Modeling Carbon-Based Nanomaterials (CNMs) and Derived Composites and Devices.

A review of different modeling techniques, specifically in the framework of carbon-based nanomaterials (CNMs, including nanoparticles such as graphene and carbon nanotubes-CNTs) and the composites and devices that can be derived from them, is presented. The article emphasizes that the overall performance of these materials depends on mechanisms that operate across different time and spatial scales, requiring tailored approaches based on the material type, size, internal structure/configuration, and the specific properties of interest. Far from attempting to cover the entire spectrum of models, this review examines a wide range of analysis and simulation techniques, highlighting their potential use, some of their weaknesses and strengths, and presenting the latest developments and some application examples.

Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.

The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the custom-designed 1-10% Fe-doped CuO NM library. Effects were assessed using the soil ecotoxicology model (Oligochaeta) in the standard 21 days plus its extension (49 days).

Rocket Dynamics of Capped Nanotubes: A Molecular Dynamics Study.

The study of nanoparticle motion has fundamental relevance in a wide range of nanotechnology-based fields. Molecular dynamics simulations offer a powerful tool to elucidate the dynamics of complex systems and derive theoretical models that facilitate the invention and optimization of novel devices. This research contributes to this ongoing effort by investigating the motion of one-end capped carbon nanotubes within an aqueous environment through extensive molecular dynamics simulations.

Diffusion of curcumin in PLGA-based carriers for drug delivery: a molecular dynamics study.

Context: The rapid growth and diversification of drug delivery systems have been significantly supported by advancements in micro- and nano-technologies, alongside the adoption of biodegradable polymeric materials like poly(lactic-co-glycolic acid) (PLGA) as microcarriers. These developments aim to reduce toxicity and enhance target specificity in drug delivery. The use of in silico methods, particularly molecular dynamics (MD) simulations, has emerged as a pivotal tool for predicting the dynamics of species within these systems.

Enhancing ReaxFF for molecular dynamics simulations of lithium-ion batteries: an interactive reparameterization protocol.

Lithium-ion batteries (LIBs) have become an essential technology for the green economy transition, as they are widely used in portable electronics, electric vehicles, and renewable energy systems. The solid-electrolyte interphase (SEI) is a key component for the correct operation, performance, and safety of LIBs. The SEI arises from the initial thermal metastability of the anode-electrolyte interface, and the resulting electrolyte reduction products stabilize the interface by forming an electrochemical buffer window.

Mesoscopic Modeling and Experimental Validation of Thermal and Mechanical Properties of Polypropylene Nanocomposites Reinforced By Graphene-Based Fillers.

The development of nanocomposites relies on structure-property relations, which necessitate multiscale modeling approaches. This study presents a modeling framework that exploits mesoscopic models to predict the thermal and mechanical properties of nanocomposites starting from their molecular structure. In detail, mesoscopic models of polypropylene (PP)- and graphene-based nanofillers (graphene (Gr), graphene oxide (GO), and reduced graphene oxide (rGO)) are considered.

Method for predicting the wettability of micro-structured surfaces by continuum phase-field modelling.

Numerical prediction of material properties is attracting the attention of the scientific community and industry because of its usefulness in the design process. In the fields of fluid dynamics and microfluidics, several simulation methods have been proposed and adopted to evaluate the properties of surfaces and material interfaces, thanks to the increasing computational power available. However, despite the efforts made, a general and standardized methodology for implementing such methods is still lacking, thus requiring a trial-and-error approach for each new problem, making them difficult to implement and creating a bottleneck at the initial stage of surface design.

Atomistic to Mesoscopic Modelling of Thermophysical Properties of Graphene-Reinforced Epoxy Nanocomposites.

This research addresses the need for a multiscale model for the determination of the thermophysical properties of nanofiller-enhanced thermoset polymer composites. Specifically, we analyzed the thermophysical properties of an epoxy resin containing bisphenol-A diglyceryl ether (DGEBA) as an epoxy monomer and dicyandiamide (DICY) and diethylene triamine (DETA) as cross-linking agents. The cross-linking process occurs at the atomistic scale through the formation of bonds among the reactive particles within the epoxy and hardener molecules.

The impact of physicochemical features of carbon electrodes on the capacitive performance of supercapacitors: a machine learning approach.

