Collisions between amorphous carbon nanoparticles: phase transformations

2022

Sci Rep

Collisions of Lennard-Jones nanoparticles (NPs) may be used to study the generic collision behavior of NPs. We study the collision dynamics of amorphous NPs for oblique collisions using molecular dynamics simulation as a function of collision velocity and impact parameter. In order to allow for NP bouncing, the attraction between atoms originating from differing NPs is reduced. For near-central collisions, a finite region of velocities – a ‘bouncing window’ – exists where the 2 NPs bounce from each other. At smaller velocities, energy dissipation and – at larger velocities – also NP deformation do not allow the NPs to surpass the attractive forces such that they stick to each other. Oblique collisions of non-rotating NPs convert angular momentum into NP spin. For low velocities, the NP spin is well described by assuming the NPs to come momentarily to a complete stop at the contact point (‘grip’), such that orbital and spin angular momentum share the pre-collision angular momentum in a ratio of 5:2. The normal coefficient of restitution increases with impact parameter for small velocities, but changes sign for larger velocities where the 2 NPs do not repel but their motion direction persists. The tangential coefficient of restitution is fixed in the ‘grip’ regime to a value of 5/7, but increases towards 1 for high-velocity collisions at not too small impact parameters, where the 2 NPs slide along each other.

Section: Normal and Tangential Restitution Coefficientsmentioning

confidence: 99%

Bouncing and spinning of amorphous Lennard-Jones nanoparticles under oblique collisions

Nietiadi

2022

Sci Rep

“…-Aggregates of different materials: In addition to silica, there is a need for simulations that provide information on collisions between aggregates of other materials, such as ice -of particular interest in astrophysics granular collisions (Wada et al 2009;Kimura et al 2020) -and organic (carbon-based) matter (Nietiadi et al 2020b). Aggregates whose composition is a mixture of different materials (such as a silica core and a water shell) would also need to be considered (Nietiadi et al 2020a).…”

Section: Conclusion and Future Possibilitiesmentioning

confidence: 99%

A Monte Carlo code for the collisional evolution of porous aggregates (CPA)

Millán

Planes

et al. 2023

A&A

Self Cite

Context. The collisional evolution of submillimeter-sized porous dust aggregates is important in many astrophysical fields. Aims. We have developed a Monte Carlo code to study the processes of collision between mass-asymmetric, spherical, micron-sized porous silica aggregates that belong to a dust population. Methods. The Collision of Porous Aggregates (CPA) code simulates collision chains in a population of dust aggregates that have different sizes, masses, and porosities. We start from an initial distribution of granular aggregate sizes and assume some collision velocity distribution. In particular, for this study we used a random size distribution and a Maxwell-Boltzmann velocity distribution. A set of successive random collisions between pairs of aggregates form a single collision chain. The mass ratio, filling factor, and impact velocity influence the outcome of the collision between two aggregates. We averaged hundreds of thousands of independent collision chains to obtain the final, average distributions of aggregates. Results. We generated and studied four final distributions (F), for size (n), radius (R), porosity, and mass-porosity distributions, for a relatively low number of collisions. In general, there is a profuse generation of monomers and small clusters, with a distribution F (R) ∝ R−6 for small aggregates. Collisional growth of a few very large clusters is also observed. Collisions lead to a significant compaction of the dust population, as expected. Conclusions. The CPA code models the collisional evolution of a dust population and incorporates some novel features, such as the inclusion of mass-asymmetric aggregates (covering a wide range of aggregate radii), inter-granular friction, and the influence of porosity.

“…Collisions between dust grains are relevant for the grain-size distribution in dust clouds and disks: Sticking collisions lead to dust agglomeration, while bouncing -or even fragmenting -collisions may prevent the formation of larger entities in the clouds. While collisions between silica and ice particles have often been studied, both by experiment and simulation (Dominik & Tielens 1997;Blum 2010Blum , 2018, our knowledge of collisions between carbonaceous grains is still poor (Nietiadi et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Bouncing and sticking collisions of organic nanoparticles: Atomistic study

Anders

2021

A&A

Self Cite

Context. Whether nanoparticles bounce or stick during collisions determines whether particles grow or fragment, hence shaping collision-induced agglomeration processes. The collision behavior of organic matter may strongly differ from that of silica or ice grains. Aims. We explore the microscopic processes underlying the bouncing behavior of organic nanoparticles. Methods. Molecular dynamics simulations based on a reactive potential, which follow molecular motion on an atomistic scale, are used. Results. For the exemplary case of glycolic acid molecules, warm nanoparticles (250 K) always show sticking, while at low velocities (2.5 m s−1) cold nanoparticles (100 K) exhibit a considerable probability for bouncing. This behavior can be traced back to the distant electrostatic repulsion of the nanoparticles at certain orientations; this prevents a closer approach, during which van der Waals and H-bonded interactions would lead to sticking. At higher temperatures, molecular vibrations and conformational flexibility average over the nanoparticle interaction, such that attraction dominates and bouncing is prevented. Our results are in qualitative agreement with laboratory experiments. Conclusions. Organic matter distinctly influences the collision behavior of nanoparticles.