Join us for a drink or two at our joint Halloween Party with the other Staff Associations of the HCI.
Friday, the 1st of November starting at 6 pm at Lochness in HXE.
We are organising a running dinner on the 4th of October, together with our friends from AMB, PSA and VAC. For the ones that don't know what a running dinner is, don't worry, there is no running involved.
You pair up with a partner and will host one out of three courses (starters, main, dessert) at your or your partner’s place. For each course you therefore change location and get to enjoy a lovely meal while getting to know people from different departments in HCI.
If you are interested, you can find out more in the registration form: https://forms.gle/gL9wXhKiApijXFHx8
Please assure that your registration went through as we heard of certain people having issues.
(sign up until 18.09.24)
In-person in HCI J4:
Phase separation is a fascinating physical process that is not only responsible for the internal organization of living cells but also a promising tool for structuring soft materials. The central challenge in making meso-structured materials via phase separation is the lack of structural control at length scales beyond the macromolecular scale. In this talk, I will introduce Elastic MicroPhase Separation (EMPS) as a route to create bi-continuous structures in the scale of hundreds of nanometers inside elastomeric networks. I will present the analysis of the microstructure, phase equilibria, and kinetics of the system, and show how it features aspects of both nucleation and growth and spinodal decomposition. Finally, I will demonstrate the potential our approach by toughening polymeric materials, and making bi-continuous structures with controlled structural and anisotropic gradients.
In the last decade, plasmonic and dielectric nanoantennas have revolutionized light manipulation and control at the nanoscale. Interestingly, hot carriers and photoluminescence in metals have opened new pathways for controlling photo(electro)chemical processes and monitoring temperatures. Yet, fundamental questions remain about the microscopic details of these complex light-matter interactions. We have recently developed a well-controlled experimental platform based on ultrathin monocrystalline gold flakes and scanning electrochemical microscopy that, in combination with theory, enables deeper insight into light absorption and emission processes as well as photochemical transformations. In particular, I will present micro-scale photoelectrochemical measurements clarifying the interplay of hot carrier generation/transport and quantifying the injection probability of high-energy d-band holes at the metal-electrolyte interface, connecting it to the ultrafast dynamics of these carriers in monocrystalline metals. Overall, this microscopic insight is critical to advance the design of plasmonic-based energy devices. I will also show complementary results unraveling the origin of luminescence in gold and how crystallinity improves hot carrier dynamics and transport.
In-person in HCI G4:
Multiscale material modeling has two primary goals: (i) understanding and predicant a material’s properties based on its small-scale architecture, and (ii) identifying those small-scale structural features that enable us to control and optimize a material’s properties and performance. Owing to the rise of additive manufacturing, metamaterials (or architected materials) have emerged as a special class of artificial materials with interesting or tunable properties, and as a new playground for computational modeling. While the forward problem (i) has produced many successful modeling techniques across scales, the inverse problem (ii) has remained a challenge: how do we design (meta-)materials with target properties? At the core of this challenge are the abundant design and property spaces, as well as the fact that the map from structure to properties cannot be inverted. Here, we will discuss how in recent years machine learning has offered new opportunities for the inverse design of (meta-)materials through generative models that predict metamaterial architectures with extreme, peculiar, or as-designed mechanical properties
Nanostructured materials promise to unlock new functionality that can address modern challenges in electronics, health, and infrastructure. However, to fully hardness the power of size-based effects, we need to develop new methods for designing microstructurally complex and heterogeneous nanostructures. Furthermore, deep fundamental understanding of designed nanoscale materials is critical for bringing these tools to the materials engineers of tomorrow. Using novel nanoscale additive manufacturing and nanomechanical techniques, we will explore new pathways for nanoscale materials design and investigate the emergingmaterials behaviors that arise at the intersection of geometric and microstructural size-effects. Insights will focus on beginning to untangle the intricate roles of processing and microstructure in advancing nanoscale materials performance.
In-person in HCI J4:
Meat accounts for nearly 60% of all greenhouse gases from food production and is associated with detrimental health effects and ethical issues. Despite these pressing challenges, current meat analogues are not able to replace more than 2.5% of meat consumption due to a lack of texture, taste, and juiciness in plant-based meat. The core challenge in the industry is to effectively replicate plant-based meat products that are as good as meat or even better. Our sustainable and proprietary biostructuring technology developed at Planted allows to create meat that rivals the texture, juiciness, flavor, and aroma of animal-based meat by using a bioprocess that is efficient, ready to scale, and free of additives.
