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• W2622832893 abstract "The study sets its main focus on the introduction of a random-walk-based model for the generation of variably shaped particle aggregates consisting of a predefined number of spherical components. With the help of a well-defined algorithm, the user is enabled to select between isodimensional, chain-like and platelet-like aggregates, for which related aerodynamic parameters (dynamic shape factors, volume-equivalent diameters, aerodynamic diameters) are determined automatically. The theoretical approach for random aggregate construction is directly connected with the previously developed stochastic particle transport and deposition model. Thereby, individually shaped aggregates may be provided for each random-walk scenario taking place in the almost realistic lung structure. Preliminary application of the aggregate generation model was carried out by assuming single components with a constant diameter of 1 nm and unit-density (1 g cm-3) and variably shaped aggregates consisting of 10, 100 and 1000 components. Inhalation of the aggregate-loaded aerosol into lungs of average size (FRC = 3300 mL) was supposed to take place under sitting, light-exercise and heavy-exercise conditions. Results obtained from deposition modeling clearly show that, independent of aggregate geometry, total deposition declines with increasing number of components included in the particulate construct, but experiences a continuous enhancement with rising inhalation flow rate. Among the predefined geometric categories, platelet-like aggregates are distinguished by lowest deposition and isodimensional clusters by highest. While isodimensional aggregates preferentially deposit in the extrathoracic and bronchial airways, chain-like and platelet-like aggregates exhibit a significantly increased tendency to hit the alveolar walls." @default.
• W2622832893 created "2017-06-15" @default.
• W2622832893 creator A5091893852 @default.
• W2622832893 date "2017-03-21" @default.
• W2622832893 modified "2023-09-24" @default.
• W2622832893 title "Computer-aided generation and lung deposition modeling of nano-scale particle aggregates" @default.
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• W2622832893 doi "https://doi.org/10.1080/08958378.2017.1329362" @default.
• W2622832893 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28585473" @default.
• W2622832893 hasPublicationYear "2017" @default.
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