Open Access
Issue
A&A
Volume 670, February 2023
Article Number L21
Number of page(s) 10
Section Letters to the Editor
DOI https://doi.org/10.1051/0004-6361/202345887
Published online 22 February 2023

© The Authors 2023

Licence Creative CommonsOpen Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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1. Introduction

Collisional growth of dust aggregates consisting of micro- or nanosized grains is ubiquitous in the Universe. For example, collisional growth of soot nanoparticles produced by combustion processes is important in environmental science and engineering (e.g., Haynes & Wagner 1981). Atmospheric hazes on the early Earth and other planetary bodies are also dust aggregates consisting of micro- or nanosized particles, and their collisional growth affects the atmospheric structure (e.g., Trainer et al. 2006; Zhang et al. 2017; Ohno et al. 2021). The first step of planet formation in circumstellar disks is collisional growth of micro- or nanosized interstellar dust particles (e.g., Hayashi et al. 1985; Drazkowska et al. 2022), and dust growth might also trigger the formation of planetary objects around supermassive black holes in a galactic center (e.g., Wada et al. 2021).

The condition for collisional growth of dust aggregates has been studied with laboratory experiments (e.g., Blum & Wurm 2008; Güttler et al. 2010; Fritscher & Teiser 2021; Schräpler et al. 2022) and numerical simulations (e.g., Wada et al. 2009; Seizinger et al. 2013; Hasegawa et al. 2021; Osinsky & Brilliantov 2022). Previous studies found that the conditions for growth or fragmentation depend on the strength of interparticle forces that act on constituent particles that are in contact with each other.

Wada et al. (2009) performed a large number of numerical simulations of collisions between two equal-mass dust aggregates consisting of submicron-sized spherical ice particles. They varied the collision velocities and impact angles and obtained the collisional growth efficiency. Their numerical simulations revealed that the threshold velocity for collisional growth or fragmentation of dust aggregates, vfra, is approximately 60 m s−1 when the radius of the constituting particles is 0.1 μm and the initial aggregates before collisions are prepared by ballistic particle–cluster aggregation (BPCA; Mukai et al. 1992). The authors also predicted that vfra would be proportional to the square root of the energy required for breaking one interparticle contact, Ebreak, which is related to the connection or disconnection of particles due to interparticle normal motion (e.g., Dominik & Tielens 1997; Wada et al. 2007).

Arakawa et al. (2022b) also performed numerical simulations of collisions between dust aggregates and investigated the dependence of the threshold velocity on the strength of the viscous dissipation. They found that the main energy dissipation mechanism is not the normal interaction (i.e., viscous dissipation and connection or disconnection of particles), but the rolling friction between particles that are in contact.

Then Arakawa et al. (2022a) investigated the dependence of the threshold velocity on the strength of rolling friction. They revealed that the threshold velocity only very weakly depends on the strength of rolling friction, however. In their simulations, frictions arising from two other tangential motions (sliding and twisting) complemented the change in energy dissipation due to rolling friction.

Energy dissipation is essentially required for the collisional growth of dust aggregates. The results of Arakawa et al. (2022a,b) indicate that the threshold velocity for collisional growth or fragmentation are affected by the presence or absence of interparticle tangential frictions when the motions cannot complement one another.

Here, we report numerical simulations of collisions between two equal-mass dust aggregates consisting of submicron-sized spherical ice particles, with and without interparticle friction. We also systematically varied the collision velocities and impact angles, and we calculated the collisional growth efficiency by averaging over impact angles. We confirm that the collisional growth efficiency of dust aggregates clearly depends on the presence or absence of interparticle frictions associated with tangential motions. Our results indicate that the dependence of the collisional growth efficiency on the material properties of constituent particles is more complex than previously assumed.

