Master in Chemical Engineering, Politecnico di Milano, 1998
PhD Chemical Engineering, ETH Zurich, 2003
Postdoctoral Scholar, Chemical Engineering Department, MIT, 2006
RESEARCH, TEACHING, or OTHER INTERESTS
Colloid and Surface Chemistry, Physical and Theoretical Chemistry, Materials Science, Chemical Engineering
186
Scopus Publications
9878
Scholar Citations
48
Scholar h-index
131
Scholar i10-index
Scopus Publications
From Experimental Planning to Autonomous Discovery: The Changing Role of Design of Experiments in Nanotechnology Miroslava Nedyalkova, Vasil Simeonov, Marco Lattuada Chimia, 2026 Design of Experiments (DoE) is increasingly reshaping how nanomaterials are discovered, optimized, and understood, enabling a shift from empirical trial-and-error toward predictive, knowledge-driven design. As nanotechnology advances toward multifunctional and highly coupled systems, unstructured experimentation struggles to deliver reproducibility, efficiency, or transferability. This perspective highlights the evolution of DoE from classical factorial designs and response surface methodology to Bayesian, adaptive, and machine-learning-enabled frameworks. We discuss how structured experimentation reveals hidden interactions, supports multi-objective optimization, and enables uncertainty-aware decision-making across complex synthesis spaces.
Bio-Inspired Magnetically Tunable Structural Colors from Elliptical Self-Assembled Block Copolymer Microparticles Gianluca Mazzotta, Simone Bertucci, Jose Mendoza‐Carreño, Agustín Mihi, Paola Lova, Davide Comoretto, Ullrich Steiner, Marco Lattuada, Andrea Dodero Advanced Functional Materials, 2026 Cephalopods achieve their vivid, dynamic structural coloration through reconfigurable lamellar reflectors, acting as a powerful inspiration for adaptive optical materials. However, synthetic systems that replicate this functionality typically require complex material architectures or multistep fabrication processes. Here, a straightforward strategy is presented for producing magnetically responsive photonic microparticles using linear poly(styrene)‐ b ‐poly(2‐vinylpyridine) block copolymers. Self‐assembly in emulsion droplets yields ellipsoids with stacked lamellar domains that exhibit structural colors spanning the entire visible spectrum. Blending block copolymers with different molecular weights enables precise, continuous control over lamellar periodicity and photonic bandgap spectral position, eliminating the need for chemical modification or the use of swelling agents. Notably, incorporating superparamagnetic iron oxide nanoparticles imparts rapid and reversible magnetic alignment of the microparticles. This orientation aligns the lamellar stacks perpendicular to the magnetic field, resulting in Bragg reflection and angle‐dependent coloration. The reflected wavelength can be tuned by changing the viewing angle, which mimics the dynamic optical responses of biological iridophores. Compared to prior systems, our approach reduces synthetic complexity while maintaining high color intensity and angular tunability. Thus, this work introduces a bio‐inspired materials concept that offers a simple route toward dynamically tunable optical materials for adaptive camouflage, smart coatings, and next‐generation photonic devices.
Outlook: Emerging Enzyme–Material Designs for Advanced Biocatalysis Miroslava Nedyalkova, Diana Potes Vecini, Marco Lattuada Chemistryselect, 2025 Biocatalysis lies at the heart of nature's intricate processes and the development of greener technologies. Our scientific grasp of this field has grown remarkably. Under mild conditions, enzymes were recognized as the primary biocatalysts due to their high catalytic efficiency. Enzyme‐based catalysis is a cornerstone of sustainable chemistry; however, instability and activity loss under more severe conditions remain significant obstacles to its industrial application. In recent years, notable advances in sequencing, protein engineering, and AI‐driven enzyme discovery have transformed catalyst design approaches; however, these approaches still overlook the importance of immobilization. A crucial strategy is needed to enhance stability, reusability, and control. Materials designed toward solid supports, such as MOFs, COFs, HOFs, nanoparticles, and molecular cages, provide tunable environments that can reshape and enhance enzyme performance. However, the questions about the mechanistic impacts are still poorly understood and remain open. Computational chemistry and machine learning now offer the tools to predict enzyme–material interactions, quantify immobilization effects, and guide rational support selection. This perspective advocates for a closed‐loop framework that integrates enzyme engineering with material co‐design to create immobilization‐optimized catalyst pathways. Embedding such approaches will enable the development of robust, predictive, and scalable biocatalysts for advancing sustainable chemical manufacturing.
