The air flows in the proximal and distal portions of the human lungs are interconnected: the lower Reynolds number in the deeper generations causes a progressive flow regularization, but mass conservation requires flow rate oscillations to propagate through the airway bifurcations. To explain how these competing effects shape the flow state in the deeper generations, we have performed the first high-fidelity numerical simulation of the air flow in a lung model that includes 23 successive bifurcations of a single planar airway. Turbulence modeling or assumptions on flow regimes are not required. The chosen flow rate is steady on average, and representative of the peak inspiratory flow reached by adult patients breathing through therapeutic inhalers. As expected, advection becomes progressively less important after each bifurcation, until a time-dependent Stokes regime governed solely by viscous diffusion is established in the smallest generations. However, fluctuations in this regime are relatively fast and large with respect to the mean flow, which is in contrast with the commonly agreed picture that only the breathing frequency is relevant at the scale of the alveoli. We demonstrate that the characteristic frequency and amplitude of these fluctuations are linked to the flow in the upper part of the bronchial tree, as they originate from the time-dependent flow splitting in the upper bifurcations. Even though these fluctuations are observed here in an idealized, rigid lung model, our findings suggest that the assumptions usually adopted in many of the current lung models might need to be revised.

A detailed picture of how an aerosol is transported and deposited in the self-affine bronchial tree structure of patients is fundamental to design and optimize orally inhaled drug products. This work describes a Monte Carlo-based statistical deposition model able to simulate aerosol transport and deposition in a 3D human bronchial tree. The model enables working with complex and realistic inhalation maneuvers including breath-holding and exhalation. It can run on fully stochastically generated bronchial trees as well as on those whose proximal airways are extracted from patient chest scans. However, at present, a mechanical breathing model is not explicitly included in our trees; their ventilation can be controlled by means of heuristic airflow splitting rules at bifurcations and by an alveolation index controlling the distal lung volume. Our formulation allows us to introduce different types of pathologies on the trees, both those altering their morphology (e.g., bronchiectasis and chronic obstructive pulmonary disease) and those impairing their function (e.g., interstitial lung diseases and emphysema). In this initial activity we describe deposition and ventilation models as well as the stochastic tree construction algorithm, and we validate them against total, regional, lobar, and sub-lobar deposition for healthy subjects.

In this work we present, for the first time, a computational fluid dynamics tool for the simulation of the metered discharge in a pressurized metered dose inhaler. The model, based on open-source software, adopts the Volume-Of-Fluid method for the representation of the multiphase flow inside the device and a cavitation model to explicitly account for the onset of flashboiling upon actuation. Experimental visualizations of the flow inside the device and measurements of the mixture density and liquid and vapor flow rates at the nozzle orifice are employed to validate the model and assess the sensitivity of numerical results to modeling parameters. The results obtained for a standard device geometry show that the model is able to quantitatively predict several aspects of the dynamics and thermodynamics of the metered discharge. We conclude by showing how, by allowing to reproduce and understand the fluid dynamics upstream of the atomizing nozzle, our computational tool enables systematic design and optimization of the actuator geometry.

The reliability and accuracy of numerical models and computer simulations to study aerosol deposition in the human respiratory system is investigated for a patient-specific tracheobronchial tree geometry. A computational fluid dynamics (CFD) model coupled with discrete elements methods (DEM) is used to predict the transport and deposition of the aerosol. The results are compared to experimental and numerical data available in the literature to study and quantify the impact of the modeling parameters and numerical assumptions. Even if the total deposition compares very well with the reference data, it is clear from the present work how local deposition results can depend significantly upon spatial discretization and boundary conditions adopted to represent the respiratory act. The modeling of turbulent fluctuations in the airflow is also found to impact the local deposition and, to a minor extent, the flow characteristics at the inlet of the computational domain. Using the CFD-DEM model, it was also possible to calculate the airflow and particles splitting at bifurcations, which were found to depart from the assumption of being equally distributed among branches adopted by some of the simplified deposition models. The results thus suggest the need for further studies towards improving the quantitative prediction of aerosol transport and deposition in the human airways.