2. Model

We performed three-dimensional numerical simulations of collisions between two equal-mass dust aggregates. Our numerical code was originally developed by Wada et al. (2007), and Arakawa et al. (2022b) introduced a viscous drag force for normal motion (e.g., Krijt et al. 2013). We prepared two initial aggregates before collisions by BPCA as in previous studies (Wada et al. 2009; Arakawa et al. 2022b,a). We set the number of particles in the target aggregate, Ntar, equal to that for the projectile aggregate, Npro, and the total number of particles in a simulation, Ntot = Ntar + Npro, was 100 000. The constituent dust particles were made of water ice, and the particle radius was r1 = 0.1 μm. The particle interaction model is briefly described in Appendix A.

The strength of interparticle normal dissipation is controlled by a parameter called the viscoelastic timescale, Tvis (e.g., Arakawa et al. 2022b). We performed numerical simulations with two models for interparticle normal dissipation: with dissipation (Tvis = 6 ps), and without dissipation (Tvis = 0 ps; see Appendix A.1).

The strengths of the interparticle tangential friction are characterized by the spring constants for rolling (kr), sliding (ks), and twisting (kt). In this study, we also performed numerical simulations with two models for interparticle tangential motions: frictional and frictionless models. In the frictional model, we considered the interparticle tangential interactions as modeled by Wada et al. (2007), and we used the same values of kr, ks, and kt as assumed in Wada et al. (2007). In the frictionless model, in contrast, we did not consider the interparticle tangential frictions; in other words, we set kr = ks = kt = 0 (see Appendix A.2).

3. Results

Figure 1 shows snapshots of the collisional outcomes. We show the numerical results for the frictionless model (kr = ks = kt = 0) without normal dissipation (Tvis = 0 ps), and we set vcol = 39.8 m s−1, where vcol is the collision velocity of two dust aggregates. We found that the collisional behavior strongly depends on the impact angles. Comparing Fig. 1c with Fig. 2 of Arakawa et al. (2022a), we can visually understand that the collisional behavior also depends on the interparticle interaction model. Arakawa et al. (2022a) presented the results for the same collision velocity and impact angle, but used the frictional model with normal dissipation. In contrast, Fig. 1c of this study shows the results for the frictionless model without normal dissipation. We found that the number of small fragments significantly increases compared to the results of Arakawa et al. (2022a).

thumbnail Fig. 1.

Snapshots of the collisional outcomes. We show the numerical results for the frictionless model (kr = ks = kt = 0) without normal dissipation (Tvis = 0 ps), and we set vcol = 39.8 m s−1. Panels (a)–(d) are the time series of snapshots for , 3/12, 6/12, and 9/12, respectively. The time interval for each snapshot is 0.40 μs.

In this study, we use the normalized impact parameter, Boff, to quantify the offset of oblique collisions. We defined Boff as Boff = boff/bmax, where boff is the impact parameter and bmax is the sum of the radii of the target and projectile aggregates (see Arakawa et al. 2022b). The radius of the dust aggregates was set equal to the characteristic radius, rc, which is given by , where rg is the gyration radius (e.g., Mukai et al. 1992; Wada et al. 2009). It is clear that for head-on collisions, and ranges from 0 to 1.

When collisions in space are considered, the impact parameter should vary with each collision event. The average value of a variable A weighted over Boff,

(1)

is useful to measure the average outcome of the collision.

3.1. Collisional growth efficiency and the threshold velocity for collisional growth or fragmentation

Figure 2 shows the Boff-weighted collisional growth efficiency, ⟨fgro⟩, as a function of vcol for different particle interaction models. The growth efficiency, fgro, was defined for each simulation, and it is given by fgro = (Nlar − Ntar)/Npro, where Nlar denotes the number of constituent particles in the largest remnant (see Hasegawa et al. 2021). The collisional outcome of each simulation is summarized in Fig. B.1.

thumbnail Fig. 2.

Boff-weighted collisional growth efficiency, ⟨fgro⟩. We note that the results for frictional models (gray lines) are identical to those presented in Fig. 3 of Arakawa et al. (2022b) for vcol ≥ 20.0 m s−1.

