystal aluminum. The paper benchmarks this equivalence by pair-correlation agreement (correlation coefficient 0.998 at the same dose) and by convergence of cluster-size statistics beyond about 0.048 dpa, then uses IKA to reach 0.175 dpa—about three times the damage feasible with explicit cascades. At these high doses the paper reports three regimes: recombination-driven annihi

What carries the argument

The Iterative Kinetic Approach (IKA): each step inserts 45 randomly placed vacancy–interstitial pairs—the stable Frenkel-pair yield of a single 5 keV cascade estimated from athermal-recombination-corrected dpa—minimizes the cell, and relaxes it for 35 ps, accumulating about 1.6×10^-4 dpa per step. The method is designed to skip the computationally expensive ballistic stage while keeping the kinetic stage that governs cluster evolution; the paper argues that residual defects from the ballistic stage, not the collision details, determine subsequent microstructure. The analysis also uses the dispersed-barrier hardening model, which converts computed defect densities and sizes into yield-stress

Load-bearing premise

The load-bearing premise is that randomly inserting Frenkel pairs with short 35 ps relaxations preserves the physical defect-evolution pathways of real collision cascades up to 0.175 dpa; the paper's own benchmark reaches only about 0.061 dpa and shows IKA producing roughly twice the defect fraction of cascade-overlap simulations at the same nominal dose.

What would settle it

Run explicit cascade-overlap molecular dynamics in the same 276,480-atom aluminum cell to 0.175 dpa and compare total defect fraction, cluster-size distributions, Frank-loop dissociation, SFT density, and hardening. If the factor-of-two defect excess seen at 0.061 dpa persists, or if no SFTs appear past 0.09 dpa, the IKA-based three-regime narrative fails. A complementary check is transmission electron microscopy of aluminum irradiated with about 50 keV He to roughly 0.17 dpa: it should show SFT densities approaching 8×10^24 m^-3 if the prediction is right.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • IKA makes doses around 0.175 dpa accessible in atomistic simulations, roughly three times farther than explicit cascade-overlap runs, so high-dose microstructures can be studied directly.
  • Aluminum's radiation response at 300 K is organized into three regimes with transitions near 0.03 and 0.09 dpa, giving a predictive scaffold for when recombination, accumulation, or sink absorption dominates.
  • Frank loops are not stable end products: they dissociate into Shockley partials and stair-rods through stitch-and-transform and coalescence mechanisms, converting mobile defects into immobile configurations.
  • Stacking-fault tetrahedra form through both vacancy collapse and dislocation-mediated stair-rod reactions, and their coalescence into larger SFTs explains late-stage defect retention.
  • Irradiation hardening in single-crystal aluminum is controlled early by interstitial clusters (about 90% of strengthening below 0.02 dpa), rises to a total near 2.4–2.5 GPa, and saturates while the SFT contribution is still increasing.

Where Pith is reading between the lines

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

  • A testable extension: because IKA bypasses thermal-spike spatial correlations, the exact regime boundaries and SFT densities may shift if explicit cascade-overlap simulations are run to the same doses; the underlying pathways could survive even if the numbers move.
  • The dislocation-mediated SFT pathway suggests a transferable prediction for other FCC metals: metals with lower stacking-fault energy should show SFT formation at lower doses under the same IKA protocol, since Shockley partials will be more readily absorbed into stair-rod configurations.
  • At the method's effective dose rate (about 4.65×10^6 dpa/s), thermally activated recovery is compressed, so absolute SFT counts and hardening values likely overestimate what would be seen at experimental reactor dose rates even if the evolutionary sequence is preserved.
  • The observed stress-assisted coarsening implies that in polycrystalline aluminum, where grain boundaries act as sinks and constrain volume relaxation, the regime boundaries could shift; extending IKA to polycrystals would test whether the three-regime picture is intrinsic or cell-dependent.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

5 major / 6 minor

Summary. The paper presents an accelerated molecular dynamics strategy, the Iterative Kinetic Approach (IKA), for simulating radiation damage accumulation in single-crystal Al under 50 keV He irradiation. IKA inserts Frenkel-pair seeds calibrated by arc-dpa and relaxes the system for 35 ps per iteration, bypassing explicit cascade ballistic stages. The authors benchmark IKA against conventional cascade-overlap (CA) simulations up to ~0.061 dpa, showing comparable pair correlations and cluster-size distributions, though with a roughly factor-of-two higher total defect fraction at the same dpa. They then apply IKA alone to 0.175 dpa and identify three damage regimes: recombination-dominated annihilation, defect accumulation, and sink-controlled absorption. They further report Frank-loop dissociation into Shockley partials and stair-rod dislocations, nucleation and growth of stacking-fault tetrahedra (SFTs), and irradiation hardening predicted by the dispersed-barrier hardening model.