Machine Learning-Guided Design of Rhenium Tricarbonyl Complexes for Next-Generation Antibiotics Miroslava Nedyalkova, Gozde Demirci, Youri Cortat, Kevin Schindler, Fatlinda Rahmani, Justine Horner, Mahdi Vasighi, Aurelien Crochet, Aleksandar Pavic, Olimpia Mamula, Fabio Zobi, Marco Lattuada ACS Bio and Med Chem Au, 2025 The escalating prevalence of antibiotic-resistant bacteria and the increasing complexity of managing severe infections emphasize the critical need for novel and effective antibiotics. Herein, we present a novel computational strategy focused on metal-based antibiotics, specifically rhenium (Re) complexes, for the rational design of next-generation antibacterial agents. Our approach integrates machine learning (ML) classification models to predict antibacterial potency, particularly against multidrug-resistant pathogens. A recognized limitation of conventional ML-driven antibiotic discovery is its dependence on structural similarity to known antibiotics, which hinders the exploration of structurally diverse and innovative antibiotic classes. To address this, we developed predictive ML models based on multi-layer perceptron (MLP) and random forest (RF) algorithms to estimate the minimum inhibitory concentration (MIC) of Re complexes against methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) Staphylococcus aureus strains. Utilizing structural descriptors, these models demonstrated strong predictive performance and were successfully applied to evaluate 26 novel Re complexes. Additionally, Shapley additive explanation (SHAP) analysis provided insights into the structural features influencing antibacterial activity predictions. The study’s outcomes affirm the effectiveness of our ML-guided approach as a promising pathway for the rational, de novo design of potent Re based antibiotics capable of combating antibiotic-resistant bacterial infections.
Fluorinated Aromatic Amide Helices: Synthesis and Modeling of Helical Handedness Saquib Farooq, Miroslava Nedyalkova, Subhajit Pal, Aurelien Crochet, Marco Lattuada, Andreas F. M. Kilbinger Macromolecules, 2025 We present a next-generation helical polyamide synthesized from 5-amino-2,4-difluorobenzoic acid. Polymerization, driven by chloro-tritolylphosphonium iodide (PHOS3), achieved precise molecular weight control and narrow dispersity. Introducing (R) and (S) chiral initiators successfully induced well-defined helical structures, as confirmed by distinct Cotton effects with opposing signs. Molecular dynamics simulations provided deeper insight into the self-assembly process of two helices adopting opposite helicities (P and M). Notably, S–M helices formed compact, highly cohesive, noncovalent stacks, demonstrating packing efficiency over their S–P counterparts. These findings enhance our understanding of polymer chirality, molecular organization, and self-assembly, paving the way for the rational design of advanced helical materials with promising applications in materials science.
Integrating surface chemistry properties and machine learning to map the toxicity landscape of superparamagnetic iron oxide nanoparticles Miroslava Nedkyalkova, Mahdi Vasighi, Marco Lattuada Chemosphere, 2025 The relationship between Superparamagnetic Iron Oxide Nanoparticles (SPIONs) surface chemistry and their toxicological outcomes is crucial for biomedical applications, including drug delivery and imaging diagnostics. SPIONs' surface properties—such as size, shape, type of coating agents, and charge—are directly linked to their interactions with the biological environment, significantly affecting their toxicity. Surface chemistry plays a significant role in determining biocompatibility, cellular uptake, and the potential for adverse reactions. This study focuses on building a classification and prediction model based on the experimentally obtained properties and linked with the calculated molecular descriptors to describe the nature of the various coatings used for SPIONs in such a combined mode. The predictive model helps identify how specific surface modifications, including coating types and functional groups, influence toxicity responses. The results that were obtained, which correlate well with the existing literature, confirm the effects of surface chemistry on toxicity. For instance, the model accurately predicts that chitosan derivative coatings with a higher positive charge exhibit toxic potential, which aligns with previous findings. Incorporating these experimentally obtained surface features into a predictive framework enables the design of safer SPION formulations, enhancing therapeutic efficacy while managing surface chemistry's effects on toxicity. • The surface properties of SPIONs, particularly the type of coating, significantly affect their toxicity and biocompatibility in biomedical applications. • Leveraging a classification and prediction model based on data-driven approach. • Combining experimentally obtained surface properties with molecular descriptors enables the prediction of toxicological outcomes for SPIONs. • The predictive model supports the design of safer SPIONs by optimizing surface chemistry.