We found that ⟨fgro⟩ clearly depends on the choice of particle interaction models. In our simulation of the frictional model without normal dissipation (solid gray line), ⟨fgro⟩ ≃ 0 at approximately vcol = 60 m s−1. Wada et al. (2009) also performed simulations with the same particle interaction model, and their result is in excellent agreement with ours. We defined the threshold velocity for collisional growth or fragmentation, vfra, as the collision velocity that satisfies ⟨fgro⟩ = 0.

In the frictional model with normal dissipation (dashed gray line), we found that vfra ≃ 50 m s−1, which is close to the value for the frictional model without normal dissipation. The dependence of ⟨fgro⟩ on vcol in frictional models with and without normal dissipation is similar; their difference in ⟨fgro⟩ is typically smaller than 0.1 in the range of 10 m s−1vcol ≤ 100 m s−1. Arakawa et al. (2022b) concluded that this independence of ⟨fgro⟩ on the presence or absence of normal dissipation is consistent with the fact that the main energy dissipation mechanism is not normal dissipation, but interparticle tangential friction when frictional models are used for particle interaction.

In frictionless models, however, we found that vfra is significantly lower than that of frictional models, for example, vfra ≃ 30 m s−1 in the frictionless model without normal dissipation (solid red line). In addition, ⟨fgro⟩ also decreases compared to the frictional models. For example, 0.1 ≲ ⟨fgro⟩ ≲ 0.2 at vcol = 15.8 m s−1 in frictionless models, while 0.8 ≲ ⟨fgro⟩ ≲ 0.9 at the same vcol in frictional models. These differences would be related to the difference in energy dissipation processes (see Appendix C).

We note that vfra depends on the presence or absence of normal dissipation when tangential frictions are absent. In the frictionless model with normal dissipation (dashed red line), our numerical results show that vfra ≃ 45 m s−1, which is 1.5 times higher than that of the frictionless model without normal dissipation. Figure 2 shows that ⟨fgro⟩ for the frictionless model with normal dissipation is significantly higher than that of the frictionless model without normal dissipation in the ranges of vcol ≪ 20 m s−1 and vcol ≫ 60 m s−1, although their difference in ⟨fgro⟩ is roughly within 0.1 in the intermediate range of vcol.

Based on the results of Wada et al. (2009), Wada et al. (2013) proposed an empirical formula to estimate vfra as a function of the particle radius and material properties of constituting particles. The empirical formula is , where m1 is the mass of each particle. As both Ebreak and m1 are independent of the spring constants for tangential motions (kr, ks, and kt), this equation cannot express the effects of tangential interactions on vfra. Our numerical results, however, highlight the impact of tangential interactions on vfra. Thus we need to modify the prediction formula for vfra.

Our results indicate that vfra depends not only on Ebreak, but also on interparticle energies associated with tangential motions. It is important to note that their dependences on the particle radius and material properties are different from each other (see Wada et al. 2007). For example, Ebreak is proportional to (see Appendix A.1), while the energy needed to slide a particle by π/2 radian around its contact point, Eslide, is proportional to . The energy needed to twist over π/2 radian, Etwist, is proportional to (see Appendix A.2). Although it seems an extreme and unrealistic assumption, vfra might be proportional to when it is proportional to , or vfra might be proportional to when it is proportional to .

Blum & Wurm (2008) reviewed laboratory experiments of collisions of dust aggregates and reported that the threshold velocity for the sticking of dust aggregates is proportional to , with x ≳ 1 for 0.1 μm ≲ r1 ≲ 1 μm and x ≲ 1 for 1 μm ≲ r1 ≲ 10 μm. Although these experimental results are for head-on collisions and cannot be directly compared with our Boff-weighted numerical results, we can speculate that the dependence of vfra on r1 might not be given by a simple power-law relation.

