Additive manufacturing of silica aerogels.

Owing to their ultralow thermal conductivity and open pore structure1-3, silica aerogels are widely used in thermal insulation4,5, catalysis6, physics7,8, environmental remediation6,9, optical devices10 and hypervelocity particle capture11. Thermal insulation is by far the largest market for silica aerogels, which are ideal materials when space is limited. One drawback of silica aerogels is their brittleness. Fibre reinforcement and binders can be used to overcome this for large-volume applications in building and industrial insulation5,12, but their poor machinability, combined with the difficulty of precisely casting small objects, limits the miniaturization potential of silica aerogels. Additive manufacturing provides an alternative route to miniaturization, but was "considered not feasible for silica aerogel"13. Here we present a direct ink writing protocol to create miniaturized silica aerogel objects from a slurry of silica aerogel powder in a dilute silica nanoparticle suspension (sol). The inks exhibit shear-thinning behaviour, owing to the high volume fraction of gel particles. As a result, they flow easily through the nozzle during printing, but their viscosity increases rapidly after printing, ensuring that the printed objects retain their shape. After printing, the silica sol is gelled in an ammonia atmosphere to enable subsequent processing into aerogels. The printed aerogel objects are pure silica and retain the high specific surface area (751 square metres per gram) and ultralow thermal conductivity (15.9 milliwatts per metre per kelvin) typical of silica aerogels. Furthermore, we demonstrate the ease with which functional nanoparticles can be incorporated. The printed silica aerogel objects can be used for thermal management, as miniaturized gas pumps and to degrade volatile organic compounds, illustrating the potential of our protocol.

Energy Formulation for Infinite Structures: Order Parameter for Percolation, Critical Bonds, and Power-Law Scaling of Contact-Based Transport.

Investigating heterogeneous materials' microstructure, often simulated using periodic images, is crucial for understanding their physical traits. We propose a generic spring-based representation for periodic two-component structures. The equilibrium energy in this framework serves as an order parameter, offering an analytical expression for wrapping and introducing the concept of critical bonds. We show that these minimum bonds for depercolation can be efficiently detected. The number of critical bonds scales with system size, accurately capturing contact-based transport's scaling. This approach holds potential to analyze functional robustness of networks.

The Atomic-Level Structure of Cementitious Calcium Aluminate Silicate Hydrate.

Despite use of blended cements containing significant amounts of aluminum for over 30 years, the structural nature of aluminum in the main hydration product, calcium aluminate silicate hydrate (C-A-S-H), remains elusive. Using first-principles calculations, we predict that aluminum is incorporated into the bridging sites of the linear silicate chains and that at high Ca:Si and H2O ratios, the stable coordination number of aluminum is six. Specifically, we predict that silicate-bridging [AlO2(OH)4]5- complexes are favored, stabilized by hydroxyl ligands and charge balancing calcium ions in the interlayer space. This structure is then confirmed experimentally by one- and two-dimensional dynamic nuclear polarization enhanced 27Al and 29Si solid-state NMR experiments. We notably assign a narrow 27Al NMR signal at 5 ppm to the silicate-bridging [AlO2(OH)4]5- sites and show that this signal correlates to 29Si NMR signals from silicates in C-A-S-H, conflicting with its conventional assignment to a "third aluminate hydrate" (TAH) phase. We therefore conclude that TAH does not exist. This resolves a long-standing dilemma about the location and nature of the six-fold-coordinated aluminum observed by 27Al NMR in C-A-S-H samples.

Beyond Unpredictability: The Importance of Reproducibility in Understanding the Protein Corona of Nanoparticles.