Significance. If the IKA high-dose predictions are trustworthy, the work offers a computationally efficient route to dose regimes inaccessible to conventional cascade-overlap MD and provides a mechanistic picture—three regimes, dislocation-mediated SFT formation, and hardening saturation—that is relevant to Al research-reactor materials. The benchmark effort is genuine and unusually detailed: the pair-correlation comparison at fixed dpa (R=0.998), the cluster-size distribution comparisons at multiple damage levels, and the explicit stress-relaxation control are strengths. The limitations section is candid about missing thermal-spike correlations, a single representative PKA, and high effective dose rate. However, the high-dose conclusions rest entirely on IKA and therefore on the premise that random, uncorrelated Frenkel-pair insertion preserves cascade evolution pathways beyond the validated dose range. The manuscript does not yet provide sufficient evidence for that premise, and some of the quantitative claims (SFT density, hardening magnitude) depend on under-documented approximations.

major comments (5)
  1. [Results: Dynamics of Defects (Fig. 1a)] The central validation is incomplete. The paper shows that at the same nominal 0.061 dpa, IKA produces roughly twice the total defect fraction of CA, and the authors mitigate this with pair-correlation and cluster-size comparisons. Those aggregate metrics do not constrain the extended-defect reactions—Frank-loop dissociation, stair-rod formation, SFT nucleation—that drive the high-dose narrative. All Regime II/III results, including Figs. 9d and 12, are IKA-only. The benchmark must be extended to at least the onset of the claimed Regime II (e.g., 0.09 dpa) or supplemented by a robustness test in which insertion correlations/relaxation times are varied and the high-dose pathway is shown to be insensitive. Without this, the claim that IKA 'reproduces the essential defect kinetics of cascade simulations' is not established for the damage range where the novel conclusions are drawn.
  2. [Methods: Iterative Kinetic Approach; Limitations paragraph] The IKA inserts 45 uncorrelated Frenkel pairs per event and relaxes for 35 ps (Eqs. 5–7), and the limitations paragraph explicitly acknowledges the absence of thermal-spike spatial correlations, a single representative PKA, and an effective dose rate of ~4.65×10^6 dpa/s. These are not merely residual limitations: they directly control the short-range reactions proposed in Regimes II and III. The paper also attributes the early IKA/CA cluster-size difference to the lack of ballistic spatial dispersion (Discussion). The authors should provide a sensitivity study—for example, varying the inter-event relaxation time, introducing spatially correlated FP insertion, or comparing with at least one cascade-overlap run past 0.09 dpa—to show that the Frank-to-Shockley-to-stair-rod/SFT pathway is not an artifact of uncorrelated FP accumulation or accumulated internal stress.
  3. [Dislocation Formation, Structure and Evolution (Fig. 9d, SFT counting)] The SFT population is estimated by dividing the total number of stair-rod segments by six (Methods, 'Damage Analysis and Outlook'). The paper acknowledges that not every stair-rod participates in a perfect tetrahedron, but this proxy is then used as the quantitative SFT density in Fig. 9d and as the SFT obstacle density in the hardening calculation. A stair-rod segment count divided by six can both overcount truncated/partial tetrahedra and undercount SFTs containing non-stair-rod dislocations. The authors should validate the proxy against direct structural identification (e.g., HCP-atom cluster analysis or tetrahedron-segment indexing) and report the uncertainty. This is load-bearing for the SFT nucleation claim and for the SFT hardening contribution in Fig. 13.
  4. [Quantitative irradiation hardening (Eqs. 8–11)] The hardening prediction is highly sensitive to obstacle strength factors α_i, which are stated only as 'assumed 0.1–0.5 for different obstacles' without a table mapping each defect type to its α_i. The total saturation hardening of 2.4–2.5 GPa depends on these undocumented choices. Additionally, M=3.06 is a polycrystalline Taylor factor, but the simulation is a single crystal; its use for single-crystal Al should be justified or replaced with an appropriate orientation-dependent Schmid factor. The authors should provide the full parameter set and a sensitivity analysis, and ideally compare the predicted Δσ with experimental radiation-hardening data for Al, to support the claim that the hardening picture describes Al behavior.
  5. [Results: Total Defect Concentration at High Damage (Eq. 1, Fig. 5)] Eq. (1) defines A_cum(d) = 1 − N_surv(d)/N_FP,ins(d), where N_surv includes atoms in clusters and dislocation cores. This quantity decreases only when defect atoms are removed from the off-lattice population, i.e., by recombination. Sink absorption that incorporates a defect into a dislocation or SFT does not, by itself, reduce N_surv. Therefore, the statement that the increase in annihilation fraction after 0.09 dpa is 'due to enhanced sink absorption rather than direct recombination' is not supported by the defined metric. The authors need a separate measure—e.g., absorption rate at dislocations or composition of annihilation events—to distinguish sink-mediated recombination from isolated Frenkel-pair recombination. This affects the physical interpretation of Regime III.
minor comments (6)
  1. [Discussion, stress-relaxation subsection] The text refers to 'Fig. 8 a and b' when comparing stressed and relaxed systems; these should be Fig. 14a and 14b.
  2. [Fig. 3 caption/text] The text describes 'a–g' for interstitial cluster distributions, but the figure shows only a–d; the cluster-size-range panels in e are described separately. Please correct the panel references.
  3. [Eq. (4)] The dpa expression is dimensionally unclear as written. Please define all symbols in one place and confirm that N_IKA is the cumulative number of iterations and that the factor 0.8 corresponds to the NRT model.
  4. [References] Reference 49 duplicates Reference 18 (Goryaeva et al., 'Compact A15 Frank-Kasper nano-phases'). Please consolidate.
  5. [Abstract and Introduction] The abstract states '50 keV He irradiation,' while the Methods use a 5 keV PKA derived from a 50 keV He ion via SRIM. This is likely correct but should be stated explicitly in the abstract or early in Results to avoid confusion.
  6. [Discussion, first paragraph] The sentence 'In Fig. 1c, the distinct evolution of the average cluster size...' should probably refer to Fig. 2c, not Fig. 1c.