3.2. Size distribution of fragments

As shown in Fig. 1, collisions of dust aggregates consisting of frictionless particles without normal dissipation (kr = ks = kt = 0 and Tvis = 0 ps) produce a large number of small fragments. In circumstellr disks, the strength of turbulence driven by magnetorotational instability is a function of the gas ionization degree and depends on the number of small dust aggregates (e.g., Okuzumi & Hirose 2012). Thus, the number of small dust aggregates might also be the key parameter for planet formation via collisional growth of dust aggregates. Here, we quantify the size distribution of fragments in our simulations (see also Arakawa et al. 2022b; Hasegawa et al. 2022; Osinsky & Brilliantov 2022).

Arakawa et al. (2022b) defined Ncum(≤N) as the cumulative number of particles that are constituents of fragments that contain not more than N particles. Figure 3 shows the Boff-weighted average of Ncum(≤N), ⟨Ncum(≤N)⟩. We found that ⟨Ncum(≤N)⟩ significantly differs among particle interaction models.

thumbnail Fig. 3.

Boff-weighted average of Ncum(≤N), ⟨Ncum(≤N)⟩. (a) For the case of vcol = 20 m s−1. (b) For the case of vcol = 39.8 m s−1.

As shown in Fig. 3, the size distributions of fragments for frictional models with and without normal dissipations (dashed and solid gray lines, respectively) are similar, particularly for larger fragments (N > 10 for vcol = 20 m s−1 and N > 103 for vcol = 39.8 m s−1). This trend is consistent with the results of Arakawa et al. (2022b).

We found that the number of small fragments strongly depends on the presence or absence of interparticle tangential friction. When we apply the frictionless model without normal dissipation for constituting particles (solid red line), the number of small fragments with N < 102 was orders of magnitude larger than that of the frictional models. This difference might also imply the importance of interparticle tangential frictions on the energy dissipation and deformation of dust aggregates during collision.

We note that for frictionless models, the size distribution of fragments clearly depends on the strength of normal dissipation (Tvis). When we consider vcol = 20 m s−1 as an example, the difference in ⟨fgro⟩ is small (approximately 0.1; Fig. 2), but the difference in ⟨Ncum(≤N)⟩ is approximately two orders of magnitude for N < 102. These simulation results might indicate that the mechanisms for aggregate-wide deformation and the ejection of small fragments are different. We will test this hypothesis in future studies.

4. Conclusions

Understanding the collisional behavior of dust aggregates consisting of micro- or nanosized grains is essential for understanding planet formation. The threshold velocity for collisional growth or fragmentation, vfra, is one of the most important parameters that controls the size of dust aggregates in circumstellar disks (e.g., Okuzumi & Tazaki 2019; Arakawa et al. 2021), but the dependence of vfra on the particle radius and the material properties of constituting particles is still under debate.

Arakawa et al. (2022a,b) revealed that the main energy dissipation mechanism for oblique collisions of dust aggregates is not the interparticle normal interaction (i.e., connection and disconnection of particles), but the tangential friction between particles in contact with each other. Thus, we expect that the collisional outcomes of dust aggregates could depend on the strength of interparticle frictions.

In this study, we demonstrated that vfra depends on the strength of tangential interactions using numerical simulations of collisions between dust aggregates. We tested 2 × 2 = 4 types of particle interaction models in this study. In these models, the presence or absence of the interparticle tangential frictions is captured by differences in the spring constants (kr, ks, and kt), and the presence or absence of the normal dissipation is captured by differences in the viscoelastic timescale (Tvis).