While it is well established that the surface of a nanoparticle plays a pivotal role for the protein corona, the vast number of proteins present in biological media render general conclusions about affinities between nanoparticle surfaces and proteins nontrivial. Recently published articles increasingly reveal differences between systems and an ever increasing number of influencing factors for the protein corona. In contrast, the present study posits that the reported differences may, at least in part, be due to poor experimental design, which leads to biased results. The present study investigates protein adsorption onto silica nanoparticles with different chemical groups on the surface by the statistical analysis of triplicate measurements as well as control measurements. We demonstrate that 60% of the identified protein types did not have any significant affinities for the nanoparticles. Of the remaining 40%, 60% were driven by surface charges and only 40% preferentially adsorbed onto specific surface groups. Furthermore, we found that of the 20 most abundant proteins in the serum, only five bound to the nanoparticles studied here. We illustrate the importance of control replicate experiments to avoid exaggerated differences between systems and to properly quantify the differences and similarities between comparable systems.

Learning Adsorption Patterns on Amorphous Surfaces.

The physicochemical heterogeneity found on amorphous surfaces leads to a complex interaction of adsorbate molecules with topological and undercoordinated defects, which enhance the adsorption capacity and can participate in catalytic reactions. The identification and analysis of the adsorption structure observed on amorphous surfaces require novel tools that allow the segmentation of the surfaces into complex-shaped regions that contrast with the periodic patterns found on crystalline surfaces. We propose a Random Forest (RF) classifier that segments the surface into regions that can then be further analyzed and classified to reveal the dynamics of the interaction with the adsorbate. The RF segmentation is applied to the surface density map of the adsorbed molecules and employs multiple features (intensity, gradient, and the eigenvalues of the Hessian matrix) which are nonlocal and allow a better identification of the adsorption structures. The segmentation depends on a set of parameters that specify the training set and can be tailored to serve the specific purpose of the segmentation. Here, we consider an example in which we aim to separate highly heterogeneous regions from weakly heterogeneous regions. We demonstrate that the RF segmentation is able to separate the surface into a fully connected weakly heterogeneous region (whose behavior is somehow similar to crystalline surfaces and has an exponential distribution of the residence time) and a very heterogeneous region characterized by a complex residence-time distribution, which is generated by the undercoordinated defects and is responsible for the peculiar characteristics of the amorphous surface.

The poor reliability of thermal conductivity data in the aerogel literature: a call to action!

Aerogels are an exciting class of materials with record-breaking properties including, in some cases, ultra-low thermal conductivities. The last decade has seen a veritable explosion in aerogel research and industry R&D, leading to the synthesis of aerogels from a variety of materials for a rapidly expanding range of applications. However, both from the research side, and certainly from a market perspective, thermal insulation remains the dominant application. Unfortunately, continued progress in this area suffers from the proliferation of incorrect thermal conductivity data, with values that often are far outside of what is possible within the physical limitations. This loss of credibility in reported thermal conductivity data poses difficulties in comparing the thermal performance of different types of aerogels and other thermal superinsulators, may set back further scientific progress, and hinder technology transfer to industry and society. Here, we have compiled 519 thermal conductivity results from 87 research papers, encompassing silica, other inorganic, biopolymer and synthetic polymer aerogels, to highlight the extent of the problem. Thermal conductivity data outside of what is physically possible are common, even in high profile journals and from the world's best universities and institutes. Both steady-state and transient methods can provide accurate thermal conductivity data with proper instrumentation, suitable sample materials and experienced users, but nearly all implausible data derive from transient methods, and hot disk measurements in particular, indicating that under unfavorable circumstances, and in the context of aerogel research, transient methods are more prone to return unreliable data. Guidelines on how to acquire reliable thermal conductivity data are provided. This paper is a call to authors, reviewers, editors and readers to exercise caution and skepticism when they report, publish or interpret thermal conductivity data.

Voronoi tessellation-based algorithm for determining rigorously defined classical and generalized geometric pore size distributions.

