Criblage à haut débit | EPFL Graph Search

thumb|Machine de criblage à haut débit en Allemagne Le criblage à haut débit (high-throughput screening, HTS) désigne dans le domaine de la pharmacologie, de la biochimie, de la génomique et de la protéomique, les techniques visant à étudier et à identifier dans les chimiothèques et ciblothèques, des molécules aux propriétés nouvelles, biologiquement actives. L’expression haut débit évoque ici l’utilisation de la robotique, de l’informatique et de la bio-informatique pour accélérer la phase de test des molécules, protéines, catalyseurs, etc. en vue de processus de production de matériaux, médicaments, etc. Procédure Le criblage à haut débit consiste à faire réagir simultanément un grand nombre de molécules différentes avec un substrat donné, en vue d’identifier, en un minimum de temps, celles de ces molécules qui présentent un intérêt éventuel pour une application déterminée. Criblage virtuel (ou essai in silico) Pour encore accélérer les découvertes, en lim

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Sokseiha Muy, Yang Yu

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different traditional and emerging approaches to demonstrate their inherent connection and highlight the evolving paradigms of materials design. Breakthroughs in molecular and materials discovery require meaningful outliers to be identified in existing trends. As knowledge accumulates, the inherent bias of human intuition makes it harder to elucidate increasingly opaque chemical and physical principles. Moreover, given the limited manual and intellectual throughput of investigators, these principles cannot be efficiently applied to design new materials across a vast chemical space. Many data-driven approaches, following advances in high-throughput capabilities and machine learning, have tackled these limitations. In this Review, we compare traditional, human-centred methods with state-of-the-art, data-driven approaches to molecular and materials discovery. We first introduce the limitations of human-centred Edisonian, model-system and descriptor-based approaches. We then discuss how data-driven approaches can address these limitations by promoting throughput, reducing cognitive overload and biases, and establishing atomistic understanding that is transferable across a broad chemical space. We examine how high-throughput capabilities can be combined with active learning and inverse design to efficiently optimize materials out of millions or an intractable number of candidates. Lastly, we pinpoint challenges to accelerate future workflows and ultimately enable self-driving platforms, which automate and streamline the optimization of molecules and materials in iterative cycles.

NATURE PORTFOLIO2022

Up-scalable plasmonic and diffractive nanostructures

Fabian Michael Lütolf

Since most of the academic photonic and plasmonic nanostructures are based on slow and expensive electron beam lithography processes, there is a need for innovative alternatives suitable for industrial manufacturing. Large areas need to be patterned with a high throughput, which is for example achieved with roll-to-roll machines. Up-scalable designs of photonic and plasmonic nanostructures are therefore studied in this thesis. Typical industrial processes include embossing and evaporation, which are consequently used throughout the thesis. I propose oblique evaporation of high refractive index materials to render binary gratings highly efficient for first order transmission. Zinc sulfide coatings are employed to diffract close to 70% of unpolarized green light. Simulations further show that they can be encapsulated to protect them from environmental influences like humidity, wear or dust, while retaining their exceptional diffractive properties, which is very appealing for outdoor applications. I also show that thin metallic coatings can attain similar efficiencies for TE polarized light. The effect is asymmetric and shows a maximum at the Wood-Rayleigh anomaly, which results in orientation dependent coloration of the zero order as well as first order transmittances. A large part of the standard RGB gamut can be covered through proper adjustment of the grating parameters. Combination of zero order and first order effects allows creation of color appearances that switch when rotating or flipping the device. I finally present how floating images become apparent when a patterned light source like e.g. a mobile phone is used in conjunction with the metallized grating. Direct transfer of plasmonic technology from universities to industry is often not possible: in academia, metallic nanostructures often require a lateral resolution of a few nanometers, which is challenging to achieve in up-scalable processes. Thicknesses on the other hand can be controlled in this regime using evaporation techniques, which are hence powerful methods for high-throughput production. In this thesis, Fano-resonant, U-shaped nanowires are created with oblique metal deposition. In order to make them available for mass-production, aluminum is chosen as the plasmonic material. The surface integral equation method is used to investigate near-fields and charge distributions, which shed light onto the physics behind the present resonances. A surface plasmon polariton is found to couple to a localized plasmonic mode with a hexapolar charge distribution. It is finally shown that the Fano-resonance can be accurately tuned by adapting evaporation angle and metal thickness. These two parameters can easily be accessed and would allow for good control over the optical response even in an industrial environment. The applicability of the above insights is then demonstrated by creating a strain sensor. To that end, the process is transferred to a stretchable polymer and when elongating the structure perpendicular to the wires, the polymeric spacing between them is expanded. The sensitivity of the Fano-resonance to this change in inter-wire distance is investigated and a strong damping is observed. Through careful design, a clearly visible color switch from purple to green is achieved for elongations less than 20%. The sensor was deemed to be very durable, as no deterioration in the color or the spectral response was observed even after several strain cycles.

EPFL2015

Rapid screening of nanopore candidates in nanoporous single-layer graphene for selective separations using molecular visualization and interatomic potentials

Luc Sébastien Bondaz, Rohit Karnik

Nanoporous single-layer graphene is promising as an ideal membrane because of its extreme thinness, chemical resistance, and mechanical strength, provided that selective nanopores are successfully incorporated. However, screening and understanding the transport characteristics of the large number of possible pores in graphene are limited by the high computational requirements of molecular dynamics (MD) simulations and the difficulty in experimentally characterizing pores of known structures. MD simulations cannot readily simulate the large number of pores that are encountered in actual membranes to predict transport, and given the huge variety of possible pores, it is hard to narrow down which pores to simulate. Here, we report alternative routes to rapidly screen molecules and nanopores with negligible computational requirement to shortlist selective nanopore candidates. Through the 3D representation and visualization of the pores' and molecules' atoms with their van der Waals radii using open-source software, we could identify suitable C-passivated nanopores for both gas- and liquid-phase separation while accounting for the pore and molecule shapes. The method was validated by simulations reported in the literature and was applied to study the mass transport behavior across a given distribution of nanopores. We also designed a second method that accounts for Lennard-Jones and electrostatic interactions between atoms to screen selective non-C-passivated nanopores for gas separations. Overall, these visualization methods can reduce the computational requirements for pore screening and speed up selective pore identification for subsequent detailed MD simulations and guide the experimental design and interpretation of transport measurements in nanoporous atomically thin membranes.