In the frictional model without normal dissipation, we found that vfra ≃ 60 m s−1, which is consistent with what has been reported in previous studies (e.g., Wada et al. 2009; Hasegawa et al. 2021). In contrast, in the frictionless model without normal dissipation, we found that vfra ≃ 30 m s−1, which is notably lower than for the frictional model (see Fig. 2). We also found that vfra depends on the presence or absence of the normal dissipation when tangential frictions are absent, while vfra is nearly independent of Tvis for frictional models. Our results further indicate that the dependence of vfra on the particle radius and material properties cannot be described by a simple power-law relation (see Blum & Wurm 2008; Wada et al. 2009, 2013). Future studies of this point are essential, although a large number of numerical simulations are needed to construct a better fitting formula to predict vfra as a function of particle radius and material properties.

The size distribution of fragments also depends on the choice of particle interaction models (see Fig. 3). As shown in Fig. 1, collisions of dust aggregates consisting of frictionless particles without normal dissipation produce a large number of small fragments. We also found that for frictionless models, the size distribution of fragments significantly depends on the strength of normal dissipation, even if the difference in ⟨fgro⟩ is small. Our results might indicate that the mechanisms for aggregate-wide deformation and the ejection of small fragments are different, although we need to investigate this hypothesis in future studies.

Acknowledgments

The anonymous reviewer provided a constructive review that improved this paper. Numerical computations were carried out on PC cluster at CfCA, NAOJ. H.T. and E.K. were supported by JSPS KAKENHI grant No. 18H05438. We thank American Journal Experts (AJE) for English language editing.

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Appendix A: Particle interaction model

Here, we briefly explain the particle interaction model used in this study. Details are described in Wada et al. (2007) and Arakawa et al. (2022b).

A.1. Normal motion

We assume that the normal force acting between two particles, F, is given by the sum of the two terms

(A.1)

where FE denotes the force arising from the elastic deformation of particles, and FD is the force related to the viscous dissipation.

When two particles in contact are elastic spheres with a surface energy, the elastic term is given by the following equation (Johnson et al. 1971):

(A.2)

where a is the contact radius, a0 is the contact radius at equilibrium, Fc = 3πγR is the maximum force needed to separate the two particles in contact, γ is the surface energy, and R = r1/2 is the reduced particle radius. At the equilibrium state, a0 is given by

(A.3)

where ℰ* is the reduced Young modulus.

The contact radius is a function of the compression length between two particles in contact, δ, and vice versa,

(A.4)

where is the equilibrium compression length at a = a0. Two particles in contact separate when the compression length reaches a critical length, δ = −δc, where δc = (9/16)1/3δ0.

The viscous drag force is given by

(A.5)

where ν is Poisson’s ratio, vrel is the normal component of the relative velocity of the two particles, and Tvis is the viscoelastic timescale (see Krijt et al. 2013).

In this study, we considered two cases: Tvis = 0 ps and Tvis = 6 ps. We set Tvis = 6 ps in our previous studies (e.g., Arakawa et al. 2022a), and the choice of Tvis = 6 ps was motivated by extrapolation of laboratory experiments (see Figure 5 of Arakawa & Krijt 2021). Krijt et al. (2013) predicted that Tvis would be approximately proportional to R, and Arakawa & Krijt (2021) confirmed this relation using experimental results of Gundlach & Blum (2015) and Musiolik et al. (2016).

The potential energy for the normal motion of the two particles in contact, Un, is given by

(A.6)

The energy needed to break a contact in equilibrium by a quasistatic process (i.e., vrel → 0 and FD → 0), Ebreak, is

(A.7)

and Ebreak is proportional to .

A.2. Tangential motion

The tangential motion of two particles in contact is the combination of three motions: rolling, sliding, and twisting. The displacements corresponding to these motions are described as the rotation of two particles in contact. Wada et al. (2007) provided the particle interaction model for these tangential motions (see also Dominik & Tielens 1995, 1996), which is equivalent to the linear spring model with critical displacements to their elastic limits. The concept of the tangential interaction model is summarized in Figures 2 and 3 of Wada et al. (2007).