The geometric pore size distribution (PSD) P(r) as function of pore radius r is an important characteristic of porous structures, including particle-based systems, because it allows us to analyze adsorption behavior, the strength of materials, etc. Multiple definitions and corresponding algorithms, particularly in the context of computational approaches, exist that aim at calculating a PSD, often without mentioning the employed definition and therefore leading to qualitatively very different and apparently incompatible results. Here, we analyze the differences between the PSDs introduced by Torquato et al. and the more widely accepted one provided by Gelb and Gubbins, here denoted as T-PSD and G-PSD, respectively, and provide rigorous mathematical definitions that allow us to quantify the qualitative differences. We then extend G-PSD to incorporate the ideas of coating, which is significant for nanoparticle-based systems, and of finite probe particles, which is crucial to micro and mesoporous particles. We derive how the extended and classical versions are interrelated and how to calculate them properly. We next analyze various numerical approaches used to calculate classical G-PSDs and may be used to calculate the generalized G-PSD. To this end, we propose a simple yet sufficiently complicated benchmark for which we calculate the different PSDs analytically. This approach allows us to completely rule out a recently proposed algorithm based on radical Voronoi tessellation. Instead, we find and prove that the output of a grid-free classical Voronoi tessellation, namely, the properties of its triangulated faces, can be used to formulate an algorithm, which is capable of calculating the generalized G-PSD for a system of monodisperse spherical particles (or points) to any precision, using analytical expressions. The Voronoi-based algorithm developed and provided here has optimal scaling behavior and outperforms grid-based approaches.

Silica-Resorcinol-Melamine-Formaldehyde Composite Aerogels as High-Performance Thermal Insulators.

Here, we report the gelation and supercritical drying of ethanol-based silica-resorcinol-melamine-formaldehyde (RMF) composite aerogels with relative concentrations of initial reagents ranging from neat silica to neat RMF alcogels. The as-prepared materials are subsequently supercritically dried with carbon dioxide. Their properties include a thermal conductivity in the 15-20 mW·m-1·K-1 range even with a silica content as low as 20%wt. The possible reasons behind this interesting insulation performance and the mechanisms leading to the underlying gel structure are discussed in depth. A focus is made on the different gelation modes happening between the RMF and silica phases, from a coating of silica surfaces with RMF species to discontinuous RMF particles within a silica backbone and a continuous RMF backbone with isolated silica particles. The implications in terms of mechanical properties and thermal conductivity are elaborated upon. The initial ratio of silica-RMF species in this ethanol-based synthesis affects the micro- and macrostructure of the composites, resulting in materials with drastically different pore structures and thus an interesting array of possibilities for a new class of silica-organic composite aerogels, based on a sol-gel process.

Aqueous stabilisation of carbon-encapsulated superparamagnetic α-iron nanoparticles for biomedical applications.

Carbon-based nanomaterials, such as carbon-encapsulated magnetic nanoparticles (CEMNP, core@shell), show a wide range of desirable properties for applications in the biomedical field (clinical MRI, hyperthermia), for energy production and storage (hydrogen storage), for the improvement of electronic components and for environmental applications (water-treatment). However, this kind of nanoparticle tends to aggregate in water suspensions. This often hampers the processability of the suspensions and presents an obstacle to their application in many fields. Here the stabilisation of core-shell Fe-C nanoparticles by surface adsorbed polyvinyl-alcohol (PVA) is presented. Different PVA/CEMNP mass ratios (9, 36, 144 and 576 w/w) were studied. Several characterisation techniques were used in order to determine the size distribution of the particles and to optimize the PVA/CEMNP ratio. A good colloidal stability was obtained for spherical nanoparticles about 50 nm in diameter containing several superparamagnetic Fe cores. The nanoparticles were found to be isolated and well dispersed in solution. The use of PVA for coating carbon-encapsulated Fe nanoparticles does not only result in a good colloidal stability in aqueous suspensions, but the resulting particles also show low cytotoxicity and an interesting cell internalization behaviour. The simple stabilization method developed here can likely be extended to other core@shell nanoparticle systems as well as other carbon-based nanomaterials in the future.