Jet-milling is a particle engineering process widely adopted in industrial manufacturing to reduce the particle size of powders. Computational Fluid Dynamics simulations (CFD) coupled with Discrete Element Modelling (DEM) proved to be a valuable tool to tackle the complexity and the non-linearity of particle breakage and classification occurring in mills. To date however, they have been employed to address only single aspects of process design being unable to reproduce it completely. The coupled CFD-DEM simulations presented in this work are for the first time capable of simultaneously describe particle fragmentation, particle-gas interaction and classification. Through coarse-graining, realistic amounts of powder can be simulated allowing to demonstrate/study how the hold-up mass slows down the milling gas affecting classification and thus the milling performance. Bottlenecks/limitations of model and methodology are critically examined to understand what is currently preventing us from creating a digital twin of the milling process.

A critical evaluation of the impact of the Multiple Reference Frame (MRF) technique on steady RANS simulations of a Rushton turbine stirred-tank is presented. The analysis, based on the open-source software OpenFOAM, is focused on the choice of the diameter and thickness of the MRF region and on their effect on the predicted velocity field and mixing times in the tank. Five diameters of the MRF region are compared for the same operating conditions of the turbine, showing limited differences in velocity profiles, which are found in general good agreement with available experimental data. Significant differences are nonetheless found in the predicted levels of turbulence intensity within the tank, with a considerable amount of artificially generated turbulence at the boundary of the MRF region for the largest diameters. The impact of the different predictions of the turbulent field on the modeling of the mixing process in the tank is evaluated by simulating the release of a passive scalar, using the frozen-flow field hypothesis. The results show changes in mixing times up to a factor of three when comparing MRF regions of different sizes. Thus, the present investigation highlights the importance of assessing the effect of the MRF zone size on numerical results as a standard practice in RANS based simulations of stirred-tanks.

Powder deaggregation in Dry Powder Inhalers (DPI) with carrier-based formulations is a key process for the effectiveness of drug administration. Carrier-wall collisions are one of the recognised mechanisms responsible for active pharmaceutical ingredient (API) aerosolisation, and DPI geometries are designed to maximise their efficacy. The detachment of fine and cohesive API particles is investigated at a fundamental level by simulating with DEM the normal collision of a carrier sphere with an API particle attached. The impact velocity at which detachment occurs (escape velocity) is determined as a function of key parameters, such as cohesiveness, coefficient of restitution, static and rolling friction. An analytical model for the escape velocity is then derived, examining the role of the initial position of the particle, cohesion model and particle size. Finally, the results are framed in the context of DPI inhalers, comparing the results obtained with impact velocities typically recorded in commercial devices.

Controlling the size of powder particles is pivotal in the design of many pharmaceutical forms and the related manufacturing processes and plants. One of the most common techniques for particle size reduction in the process industry is powder milling, whose efficiency relates to the mechanical properties of the powder particles themselves. In this work, we first characterize the elastic and plastic responses of different pharmaceutical powders by measuring their Young modulus, the hardness, and the brittleness index via nano-indentation. Subsequently, we analyze the behavior of those powder samples during comminution via jet mill in different process conditions. Finally, the correlation between the single particle mechanical properties and the milling process results is illustrated; the possibility to build a predictive model for powder grindability, based on nano-indentation data, is critically discussed.

The use of computational techniques in the design of dry powder inhalers (DPI), as well as in unravelling the complex mechanisms of drug aerosolization, has increased significantly in recent years. Computational fluid dynamics (CFD) is used to study the air flow, inside the DPI, during the patient inspiratory act while discrete element methods (DEM) are used to simulate the dispersion and aerosolization of the drug product powder particles. In this work we discuss the possibility to validate a coupled CFD-DEM model for the NextHaler® DPI device against previously published experimental data. The approximations and assumptions made are deeply discussed. The comparison between computational and experimental results is detailed both for fluid and powder flows. Finally, the potential and possible applications of a calibrated DPI model are discussed as well as the missing elements necessary to achieve a fully quantitative predictive computational model.