A.2.1. Rolling motion

The spring constant for the rolling displacement, ξ, is kr. For the frictional model, we set

(A.8)

and we set kr = 0 for the frictionless model. The energy needed to rotate a particle by π/2 radian around its contact point, Eroll, is useful for interpreting the collisional outcomes of dust aggregates from energetics (e.g., Dominik & Tielens 1997). Wada et al. (2007) derived that Eroll is given by

(A.9)

where ξcrit is the critical rolling displacement. In this study, we set ξcrit = 0.8 nm for water ice particles of r1 = 0.1 μm. The dependence of ξcrit on r1 is poorly understood, however (see Arakawa et al. 2022a, and references therin).

A.2.2. Sliding motion

The spring constant for the sliding displacement, ζ, is ks. For the frictional model, we set

(A.10)

where 𝒢 = 𝒢/[2(2 − ν)], and 𝒢 is the shear modulus. We set ks = 0 for the frictionless model, as is the case for kr. The critical sliding displacement, ζcrit, is given by ζcrit = [(2 − ν)/(16π)]a0 (Wada et al. 2007). The energy needed to slide a particle by π/2 radian around its contact point, Eslide, is given by

(A.11)

and Eslide is proportional to .

A.2.3. Twisting motion

The spring constant for the twisting displacement, ϕ, is kt. For the frictional model, we set

(A.12)

where 𝒢′ = 𝒢/2 is the reduced shear modulus. We set kt = 0 for the frictionless model, as is the case for kr and ks. The critical angle for twisting, ϕcrit, is set to ϕcrit = 1/(16π) (Wada et al. 2007). The energy needed to twist over π/2 radian, Etwist, is given by

(A.13)

and Etwist is proportional to .

Appendix B: Collisional growth efficiency

Figure B.1 shows the collisional growth efficiency, fgro. The square of the normalized impact parameter ranges from to 1 with an interval of 1/12. The collision velocity was set to 10(0.1i) m s−1, where i = 10, 11, ..., 20. Each panel shows fgro for different particle interaction models. The gray lines in Figure B.1 are the Boff-weighted collisional growth efficiency, ⟨fgro⟩, and they are identical to those shown in Figure 2.

thumbnail Fig. B.1.

Collisional growth efficiency, fgro, for different settings of Boff and vcol. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

Appendix C: Energy dissipation and interparticle connection or disconnection

We briefly check the energy dissipation in our simulations (Appendix C.1). In addition, we also show the numbers of connection and disconnection events (Appendix C.2).

C.1. Energy dissipation

Figure C.1 shows the total energy dissipation due to particle interactions from the start to the end of the simulations, Edis, tot (see also Figure 8 of Arakawa et al. 2022a). For frictionless models, Edis, tot is given by Edis, tot = Edis, c + Edis, v, where Edis, c is the energy dissipation due to the connection and disconnection of particles and Edis, v is the energy dissipation due to the viscous drag force. The dashed gray line denotes the initial kinetic energy.

thumbnail Fig. C.1.

Total energy dissipation due to particle interactions from the start to the end of the simulations, Edis, tot, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation. The dashed gray line denotes the initial kinetic energy (see Arakawa et al. 2022a).

The relation between Edis, tot and fgro is complex. At approximately vcol = 10 m s−1, Edis, tot for frictionless models is larger than that for frictional models, but ⟨fgro⟩ for frictionless models is lower than that for frictional models (see Figure 2). For and vcol = 100 m s−1, Edis, tot is nearly equal to the initial kinetic energy in Figures C.1(a), C.1(b), and C.1(d), and fgro ∼ 1 in these cases (see Figure B.1). In contrast, Edis, tot is significantly lower than the initial kinetic energy in Figure C.1(c), and the corresponding growth efficiency is fgro ∼ −1 in this case.