Circularity Check

1 steps flagged

IKA benchmark is genuinely external, but the quantitative SFT density is self-definitional (SFT count ≡ stair-rod segments/6), so the SFT trend is partly a restatement of stair-rod growth.

specific steps
  1. self definitional [Dislocation Formation, Structure and Evolution (SFT estimation; Fig. 9d)]
    "By counting the total number of stair-rod segments in the simulation cell and dividing by six, we obtain an approximate SFT population 23. While not every stair-rod segment necessarily participates in a perfect tetrahedral assembly, making our SFT count somewhat of an approximation, this procedure gives a consistent, comparative metric for assessing relative SFT formation across damage states."

    The paper's quantitative SFT density (Fig. 9d, rising from ~0.5e24 to 8e24 m^-3) is defined as (number of 1/6<110> stair-rod segments)/6 per volume. Because the paper also reports a systematic increase in stair-rod segments through regimes II and III, the plotted SFT curve and the conclusion that 'the continued accumulation of stair-rod partials ... results in an increase in SFT nucleation and coalescence' are restatements of the same count, not independent predictions. The visual snapshots (Fig. 12) give qualitative support, but the quantitative SFT trend and the SFT hardening input are forced by the metric's definition.

full rationale

The central benchmarking claim is not circular: IKA's 45-FP seed is calibrated from an independent single cascade via arc-dpa, and the method is compared against conventional cascade-overlap simulations within the paper. The acknowledged ~2x defect-fraction offset at equal dpa is analyzed with pair-correlation and cluster statistics, which is a legitimate external check. The three regimes are descriptive classifications of the IKA output, not fitted inputs. The only internal circularity found is the SFT population metric: since SFT count is defined as stair-rod segments divided by six, the SFT density increase and the associated SFT hardening contribution reduce, by construction, to the stair-rod segment increase. This is a partial, metric-level circularity rather than a collapse of the whole derivation. The self-citation (ref. 86) is not load-bearing: it only provides implementation details, while validation is performed in this paper against cascade-overlap MD. The explicitly acknowledged limitations (no thermal-spike spatial correlations, single representative PKA, ~1e6 dpa/s effective rate) are correctness risks about extrapolation to high dose, not circularity. On balance, one definitional metric in an otherwise externally benchmarked study merits a moderate score.