Fine particle lift and aerodispersion are utilized as specialized technology in pharmaceutical devices such as dry powder inhalers (DPIs), where the active pharmaceutical ingredient (API) powder is delivered to the patient lungs after being dispersed and aerosolized. These processes result from the complex interplay between adhesive, impact, and hydrodynamic forces at the individual particle level. In this study, we use computational fluid dynamics-discrete element method (DEM) simulations to characterize the coupled flow field of air and API-coated carrier particles in a swirl-based DPI geometry. For the first time, the motion of particles is tracked down to the level of 10 mu m API particles, whose size ratio with the carrier is 15-20 and poses serious challenges for DEM application across the full range of scales. The predicting capability with the transiently developing swirling air flow is checked first. Then, the trajectories and velocity profiles of the particles are investigated in carrier-only systems, quantifying flow patterns, local solid distribution, and expulsion rate. The dry-coated particle deaggregation is finally analyzed during inhalation, quantifying the proportion of the detached API and expulsion patterns, also in light of the local force balances, providing valuable insights into the microscopic mechanisms.

Fine particle lift and dispersion by gas flows is utilized as specialized technology in pharmaceutical devices such as Dry Powder Inhalers (DPI), where the fine API (Active Pharmaceutical Ingredient) is delivered after aerosolization as a result of the complex interplay between adhesive, impact and hydrodynamic forces. In the present contribution, Computational Fluid Dynamics and Discrete Element Method coupled simulations (CFDDEM) are used to compute the two-phase swirling flow field in a DPI. The capability of the CFD-DEM model to represent the transiently developing swirl flow and stability is assessed in a simplified inhaler geometry. The trajectories and velocity profiles of the particles are investigated first in carrier-only systems, quantifying flow patterns, local solids distribution and expulsion rate. DEM with adhesive forces and rolling friction is then used to reproduce the deaggregation during inhalation. The proportion of detached API is studied by characterizing the trajectories, expulsion patterns and force balances, providing valuable insight into the microscopic mechanisms responsible for the macroscopic behaviour.

Predicting the outcome of jet-milling based on the knowledge of process parameters and starting material properties is a task still far from being accomplished. Given the technical difficulties in measuring thermodynamics, flow properties and particle statistics directly in the mills, modelling and simulations constitute alternative tools to gain insight in the process physics and many papers have been recently published on the subject. An ideal predictive simulation tool should combine the correct description of non-isothermal, compressible, high Mach number fluid flow, the correct particle-fluid and particle-particle interactions and the correct fracture mechanics of particle upon collisions but it is not currently available. In this paper we present our coupled CFD-DEM simulation results; while comparing them with the recent modelling and experimental works we will review the current understating of the jet-mill physics and particle classification. Subsequently we analyze the missing elements and the bottlenecks currently limiting the simulation technique as well as the possible ways to circumvent them towards a quantitative, predictive simulation of jet-milling.

Shear cell tests have been conducted on twenty different lactose powders, most of which commercially available for oral or inhalation purposes, spanning a wide range of particle sizes, particle morphologies, production processes. The aims of the investigation were: i) to verify the reliability of the technique in evaluating and classifying the flowability of powders; ii) to understand the connection between the flowability of a powder and the morphological properties of its particles; iii) to find a general mathematical relationship able to predict the yield locus shape given the particle size, shape and consolidation state of a lactose powder. These aspects and their limitations are detailed in the manuscript together with other interesting findings on the stick-slip behavior observed in most of the lactose powders examined.

Non-segregating ordered powder mixtures constituted by a coarse carrier fraction and finer components are at the basis of dry powders for inhalation pharmaceuticas. The estimation of the loading capacity, i.e. how many fines can be hosted on each carrier particle, is crucial to grant the product quality through a reproducible and affordable manufacturing process. We propose an approach based on the combination of sieve analysis, optical microscopy and powder bed permeability to quantify the loading capacity and understand the fines behavior, the impact of the mixing process was also investigated. We tested the method on model binary mixtures composed only of a coarse lactose carrier and micronized lactose fines as a surrogate of a real active pharmaceutical ingredient. The results provided by the different methods are consistent, the approach proved to be accurate and reproducible. The effect of different mixing parameters and equipment on the loading capacity is also discussed.