Figure C.2 shows Edis, c as a function of vrel and Boff. We note that Edis, c is identical to Edis, tot for the frictionless model without normal dissipation (Figure C.2(c)). It is clear that Edis, c for frictionless models is higher than that for frictional models in the range of 10 m s−1vcol ≤ 100 m s−1. For frictional models, the fraction of energy dissipation due to the connection and disconnection of particles is notably small: Edis, c/Edis, tot ≪ 1. This is because the main energy dissipation mechanism for collisions of dust aggregates is the tangential friction between particles that are in contact for frictional models (Arakawa et al. 2022b,a).

thumbnail Fig. C.2.

Energy dissipation due to connection and disconnection of particles, Edis, c, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation. The dashed gray line denotes the initial kinetic energy.

C.2. Interparticle connection and disconnection

We also verified the numbers of connection and disconnection events, as they are directly related to Edis, c. Figures C.3 and C.4 show the numbers of connection and disconnection events in a collision between dust aggregates, Ncon and Ncut, respectively (see also Figure 15 of Arakawa et al. 2022b).

thumbnail Fig. C.3.

Number of connection events in a collision between dust aggregates, Ncon, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

thumbnail Fig. C.4.

Number of disconnection events in a collision between dust aggregates, Ncut, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

For frictionless models, Ncon is larger than Ntot in the range of 10 m s−1vcol ≤ 100 m s−1 (Figures C.3(c) and C.3(d)). In contrast, Ncon is smaller than Ntot for frictionless models at approximately vcol = 10 m s−1 (Figures C.3(a) and C.3(b)). The large difference in Ncon would be related to the difference in the degree of deformation of aggregates after collisions.

For the frictionless model without normal dissipation, not only Ncon but also Ncut exceeds Ntot in the entire range of 10 m s−1vcol ≤ 100 m s−1 (Figure C.4(c)). For other models, Ncut is significantly smaller than Ntot at approximately vcol = 10 m s−1 (Figures C.4(a), C.4(b), and C.4(d)). As shown in Figure 2, ⟨fgro⟩ for the frictionless model without normal dissipation is notably lower than for the other three models. We therefore hypothesize that the dependence of ⟨fgro⟩ on vcol might be the key to understanding the large difference in vfra among particle interaction models.

All Figures

thumbnail Fig. 1.

Snapshots of the collisional outcomes. We show the numerical results for the frictionless model (kr = ks = kt = 0) without normal dissipation (Tvis = 0 ps), and we set vcol = 39.8 m s−1. Panels (a)–(d) are the time series of snapshots for , 3/12, 6/12, and 9/12, respectively. The time interval for each snapshot is 0.40 μs.

In the text
thumbnail Fig. 2.

Boff-weighted collisional growth efficiency, ⟨fgro⟩. We note that the results for frictional models (gray lines) are identical to those presented in Fig. 3 of Arakawa et al. (2022b) for vcol ≥ 20.0 m s−1.

In the text
thumbnail Fig. 3.

Boff-weighted average of Ncum(≤N), ⟨Ncum(≤N)⟩. (a) For the case of vcol = 20 m s−1. (b) For the case of vcol = 39.8 m s−1.

In the text
thumbnail Fig. B.1.

Collisional growth efficiency, fgro, for different settings of Boff and vcol. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

In the text
thumbnail Fig. C.1.

Total energy dissipation due to particle interactions from the start to the end of the simulations, Edis, tot, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation. The dashed gray line denotes the initial kinetic energy (see Arakawa et al. 2022a).

In the text
thumbnail Fig. C.2.

Energy dissipation due to connection and disconnection of particles, Edis, c, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation. The dashed gray line denotes the initial kinetic energy.

In the text
thumbnail Fig. C.3.

Number of connection events in a collision between dust aggregates, Ncon, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

In the text
thumbnail Fig. C.4.

Number of disconnection events in a collision between dust aggregates, Ncut, as a function of vrel and Boff. (a) For the frictional model without normal dissipation. (b) For the frictional model with normal dissipation. (c) For the frictionless model without normal dissipation. (d) For the frictionless model with normal dissipation.

In the text

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