AI Article Synopsis
- Interactions between droplets are crucial for understanding droplet collision and coalescence, which affects multiphase flow in emulsions and complex fluids.
- A new technique was developed to quantitatively measure the interaction force by analyzing droplet deformation during their interaction, using controlled injection rates to manage their approach speed.
- The method proved to be reliable and cost-effective, aligning closely with results from expensive commercial sensors, and highlighted droplet deformability as a key factor in determining interaction forces.
Article Abstract
Hypothesis: Interactions between droplets are of fundamental importance for understanding phenomena involving droplet collision and coalescence that determine multiphase flow behavior. The quantitative understanding of these interactions is essential for the manipulation and control of emulsions or complex fluids. The existing methods for interaction force determination are typically based on expensive mechanical probes and fine distance control. Therefore, further development of new techniques for interaction force determination is expected to be beneficial for research on surface force.
Experiments: In this study, droplet deformation during the interaction between two droplets was captured and analyzed to determine the interaction force. The approach speed of the two droplets was controlled by the injection rate of the fluid. The dynamic interaction force between two tetradecane droplets in various aqueous solutions was determined using the newly developed method, and the effects of two-phase physical properties and operating conditions on the measurement errors were investigated.
Findings: The droplet profile deformation was first applied as a probe to detect the interaction force. The measurement results were in good agreement with those obtained using the precise weighing sensor of a commercial interfacial tensiometer (K100, Kruss, Germany). The newly developed method was reliable, simple, and did not require the use of expensive devices. Furthermore, droplet deformability was found to be the key parameter in determining the total interaction force between the droplets.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.jcis.2021.07.073 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The 1831 CE mystery eruption identified as Zavaritskii caldera, Simushir Island (Kurils).
Proc Natl Acad Sci U S A
January 2025
Archaeology & Palaeoecology, School of Natural and Built Environment, Queen's University, Belfast BT9 3AZ, United Kingdom.
Polar ice cores and historical records evidence a large-magnitude volcanic eruption in 1831 CE. This event was estimated to have injected ~13 Tg of sulfur (S) into the stratosphere which produced various atmospheric optical phenomena and led to Northern Hemisphere climate cooling of ~1 °C. The source of this volcanic event remains enigmatic, though one hypothesis has linked it to a modest phreatomagmatic eruption of Ferdinandea in the Strait of Sicily, which may have emitted additional S through magma-crust interactions with evaporite rocks.
View Article and Find Full Text PDFAnalyzing Atomic Interactions in Molecules as Learned by Neural Networks.
J Chem Theory Comput
January 2025
BIFOLD─Berlin Institute for the Foundations of Learning and Data, 10587 Berlin, Germany.
While machine learning (ML) models have been able to achieve unprecedented accuracies across various prediction tasks in quantum chemistry, it is now apparent that accuracy on a test set alone is not a guarantee for robust chemical modeling such as stable molecular dynamics (MD). To go beyond accuracy, we use explainable artificial intelligence (XAI) techniques to develop a general analysis framework for atomic interactions and apply it to the SchNet and PaiNN neural network models. We compare these interactions with a set of fundamental chemical principles to understand how well the models have learned the underlying physicochemical concepts from the data.
View Article and Find Full Text PDFBalancing enthalpy and entropy in inhibitor binding to the prostate-specific membrane antigen (PSMA).
Phys Chem Chem Phys
January 2025
Center for Advanced Materials Research, Beijing Normal University at Zhuhai, Zhuhai, 519087, China.
Understanding the molecular mechanism of inhibitor binding to prostate-specific membrane antigen (PSMA) is of fundamental importance for designing targeted drugs for prostate cancer. Here we designed a series of PSMA-targeting inhibitors with distinct molecular structures, which were synthesized and characterized using both experimental and computational approaches. Microsecond molecular dynamics simulations revealed the structural and thermodynamic details of PSMA-inhibitor interactions.
View Article and Find Full Text PDFRnd3 Ameliorates Diabetic Cardiac Microvascular Injury via Facilitating Trim40-mediated Rock1 Ubiquitination.
Diabetes
January 2025
Department of Cardiology, Xijing Hospital, Air Force Medical University, Xi'an, Shaanxi, China.
Diabetic microvascular dysfunction is evidenced by disrupted endothelial cell junctions and increased microvascular permeability. However, effective strategies against these injuries remain scarce. In this study, the type 2 diabetes mouse model was established by high-fat diet combined with streptozotocin injection in Rnd3 endothelial- specific transgenic and knockout mice.
View Article and Find Full Text PDFHarnessing the Power of Machine Learning Guided Discovery of NLRP3 Inhibitors Towards the Effective Treatment of Rheumatoid Arthritis.
Cells
December 2024
Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multidisciplinary approach combining machine learning, quantitative structure-activity relationship (QSAR) modeling, structure-activity landscape index (SALI), docking, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area MM/PBSA assays was employed to identify novel NLRP3 inhibitors.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!