Axiom & Free-Parameter Ledger

4 free parameters · 6 axioms · 0 invented entities

No new physical entities are introduced: IKA is a computational scheme, and the SFT count is an analysis proxy. The central results rest on calibrated FP seeds, the assumed equivalence between random-FP insertion and cascades, and the DXA/DBH analysis chain.

free parameters (4)
  • IKA Frenkel-pair seed = 45 FPs per iteration
    Calibrated from the arc-dpa estimate of a single 5 keV PKA cascade (Eqs. 2–3); sets the damage increment per iteration and therefore all dose-dependent results.
  • Inter-event relaxation time = 35 ps
    Chosen to mimic cascade cooling; controls the effective damage rate (Eq. 7) and the amount of diffusion/recombination between insertions.
  • Obstacle strength factors α_i = 0.1–0.5 (assumed range)
    Assigned to interstitial/vacancy clusters, SFTs, Frank, and Shockley loops in the DBH hardening model (Eq. 8); not independently fitted or measured.
  • Taylor factor M = 3.06
    Polycrystalline Taylor factor used in the single-crystal DBH estimate; may overestimate the stress conversion for a single crystal.
axioms (6)
  • domain assumption The Mishin EAM potential accurately represents point-defect and stacking-fault energetics in Al
    Selected by comparing elastic constants and stacking-fault energies with experiment; all defect and dislocation results depend on it.
  • domain assumption arc-dpa/NRT scaling maps a 50 keV He event to a 5 keV PKA and then to 45 stable Frenkel pairs
    Eqs. 2–4; determines the meaning of dpa and the number of FPs inserted per IKA event.
  • ad hoc to paper Random, uncorrelated insertion of Frenkel pairs followed by 35 ps NVT evolution reproduces cascade-overlap defect evolution pathways
    Central IKA premise; benchmarked only up to 0.061 dpa and showing a factor-of-two defect concentration offset, then used to 0.175 dpa.
  • ad hoc to paper Stair-rod dislocation segment count divided by six is a valid proxy for SFT population
    Used to produce Fig. 9d and the SFT hardening contribution; the paper acknowledges it is approximate and that HCP-atom filtering overestimates.
  • domain assumption DXA dislocation extraction correctly classifies partials and stair-rods at very high dislocation densities
    OVITO/DXA is used for all dislocation identification and stair-rod counting; reliability at densities above 1e17 m^-2 is not separately validated.
  • domain assumption The periodic simulation cell of 276,480 atoms is large enough to avoid significant image interactions of loops and SFTs
    Stated in Methods; no convergence study with larger cells is provided.

pith-pipeline@v1.3.0-alltime-deepseek · 27030 in / 14971 out tokens · 160394 ms · 2026-08-01T04:59:28.605390+00:00 · methodology

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read the original abstract

Aluminum alloys are widely used in research reactor systems, yet the mechanisms governing irradiation-induced degradation remain poorly understood. Here we combine conventional cascade-overlap molecular dynamics simulations with an accelerated Iterative Kinetic Approach (IKA) to investigate defect evolution in single-crystal Al subjected to 50 keV He irradiation. Benchmarking shows that IKA reproduces the essential defect kinetics of cascade simulations while enabling access to substantially higher accumulated damage. By extending the IKA to higher damage levels, we identified three distinct regimes governing radiation-induced degradation in Al: recombination-driven annihilation, defect accumulation, and sink-controlled absorption. At higher damage, Frank loops dissociate into Shockley partials and stair-rod loops, ultimately driving the nucleation and growth of stacking-fault tetrahedra (SFTs). These transformations progressively convert mobile defects into SFTs. Ultimately, the synergistic effect of interstitial and vacancy loops and SFTs increases irradiation hardening in Al at 300 K. This work provides insight into irradiation-induced degradation in aluminum reactor materials.

Figures

Figures reproduced from arXiv: 2607.22364 by Alhassan S. Issaka, Assel Aitkaliyeva, Michael R. Tonks, Sadie Wicks, Simon R. Phillpot, Vishal Yadav.