Rapid Water Permeation by Aramid Foldamer Nanochannels With Hydrophobic Interiors Saquib Farooq, Javid Ahmad Malla, Miroslava Nedyalkova, Rafael V. M. Freire, Indradip Mandal, Aurelien Crochet, Stefan Salentinig, Marco Lattuada, Charlie T. McTernan, Andreas F. M. Kilbinger Angewandte Chemie International Edition, 2025 Aquaporins are natural proteins that rapidly transport water across cell membranes, maintaining homeostasis, whilst strictly excluding salt. This has inspired their use in water purification and desalination, a critical emerging need. However, stability, scalability, and cost have prevented their widespread adoption in water purification membrane technologies. As such, attention has turned to the use of artificial water channels, with pore‐functionalized polymers and macrocycles providing a powerful alternative. Whilst impressive rates of transport have been achieved, the combination of a scalable, high‐yielding synthesis and efficient transport has not yet been reported. Herein, we report such a system, with densely functionalized channel interiors, synthesized by high‐yielding living polymerization with low polydispersities, showing high salt exclusion and excellent water transport rates. Our aramid foldamers create artificial water channels with hydrophobic interiors and single‐channel water permeability rates of up to 108 water molecules per second per channel, approaching the range of natural aquaporins (c. 109). We show that water transport rates closely correspond to the helical length, with the polymer that most closely matches bilayer thickness showing optimal efficacy, as supported by molecular dynamics (MD) simulations. Our work provides a basis for the scalable synthesis of next‐generation artificial water channels.
Comparative Analysis of pKa Predictions for Arsonic Acids Using Density Functional Theory-Based and Machine Learning Approaches Miroslava Nedyalkova, Diana Heredia, Joaquín Barroso-Flores, Marco Lattuada ACS Omega, 2025 Arsonic acids (RAsO(OH)2), prevalent in contaminated food, water, air, and soil, pose significant environmental and health risks due to their variable ionization states, which influence key properties such as lipophilicity, solubility, and membrane permeability. Accurate pKa prediction for these compounds is critical yet challenging, as existing models often exhibit limitations across diverse chemical spaces. This study presents a comparative analysis of pKa predictions for arsonic acids using a support vector machine-based machine learning (ML) approach and three density functional theory (DFT)-based models. The DFT models evaluated include correlations to the maximum surface electrostatic potential (VS,max), atomic charges derived from a solvation model (solvation model based on density), and a scaled solvent-accessible surface method. Results indicate that the scaled solvent-accessible surface approach yielded high mean unsigned errors, rendering it less effective. In contrast, the atomic charge-based method on the conjugated arsonate base provided the most accurate predictions. The ML-based approach demonstrated strong predictive performance, suggesting its potential utility in broader chemical spaces. The obtained values for pKa from VS,max show a weak prediction level, because the way of predicting pKa is related only to the electrostatic character of the molecule. However, pKa is influenced by many factors, including the molecular structure, solvation, resonance, inductive effects, and local atomic environments. VS,max cannot fully capture these different interactions, as it gives a simplistic view of the overall molecular potential field.
Dense and strong, but superinsulating silica aerogel Subramaniam Iswar, Sandra Galmarini, Luca Bonanomi, Jannis Wernery, Eleftheria Roumeli, Sudheera Nimalshantha, Avner M. Ben Ishai, Marco Lattuada, Matthias M. Koebel, Wim J. Malfait Acta Materialia, 2021
Functional polymers through mechanochemistry Stephen Schrettl, Marco Lattuada, Katharina M. Fromm, Yoan C. Simon, Michela Di Giannantonio, Ester Verde-Sesto, Yoshimitsu Sagara, Laura N. Neumann, Anna Lavrenova, Marc Karman, Céline Calvino, Diederik W.R. Balkenende, Christoph Weder Chimia, 2019