Hybrid electric vehicles and portable electronic systems use supercapacitors for energy storage owing to their fast charging/discharging rates, long life cycle, and low maintenance. Specific capacitance is regarded as one of the most important performance-related characteristics of a supercapacitor's electrode. In the current study, Machine Learning (ML) algorithms were used to determine the impact of various physicochemical properties of carbon-based materials on the capacitive performance of electric double-layer capacitors.

Ultrafast nano generation of acoustic waves in water via a single carbon nanotube.

Generation of ultra high frequency acoustic waves in water is key to nano resolution sensing, acoustic imaging and theranostics. In this context water immersed carbon nanotubes (CNTs) may act as an ideal optoacoustic source, due to their nanometric radial dimensions, peculiar thermal properties and broad band optical absorption. The generation mechanism of acoustic waves in water, upon excitation of both a single-wall (SW) and a multi-wall (MW) CNT with laser pulses of temporal width ranging from 5 ns down to ps, is theoretically investigated via a multiscale approach.

Anisotropic Electrostatic Interactions in Coarse-Grained Water Models to Enhance the Accuracy and Speed-Up Factor of Mesoscopic Simulations.

Water models with realistic physical-chemical properties are essential to study a variety of biomedical processes or engineering technologies involving molecules or nanomaterials. Atomistic models of water are constrained by the feasible computational capacity, but calibrated coarse-grained (CG) ones can go beyond these limits. Here, we compare three popular atomistic water models with their corresponding CG model built using finite-size particles such as ellipsoids.

Machine learning and materials modelling interpretation of toxicological response to TiO nanoparticles library (UV and non-UV exposure).

Assessing the risks of nanomaterials/nanoparticles (NMs/NPs) under various environmental conditions requires a more systematic approach, including the comparison of effects across many NMs with identified different but related characters/descriptors. Hence, there is an urgent need to provide coherent (eco)toxicological datasets containing comprehensive toxicity information relating to a diverse spectra of NPs characters. These datasets are test benches for developing holistic methodologies with broader applicability.

Effect of water nanoconfinement on the dynamic properties of paramagnetic colloidal complexes.

The anomalous behavior of confined water at the nanoscale has remarkable implications in a number of nanotechnological applications. In this work, we analyze the effect of water self-diffusion on the dynamic properties of a solvated gadolinium-based paramagnetic complex, typically used for contrast enhancement in magnetic resonance imaging. In particular, we examine the effect of silica-based nanostructures on water behavior in the proximity of the paramagnetic complex via atomistic simulations, and interpret the resulting tumbling dynamics in the light of the local solvent modification based on the Lipari-Szabo formalism and of the fractional Stokes-Einstein relation.

Multistage and passive cooling process driven by salinity difference.

Space cooling in buildings is anticipated to rise because of an increasing thermal comfort demand worldwide, and this calls for cost-effective and sustainable cooling technologies. We present a proof-of-concept multistage device, where a net cooling capacity and a temperature difference are demonstrated as long as two water solutions at disparate salinity are maintained. Each stage is made of two hydrophilic layers separated by a hydrophobic membrane.

Mechanistic correlation between water infiltration and framework hydrophilicity in MFI zeolites.

Hydrophobic zeolites are nanoporous materials that are attracting an increasing interest, especially for catalysis, desalination, energy storage and biomedical applications. Nevertheless, a more profound understanding and control of water infiltration in their nanopores is still desirable to rationally design zeolite-based materials with tailored properties. In this work, both atomistic simulations and previous experimental data are employed to investigate water infiltration in hydrophobic MFI zeolites with different concentration of hydrophilic defects.

Nano-metering of Solvated Biomolecules Or Nanoparticles from Water Self-Diffusivity in Bio-inspired Nanopores.

Taking inspiration from the structure of diatom algae frustules and motivated by the need for new detecting strategies for emerging nanopollutants in water, we analyze the potential of nanoporous silica tablets as metering devices for the concentration of biomolecules or nanoparticles in water. The concept relies on the different diffusion behavior that water molecules exhibit in bulk and nanoconfined conditions, e.g.

From GROMACS to LAMMPS: GRO2LAM : A converter for molecular dynamics software.