We address the atomistic nature of the longitudinal static friction against sliding of graphene nanoribbons (GNRs) deposited on gold, a system whose structural and mechanical properties have been recently the subject of intense experimental investigation. By means of numerical simulations and modeling we show that the GNR interior is structurally lubric ("superlubric") so that the static friction is dominated by the front/tail regions of the GNR, where the residual uncompensated lateral forces arising from the interaction with the underneath gold surface opposes the free sliding. As a result of this edge pinning the static friction does not grow with the GNR length, but oscillates around a fairly constant mean value. These friction oscillations are explained in terms of the GNR-Au(111) lattice mismatch: at certain GNR lengths close to an integer number of the beat (or moire') length there is good force compensation and superlubric sliding; whereas close to half odd-integer periods there is significant pinning of the edge with larger friction. These results make qualitative contact with recent state-of-the-art atomic force microscopy experiment, as well as with the sliding of other different incommensurate systems.

The adhesive and frictional response of an AFM tip connected to a substrate through supramolecular host-guest complexes is investigated by dynamic Monte Carlo simulations. Here, the variation of the pull-off force with the unloading rate recently observed in experiments is unraveled by evidencing simultaneous (progressive) breaking of the bonds at fast (slow) rates. The model reveals the origin of the observed plateaus in the retraction force as a function of the tip-surface distance, showing that they result from the tip geometrical features. In lateral sliding, the model exhibits a wide range of dynamic behaviors ranging from smooth sliding to stick-slip at different velocities, with the average friction force determined by the characteristic formation/rupture rates of the complexes. In particular, it is shown that for some molecular complexes friction can become almost constant over a wide range of velocities. Also, we show the possibility of exploiting the ageing effect through slide-hold-slide experiments, in order to infer the characteristic formation rate. Finally, our model predicts a novel "anti-ageing" effect which is characterized by a decrease of the static friction force with the hold time. Such an effect is explained in terms of enhancement of adhesion during sliding, especially observed at high driving velocities.

The state of vanishing friction known as superlubricity has important applications for energy saving and increasing the lifetime of devices. Superlubricity, as detected with atomic force microscopy, appears when sliding large graphite flakes or gold nanoclusters across surfaces, for example. However, the origin of the behavior is poorly understood because of the lack of a controllable nanocontact. We demonstrated the superlubricity of graphene nanoribbons when sliding on gold with a joint experimental and computational approach. The atomically well-defined contact allows us to trace the origin of superlubricity, unraveling the role played by ribbon size and elasticity, as well as by surface reconstruction. Our results pave the way to the scale-up of superlubricity and thus to the realization of frictionless coatings.

Since the demonstration of superlow friction (superlubricity) in graphite at nanoscale, one of the main challenges in the field of nano- and micromechanics was to scale this phenomenon up. A key question to be addressed is to what extent superlubricity could persist, and what mechanisms could lead to its failure. Here, using an edge-driven Frenkel-Kontorova model, we establish a connection between the critical length above which superlubricity disappears and both intrinsic material properties and experimental parameters. A striking boost in dissipated energy with chain length emerges abruptly due to a high-friction stick-slip mechanism caused by deformation of the slider leading to a local commensuration with the substrate lattice. We derived a parameter-free analytical model for the critical length that is in excellent agreement with our numerical simulations. Our results provide a new perspective on friction and nanomanipulation and can serve as a theoretical basis for designing nanodevices with superlow friction, such as carbon nanotubes.

The critical fluctuations at second order structural transitions in a bulk crystal may affect the dissipation of mechanical probes even if completely external to the crystal surface. Here, we show that noncontact force microscope dissipation bears clear evidence of the antiferrodistortive phase transition of SrTiO_{3}, known for a long time to exhibit a unique, extremely narrow neutron scattering "central peak." The noncontact geometry suggests a central peak linear response coupling connected with strain. The detailed temperature dependence reveals for the first time the intrinsic central peak width of order 80 kHz, 2 orders of magnitude below the established neutron upper bound.