Effect of aging on silica aerogel properties Subramaniam Iswar, Wim J. Malfait, Sandor Balog, Frank Winnefeld, Marco Lattuada, Matthias M. Koebel Microporous and Mesoporous Materials, 2017
Retarded hydrodynamic properties of fractal clusters Engineering Sciences and Fundamentals 2014 Core Programming Area at the 2014 Aiche Annual Meeting, 2014
WORM-LIKE micelles of polymerizable surfactant as a template for polymerization Nanoscale Science and Engineering Forum 2014 Core Programming Area at the 2014 Aiche Annual Meeting, 2014
Asymmetric functionalization of shape-anisotropic polymer nanoparticles Nanoscale Science and Engineering Forum 2013 Core Programming Area at the 2013 Aiche Annual Meeting Global Challenges for Engineering A Sustainable Future, 2014
Preparation, characterization and properties of janus magnetic liposomes Nanoscale Science and Engineering Forum 2014 Core Programming Area at the 2014 Aiche Annual Meeting, 2014
Self-assembled Magnetic Silica Nano-rods and Micro-platelets as smart reinforcements for polymer-composites Technical Proceedings of the 2013 Nsti Nanotechnology Conference and Expo Nsti Nanotech 2013, 2013
Porous materials from time dependent magnetically assisted self-assembly of nanoparticles Materials Engineering and Sciences Division Core Programming Topic at the 2011 Aiche Annual Meeting, 2011
Structural control of porous polymeric materials through magnetic gelation Nanotechnology 2010 Advanced Materials Cnts Particles Films and Composites Technical Proceedings of the 2010 Nsti Nanotechnology Conference and Expo Nsti Nanotech 2010, 2010
Effect of complex surface chemistry on the electrophoretic mobility of colloidal particles Aiche Annual Meeting Conference Proceedings, 2008
Shear induced aggregation rate of colloidal nanoparticles and clusters in the presence of repulsive interactions Aiche Annual Meeting Conference Proceedings, 2008
Preparation and characterization of NOVEL Polymer-MAGNETIC COLLOIDS Aiche Annual Meeting Conference Proceedings, 2008
Generation and geometrical analysis of dense clusters with variable fractal dimension providing a basis for the interpretation of data from optical particle characterication techniques Aiche Annual Meeting Conference Proceedings, 2008
Patchy colloidal particles via surfactant adsorption: Interactions and gels of tunable structure Aiche Annual Meeting Conference Proceedings, 2008
The elasticity and breakage of colloidal aggregates in shear and turbulent flows Aiche Annual Meeting Conference Proceedings, 2008
Evidence and relevance of a structural barrier for coalescence of soft sphere colloids Aiche Annual Meeting Conference Proceedings, 2008
Use of asymmetric flow-field flow fractionation to characterize aggregating colloidal dispersions Aiche Annual Meeting Conference Proceedings, 2008
Mechanism of ADSORPTION of anionic surfactants on the surface of functionalized NANOPARTICLES Aiche Annual Meeting Conference Proceedings, 2008
Preparation of biocompatible MAGNETIC COLLOIDS from supercritical fluid extraction of emulsion Aiche Annual Meeting Conference Proceedings, 2008
Accounting for counterion association in prediction of colloidal stability Aiche Annual Meeting Conference Proceedings, 2008
Generalized model for the aggregation rate of colloidal nanoparticles and clusters induced by shear in the presence of repulsive interactions Technical Proceedings of the 2008 Nsti Nanotechnology Conference and Trade Show Nsti Nanotech Nanotechnology 2008, 2008
Scattering properties of dense clusters of nanoparticles Technical Proceedings of the 2008 Nsti Nanotechnology Conference and Trade Show Nsti Nanotech Nanotechnology 2008, 2008
Influence of structural forces and contact hysteresis on flow-induced aggregation and breakage of polymer nanoparticles Technical Proceedings of the 2008 Nsti Nanotechnology Conference and Trade Show Nsti Nanotech Nanotechnology 2008, 2008
Estimation of fractal dimension of colloidal gels in the presence of multiple scattering Physical Review E Statistical Nonlinear and Soft Matter Physics, 2001