Atomistic simulations have progressively attracted attention in the study of physical-chemical properties of innovative nanomaterials. GROMACS and LAMMPS are currently the most widespread open-source software for molecular dynamics simulations thanks to their good flexibility, numerous functionalities and responsive community support. Nevertheless, the very different formats adopted for input and output files are limiting the possibility to transfer GROMACS simulations to LAMMPS.

Coffee-based colloids for direct solar absorption.

Despite their promising thermo-physical properties for direct solar absorption, carbon-based nanocolloids present some drawbacks, among which the unpleasant property of being potentially cytotoxic and harmful to the environment. In this work, a sustainable, stable and inexpensive colloid based on coffee is synthesized and its photo-thermal properties investigated. The proposed colloid consists of distilled water, Arabica coffee, glycerol and copper sulphate, which provide enhanced properties along with biocompatibility.

Mesoscopic Moment Equations for Heat Conduction: Characteristic Features and Slow-Fast Mode Decomposition.

In this work, we derive different systems of mesoscopic moment equations for the heat-conduction problem and analyze the basic features that they must hold. We discuss two- and three-equation systems, showing that the resulting mesoscopic equation from two-equation systems is of the telegraphist's type and complies with the Cattaneo equation in the Extended Irreversible Thermodynamics Framework. The solution of the proposed systems is analyzed, and it is shown that it accounts for two modes: a slow diffusive mode, and a fast advective mode.

Efficient steam generation by inexpensive narrow gap evaporation device for solar applications.

Technologies for solar steam generation with high performance can help solving critical societal issues such as water desalination or sterilization, especially in developing countries. Very recently, we have witnessed a rapidly growing interest in the scientific community proposing sunlight absorbers for direct conversion of liquid water into steam. While those solutions can possibly be of interest from the perspective of the involved novel materials, in this study we intend to demonstrate that efficient steam generation by solar source is mainly due to a combination of efficient solar absorption, capillary water feeding and narrow gap evaporation process, which can also be achieved through common materials.

Thermal transport across nanoparticle-fluid interfaces: the interplay of interfacial curvature and nanoparticle-fluid interactions.

We investigate the general dependence of the thermal transport across nanoparticle-fluid interfaces using molecular dynamics computations. We show that the thermal conductance depends strongly both on the wetting characteristics of the nanoparticle-fluid interface and on the nanoparticle size. Strong nanoparticle-fluid interactions, leading to full wetting states in the host fluid, result in high thermal conductances and efficient interfacial transport of heat.

Thermal transport phenomena in nanoparticle suspensions.

Nanoparticle suspensions in liquids have received great attention, as they may offer an approach to enhance thermophysical properties of base fluids. A good variety of applications in engineering and biomedicine has been investigated with the aim of exploiting the above potential. However, the multiscale nature of nanosuspensions raises several issues in defining a comprehensive modelling framework, incorporating relevant molecular details and much larger scale phenomena, such as particle aggregation and their dynamics.

Interplay between hydrophilicity and surface barriers on water transport in zeolite membranes.

A comprehensive understanding of molecular transport within nanoporous materials remains elusive in a broad variety of engineering and biomedical applications. Here, experiments and atomistic simulations are synergically used to elucidate the non-trivial interplay between nanopore hydrophilicity and surface barriers on the overall water transport through zeolite crystals. At these nanometre-length scales, these results highlight the dominating effect of surface imperfections with reduced permeability on the overall water transport.

Hierarchically-Structured Magnetic Nanoconstructs with Enhanced Relaxivity and Cooperative Tumor Accumulation.

Iron oxide nanoparticles are formidable multifunctional systems capable of contrast enhancement in magnetic resonance imaging; guidance under remote fields; heat generation; and biodegradation. Yet, this potential is underutilized in that each function manifests at different nanoparticle sizes. Here, sub-micrometer discoidal magnetic nanoconstructs are realized by confining 5 nm ultra-small super-paramagnetic iron oxide nanoparticles (USPIOs) within two different mesoporous structures, made out of silicon and polymers.

Water transport control in carbon nanotube arrays.

Based on a recent scaling law of the water mobility under nanoconfined conditions, we envision novel strategies for precise modulation of water diffusion within membranes made of carbon nanotube arrays (CNAs). In a first approach, the water diffusion coefficient D may be tuned by finely controlling the size distribution of the pore size. In the second approach, D can be varied at will by means of externally induced electrostatic fields.