Rafael Delgado-Buscalioni

Sorting, filtering, and controlling colloidal particles is crucial in many fields, ranging from chemistry to biology and physics. Dielectrophoresis (DEP) enables selective manipulation of colloids by non‐uniform AC electric fields, yet the associated three‐dimensional nanoparticle dynamics and electrokinetic flows remain difficult to access experimentally. Here, we combine real‐time multiplane widefield microscopy (> 100 fps), 3D single‐particle tracking, and multiscale modeling to reconstruct the motion of 200 nm fluorescent polystyrene nanoparticles around a quadrupolar electrode under positive and negative DEP. This optical–computational approach provides volumetric trajectories and flow maps, revealing particle trapping, depletion, and three‐dimensional vortical motion. A model including DEP and AC electro‐osmotic flow quantitatively reproduces the positive DEP dynamics, demonstrating direct agreement between experiment and theory. Under negative DEP, the model captures particle depletion near the electrodes but not all observed flow structures, pointing to additional electrokinetic or electrothermal contributions. This framework provides a route to validate and refine AC electrokinetic models for complex colloidal and microfluidic systems.

The quartz crystal microbalance (QCM) is one of the few label-free techniques capable of sampling the response of proteins and their aggregates. However, QCM signals come encrypted by a complicated interaction between the biomolecular viscoelastic response and their hydrodynamic perturbations. This has hampered the quantitative interpretation of QCM signals of biomolecules. In addition, the large size disparity between proteins and the QCM flow penetration length of 100 nm creates a deadlock for standard simulation packages. Using first-principles modeling and adaptive schemes, we show that the ultrasensitive QCM sensor can be upgraded to a high-precision quantitative tool for protein analysis. We present a “Virtual-QCM” (VQCM) framework to introduce viscoelastic structures in a hydrodynamic solver for semi-infinite wall-bounded oscillatory flow. The fluid solver [R. P. Peláez, P. Palacios-Alonso, and R. Delgado-Buscalioni, J. Fluid Mech. 1010, A57 (2025)] is spectral in time and space and implements open boundaries focusing on the relevant fluid layer around proteins with ∼104 speed-up. Biomolecules are modeled as viscoelastic networks connected to the atomistic level via coarse-graining theory. Integrating VQCM with experiments allows us to predict the physicochemical properties of FtsZ and ZipA; bacterial proteins with intrinsically disordered regions (IDRs) tethered to lipid membrane substrates. Quantitative match with experiments at all coverages permits us to measure substrate binding affinities, IDR extension ℓ, stiffness k, and intrinsic friction ξ. We find the polypeptide chains to be extremely sensitive to the buffer ionic strength, with protein friction affected by Mg+2. Measured intrinsic relaxation times ξ/k ∼ [3–30] ns are consistent with FRET analyses. Access to microscopic information using standard QCM sensors will help decipher the IDR structure–function and other protein aggregates.

Effective hydrodynamic modeling is crucial for accurately predicting fluid–particle interactions in diverse fields such as biophysics and materials science. Developing and implementing hydrodynamic algorithms is challenging due to the complexity of fluid dynamics, necessitating efficient management of large-scale computations and sophisticated boundary conditions. Furthermore, adapting these algorithms for use on massively parallel architectures such as GPUs adds an additional layer of complexity. This paper presents the libMobility software library, which offers a suite of CUDA-enabled solvers for simulating hydrodynamic interactions in particulate systems at the Rotne–Prager–Yamakawa level. The library facilitates precise simulations of particle displacements influenced by external forces and torques, including both the deterministic and stochastic components. Notable features of libMobility include its ability to handle linear and angular displacements, thermal fluctuations, and various domain geometries effectively. With an interface in Python, libMobility provides comprehensive tools for researchers in computational fluid dynamics and related fields to simulate particle mobility efficiently. This article details the technical architecture, functionality, and wide-ranging applications of libMobility. libMobility is available at https://github.com/stochasticHydroTools/libMobility.

Experiments and simulations reveal that salt-dependent electrostatic repulsion modulates near- and far-field optical binding of gold nanoparticles, with a simple model reproducing observed configurations and highlighting electrostatics' key role.

We present a fast spectral solver for the linear response of viscoelastic structures under oscillatory flow either in free space or close to a flat moving wall. The scheme works in the frequency domain (using phasors) and couples the oscillatory Stokes equation with rigid or flexible structures, modeled by viscoelastic networks of immersed boundary kernels. The fluid–structure coupling can be solved by two routes. One route calculates the hydrodynamic mobility matrix required to solve the equation for the structure deformation rate in matrix form. The second route iteratively solves the coupled fluid–structure equations: fluid-induced forces on the structures create a tension field, which is then transferred to the fluid, until convergence. The resulting fixed-point problem is solved iteratively using the Anderson acceleration method. The mobility route is optimal when dealing with one or a few structures, while the iterative scheme is preferred for denser dispersions. In any case, the flow resulting from the body forces is solved by a recently developed scheme [R. P. Peláez, P. Palacios-Alonso, and R. Delgado-Buscalioni, J. Fluid. Mech. 1010 A57 (2025)], which is spectral in space and time and deals with doubly periodic open domains (either free-space or wall-bounded) where meshing is restricted to the region of interest around the structures. We test the present scheme in two applied contexts: quartz-crystal-microbalance (QCM) of spheres, suspended, adsorbed, or tethered to viscoelastic linkers; and force spectroscopy (via atomic force microscopy) reproducing the power spectra of vibrating microparticles near a solid boundary. In all cases, comparisons with analytical, numerical, and experimental results show excellent agreement. We conclude by discussing new routes the scheme opens in force spectroscopy and QCM analyses of soft objects.

The dynamics and equilibrium configurations of immersed optically-bound particles are complex phenomena involving several physical mechanisms such as optical forces, electrostatic interactions, and fluid dynamics. In this work, we unravel, using experiments and numerical simulations, the key role played by short-range electrostatic forces. The repulsive interaction among gold nanoparticles is adjusted by changing the salt concentration. When the electrostatic interaction is reduced, near-field (NF) optical binding with particles oriented along the polarization direction is promoted, while, for low values of the salt concentration, inter-particle repulsion induces far-field (FF) optical binding configurations oriented perpendicular to the polarization. The importance of electrostatic force is confirmed by a theoretical model in which the repulsive effect is explicitly tuned. The numerical results reproduce the measured particle configurations and highlight the dominant role of electrostatic interactions, particularly in FF optical binding configurations.

A nonlinear relationship for the magnetic hysteresis area of Brownian nanoparticles permits fast and accurate characterization of bioconjugated particles and solvent properties by an automated method.

Friction forces are essential for cell movement, yet they also trigger numerous active cellular responses, complicating their measurement in vivo. Here, we introduce a synthetic model designed to measure friction forces between biomimetic membranes and substrates. The model consists of a vesicle with precisely controlled properties, fabricated via microfluidics, encapsulating a single ferromagnetic particle that is magnetically driven to rotate. The rotation of the particle generates a confined rotational flow, setting the vesicle membrane into motion. By adjusting the magnetic field frequency and vesicle size, the rotation frequency of the vesicle can be finely controlled, resulting in a rolling vesicle that functions as an effective tribological tool across a wide frequency range. At low frequencies, molecular contact between the membrane and substrate dominates frictional interactions, which enables determination of the contact friction coefficient. At higher frequencies, lubrication becomes predominant, causing the vesicles to slip rather than roll. Adjusting membrane fluidity and incorporating specific ligand–receptor interactions within this model will enable detailed studies of frictional forces in more complex biomimetic systems, providing key insights into the mechanisms of cell movement and mechanotransduction.