Aromaticity‐Switchable Tetraoxa [8] circulenes as Anode Materials for Sodium‐Ion Batteries PW Fritz, M Liu, M Nedyalkova, T Ashirov, D Baster, M Lattuada, ... ChemistryEurope 4 (2), e202500149 , 2026 2026
Enhanced quantitative accuracy in single molecule imaging: a fidelity-guided denoising approach A Enayati, H Baird, M Weyland, A Fink, M Lattuada, W Jamieson, ... Zenodo , 2026 2026
Bio‐Inspired Magnetically Tunable Structural Colors from Elliptical Self‐Assembled Block Copolymer Microparticles G Mazzotta, S Bertucci, J Mendoza‐Carreño, A Mihi, P Lova, D Comoretto, ... Advanced Functional Materials, e28686 , 2025 2025
In silico screening of potential agonists of a glucagon-like peptide-1 receptor among female sex hormone derivatives M Nedyalkova, R Robeva, J Romanova, K Yovcheva, M Lattuada, ... Journal of Biomolecular Structure and Dynamics 43 (17), 9546-9557 , 2025 2025 Citations: 1
Janus Particles and the Many Faces of Colloids M Lattuada 2025 AIChE Annual Meeting , 2025 2025
Outlook: Emerging Enzyme–Material Designs for Advanced Biocatalysis M Nedyalkova, DP Vecini, M Lattuada ChemistrySelect 10 (43), e03483 , 2025 2025 Citations: 2
Machine Learning-Guided Design of Rhenium Tricarbonyl Complexes for Next-Generation Antibiotics M Nedyalkova, G Demirci, Y Cortat, K Schindler, F Rahmani, J Horner, ... ACS Bio & Med Chem Au 5 (5), 870-881 , 2025 2025 Citations: 1
Ultrasonic mediated synthesis of zinc oxide nanoparticles: An insight into operative conditions to control key properties B Botelli, M Nedyalkova, M Lattuada, V Lassalle Nano-Structures & Nano-Objects 43, 101538 , 2025 2025 Citations: 2
Fluorinated aromatic amide helices: synthesis and modeling of helical handedness S Farooq, M Nedyalkova, S Pal, A Crochet, M Lattuada, AFM Kilbinger Macromolecules 58 (12), 5990-5994 , 2025 2025 Citations: 6
Integrating surface chemistry properties and machine learning to map the toxicity landscape of superparamagnetic iron oxide nanoparticles M Nedkyalkova, M Vasighi, M Lattuada Chemosphere 378, 144381 , 2025 2025 Citations: 8
Rapid Water Permeation by Aramid Foldamer Nanochannels with Hydrophobic Interiors S Farooq, JA Malla, M Nedyalkova, RVM Freire, I Mandal, A Crochet, ... Angewandte Chemie (International ed. in English) 64 (22), e202504170 , 2025 2025 Citations: 9
Chemometrical assessment of adverse effects in lung cells induced by vehicle engine emissions M Nedyalkova, R He, A Petri-Fink, B Rothen-Rutishauser, M Lattuada Nanotoxicology 19 (3), 353-366 , 2025 2025 Citations: 2
Comparative Analysis of p K a Predictions for Arsonic Acids Using Density Functional Theory-Based and Machine Learning Approaches M Nedyalkova, D Heredia, J Barroso-Flores, M Lattuada ACS omega 10 (3), 3128-3140 , 2025 2025
Harnessing antimicrobial peptide-functionalized nanoparticles: a perspective on experimental and computational strategies to combat antibiotic resistance M Nedyalkova, DP Vecini, AS Paluch, M Lattuada Physical Chemistry Chemical Physics 27 (31), 16284-16294 , 2025 2025 Citations: 5
Theoretical evaluation of the impact of diverse treatment conditions by calculation of the tumor control probability (TCP) of simulated cervical cancer Hyperthermia … S Mingo Barba, A Ademaj, D Marder, O Riesterer, M Lattuada, ... International Journal of Hyperthermia 41 (1), 2320852 , 2024 2024
Controlling the Order in Colloidal Crystals By Progressively Changing the Shape of Particles J Smart, M Lattuada 2024 AIChE Annual Meeting , 2024 2024
The Use of Survival Dose-Rate Dependencies as Theoretical Discrimination Criteria for In-Silico Dynamic Radiobiological Models S Mingo Barba, F Lobo-Cerna, PM Krawczyk, M Lattuada, RM Füchslin, ... Dose-Response 22 (3), 15593258241279906 , 2024 2024
pKa predictions for arsonic acid derivatives. M Nedyalkova, D Heredia, M Lattuada, J Barroso-Flores ChemRxiv 2024 (0722) , 2024 2024 Citations: 1
Additive Manufacturing of Nanocellulose Aerogels with Structure‐Oriented Thermal, Mechanical, and Biological Properties D Sivaraman, Y Nagel, G Siqueira, P Chansoria, J Avaro, A Neels, ... Advanced Science 11 (24), 2307921 , 2024 2024 Citations: 36