Figure 1
Figure 1. Figure 1: Comparison of defect evolution and microstructure predicted by IKA and CA simulations. a) Total defect fraction (off- [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 3
Figure 3. Figure 3: Comparing interstitial cluster size distribution from IKA and CA. Comparing the distributions of the number of interstitial clusters of various sizes from the IKA and CA for increasing amounts of damage from a) 0.0015 dpa, b) 0.0305 dpa, c) 0.0482 dpa, d) 0.0581 dpa and e) shows the fraction of clustered interstitials in 10 different size ranges. b c d e a [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Extension of the IKA defect concentration (fraction) evolution in Fig. 1a to higher damage. This is the defect concentration throughout the entire damage up to over 0.175 dpa, three times much damage than the CA. 𝐴𝑐𝑢𝑚(𝑑) = (1 − 𝑁𝑠𝑢𝑟𝑣 (𝑑) 𝑁𝐹𝑃,𝐼𝑛𝑠(𝑑) ) (1) where 𝐴𝑐𝑢𝑚(𝑑) is the cumulative annihilation fraction at damage d, 𝑁𝑠𝑢𝑟𝑣 (𝑑) is the total number of surviving defects at damage d, 𝑁𝐹𝑃,𝐼𝑛𝑠(𝑑) is the total… view at source ↗
Figure 6
Figure 6. Figure 6: Defect Clustering up to 0.175 dpa, a) Average cluster size as a function of increasing damage, b) fraction of all atoms involved in interstitial or vacancy clusters. The black dashed lines separate the three defect evolution regimes. Fig. 6a also presents the average interstitial cluster size as a function of damage and Fig. 6b the fraction of atoms in interstitial clusters. Unlike vacancy clusters, the av… view at source ↗
Figure 7
Figure 7. Figure 7: Cluster size distribution from the IKA among all the three damage regimes. Distribution of interstitial clusters at a) 0.0048 dpa, b) 0.0430 dpa, c) 0.1068 dpa and vacancy clusters at d) 0.0430 dpa, e)0.1068 dpa and f) ratio of the cluster count in the >41 and 2-4 cluster ranges (bins) as a function of damage(dpa). b d f a c e [PITH_FULL_IMAGE:figures/full_fig_p016_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Snapshots of the dislocation networks at different damage levels at a) 0.0152 dpa, b) 0.035 dpa, c) 0.054 dpa, d) 0.074 dpa, e) 0.094 dpa, f) 0.132 dpa, g) 0.164 dpa and h) showing a perfect individual SFT with core atoms and a coalesced or interacting SFTs showing slight changes in their orientation as damage increases. Blue, green, magenta, cyan, yellow, and red represent 1/2⟨110⟩ (perfect), 1/6⟨112⟩ (Sh… view at source ↗
Figure 10
Figure 10. Figure 10: Stitch-and-transform typed nucleation of Shockley loops. Atomic snapshots showing the evolution at a) 0.0268 dpa, b) 0.0280 dpa, c) 0.0286 dpa, d) 0.0290 dpa, e) 0.0293 dpa, f) 0.0299 dpa at increasing damage showing the first dislocation absorption/transformation mechanism. Two medium sized 1/3⟨111⟩ lying within a certain critical radius, partially transform into 1/6⟨110⟩ and eventually transform into 1/… view at source ↗
Figure 13
Figure 13. Figure 13: Hardening contribution from different obstacles. Irradiation induced hardening contribution from five different obstacles, Δ𝜎𝑖𝑛𝑡𝑒𝑟𝑠𝑡𝑖𝑡𝑖𝑎𝑙𝑠 , Δ𝜎𝑣𝑎𝑐𝑎𝑛𝑐𝑖𝑒𝑠 , Δ𝜎𝑆𝐹𝑇 , Δ𝜎𝐹𝑟𝑎𝑛𝑘 𝑝𝑎𝑟𝑡𝑖𝑎𝑙𝑠, Δ𝜎𝑆ℎ𝑜𝑐𝑘𝑙𝑒𝑦 𝑝𝑎𝑟𝑡𝑖𝑎𝑙𝑠 Discussion The current study considers only single-crystal Al. We recognize that previous studies have confirmed that the presence of multiple grain boundaries may lead to significant differences due to grai… view at source ↗
Figure 14
Figure 14. Figure 14: Comparison of the impact of stressed and stress relaxation from the IKA simulations. a) Number of interstitial clusters, b) Average interstitial cluster size plot for the stressed and relaxed systems, c) Fraction of the atoms in clusters normalized to their corresponding total defect, d) Fraction of isolated point defects normalized to their corresponding total defects. Plot of the total defects for both … view at source ↗
Figure 15
Figure 15. Figure 15: Schematic illustration of the irradiation-induced dislocation transformation mechanistic sequence in Al with accumulated damage. Here we show the evolution of damage and the corresponding microstructural changes as damage accumulates, from the initial formation of clusters of different sizes through different loop nucleation to the formation of SFT and their subsequent coalescence In regime III (high dama… view at source ↗
Figure 16
Figure 16. Figure 16: Schematic of the PKA simulation box with x, y, and z directions corresponding to the [100], [021], and [01ˉ 2] crystallographic directions. The bottom circles show the PKA region and the red arrow shows the direction of movement for the PKA. The IKA simulation cell has the same setup except that it does not involve the PKA region and direction defined here An adaptive time-step control is applied to ensur… view at source ↗

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