1254: Tumor Control Probability predictions for Hyperthermia plus Radiotherapy under varying conditions SM Barba, A Ademaj, D Marder, O Riesterer, M Lattuada, RM Füchslin, ... Radiotherapy and Oncology 194, S2900-S2903 , 2024 2024
MOST CITED SCHOLAR PUBLICATIONS
Nanoparticle colloidal stability in cell culture media and impact on cellular interactions TL Moore, L Rodriguez-Lorenzo, V Hirsch, S Balog, D Urban, C Jud, ... Chemical Society Reviews 44 (17), 6287-6305 , 2015 2015 Citations: 1297
Synthesis, properties and applications of Janus nanoparticles M Lattuada, TA Hatton Nano Today 6 (3), 286-308 , 2011 2011 Citations: 702
Functionalization of monodisperse magnetic nanoparticles M Lattuada, TA Hatton Langmuir 23 (4), 2158-2168 , 2007 2007 Citations: 607
Bioinspired stimuli‐responsive color‐changing systems G Isapour, M Lattuada Advanced Materials 30 (19), 1707069 , 2018 2018 Citations: 371
Preparation and controlled self-assembly of Janus magnetic nanoparticles M Lattuada, TA Hatton Journal of the American Chemical Society 129 (42), 12878-12889 , 2007 2007 Citations: 257
Effect of aging on silica aerogel properties S Iswar, WJ Malfait, S Balog, F Winnefeld, M Lattuada, MM Koebel Microporous and Mesoporous Materials 241, 293-302 , 2017 2017 Citations: 235
Fractal-like structures in colloid science S Lazzari, L Nicoud, B Jaquet, M Lattuada, M Morbidelli Advances in colloid and interface science 235, 1-13 , 2016 2016 Citations: 235
A simple model for the structure of fractal aggregates M Lattuada, H Wu, M Morbidelli Journal of colloid and interface science 268 (1), 106-120 , 2003 2003 Citations: 231
Reversible clustering of pH-and temperature-responsive Janus magnetic nanoparticles T Isojima, M Lattuada, JB Vander Sande, TA Hatton Acs Nano 2 (9), 1799-1806 , 2008 2008 Citations: 198
Hydrodynamic radius of fractal clusters M Lattuada, H Wu, M Morbidelli Journal of colloid and interface science 268 (1), 96-105 , 2003 2003 Citations: 168
Triggered metal ion release and oxidation: ferrocene as a mechanophore in polymers M Di Giannantonio, MA Ayer, E Verde‐Sesto, M Lattuada, C Weder, ... Angewandte Chemie International Edition 57 (35), 11445-11450 , 2018 2018 Citations: 155
Aggregation kinetics of polymer colloids in reaction limited regime: experiments and simulations M Lattuada, P Sandkühler, H Wu, J Sefcik, M Morbidelli Advances in colloid and interface science 103 (1), 33-56 , 2003 2003 Citations: 150
Breakup of dense colloidal aggregates under hydrodynamic stresses A Zaccone, M Soos, M Lattuada, H Wu, MU Bäbler, M Morbidelli Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 79 (6 … , 2009 2009 Citations: 142
Critical aspects of sample handling for direct nanoparticle analysis and analytical challenges using asymmetric field flow fractionation in a multi-detector approach A Ulrich, S Losert, N Bendixen, A Al-Kattan, H Hagendorfer, B Nowack, ... Journal of Analytical Atomic Spectrometry 27 (7), 1120-1130 , 2012 2012 Citations: 139
Strong, machinable, and insulating chitosan–urea aerogels: toward ambient pressure drying of biopolymer aerogel monoliths N Guerrero-Alburquerque, S Zhao, N Adilien, MM Koebel, M Lattuada, ... ACS applied materials & interfaces 12 (19), 22037-22049 , 2020 2020 Citations: 125
Insertion of nanoparticle clusters into vesicle bilayers C Bonnaud, CA Monnier, D Demurtas, C Jud, D Vanhecke, X Montet, ... ACS nano 8 (4), 3451-3460 , 2014 2014 Citations: 118
Experimental and modeling study of breakage and restructuring of open and dense colloidal aggregates YM Harshe, M Lattuada, M Soos Langmuir 27 (10), 5739-5752 , 2011 2011 Citations: 118
Further insights into the universality of colloidal aggregation P Sandkühler, M Lattuada, H Wu, J Sefcik, M Morbidelli Advances in colloid and interface science 113 (2-3), 65-83 , 2005 2005 Citations: 118
Nanoparticle administration method in cell culture alters particle-cell interaction TL Moore, DA Urban, L Rodriguez-Lorenzo, A Milosevic, F Crippa, ... Scientific reports 9 (1), 900 , 2019 2019 Citations: 113
Dense and strong, but superinsulating silica aerogel S Iswar, S Galmarini, L Bonanomi, J Wernery, E Roumeli, S Nimalshantha, ... Acta Materialia 213, 116959 , 2021 2021 Citations: 110