Electron energy-loss spectroscopy (EELS) and energy-dispersive X-ray spectroscopy (EDXS) in the scanning transmission electron microscope (STEM) are powerful methods for elemental mapping at the nano- and atomic scale. In addition, EELS also provides information about chemical bonding or about optical materials properties. Usually, a TEM only gives projected 2D information about a sample, but by acquisition and reconstruction of a tomographic tilt series STEM imaging and spectroscopy can be extended to the third spatial dimension.
In this presentation, I will introduce the principles of spectroscopic STEM imaging for accessing elemental information, but also for the excitation and imaging of surface polariton fields stemming from either plasmons or optical phonons. I will show examples of surface plasmon imaging on different plasmonic materials and devices, ranging from single metallic nanoparticles to more complex multimaterial assemblies. Finally, I will discuss the combination of spectroscopy and tomography for accessing elemental composition in three dimensions, as well as for reconstruction the electromagnetic properties of surface polariton fields.
In-person in HCI G3:
Nature produces soft functional materials displaying exceptional mechanical properties. We are far from synthesizing soft synthetic analogues possessing a similar set of functionality and mechanical properties. This discrepancy in properties is closely related to the degree of compositional and structural control which is much higher in natural soft materials. The level of compositional and structural control depends on the processing of these materials. Inspired by the fabrication of natural soft materials, my group introduces drop-based processes to fabricate granular materials possessing well-defined microstructures and optionally abruptly changing compositions. In this talk, I will demonstrate how we 3D print or cast functional cm-sized granular load-bearing soft materials, including polymers and minerals starting from compartmentalized reagents. Inspired by the mineralization of certain soft natural scaffolds, I will discuss possibilities to transform synthetic soft materials into hard and tough composites with compositions and mechanical properties that are similar to some of the natural counterparts.
Biomaterials for implants, diagnostics or therapeutics have changed the quality of life across the globe. An ever growing number of reports on medical materials reacting in an unpredicted way upon their contact with the complex environment of the human body, however, clearly show that our understanding of the interplay between materials and biological matter is far from complete - baring a risk for patient comfort and safety.
In this talk, I will highlight what we can learn on biomaterials durability and function when taking a zoomed-in look to the material-cell interface at sub-cellular length scales, and show how Materials Science & Engineering can be leveraged to probe biological responses, to ultimately unlock our understanding of the dynamic material-cell interplay.
In-person in HCI G3:
Soft interface-rich multiphase systems such as foams, emulsions, and aerosols are all around us. To characterize the multiphase system dynamics and stability, often information about the thermodynamic and material properties of the interfaces is needed. Microscale platforms can be used to enable measurements of these soft interfaces at length and timescales of interest to the multiphase applications. These advanced platforms can generate, detect, manipulate, and sort microscale droplets and bubbles in an enclosed environment without large and expensive control systems. In this talk, I highlight our group's approach to measuring dynamic surface and interfacial tension, thin film stability, and droplet phase using microfluidic contractions, traps, and wells.
In contrast to ordered crystals, in which atomic structure can be straightforwardly measured using Bragg x-ray scattering, disordered crystals pose a significant problem. Their atomic structure can be probed using diffuse scattering, however data analysis for such signal is currently very limited, time consuming and requires multiple trials and errors. In this talk I will show how to directly solve the structure of disordered material using a flavor of machine learning technique based on the so-called Density Consistency approach.
In-person in HCI G3:
One of the major interests of modern robotics is micromanipulation by active and adaptive materials. An example to such micromanipulation is observed in respiratory system, where pathogen clearance actuation enabled by means of motile cilia. While various types of artificial cilia have been engineered recently, they often involve complex manufacturing protocols and focus on transporting liquids only. Here, we create soft magnetic carpets via an easy self-assembly route based on the Rosensweig instability. These carpets can transport liquids but also solid objects that are larger and heavier than the artificial cilia, using a crowd-surfing effect. This amphibious transportation is locally and reconfigurably tuneable by simple micromagnets or advanced programmable magnetic fields with a high degree of spatial resolution.
While our active carpets are generally applicable to integrated control systems for transport, mixing, and sorting, these effects could also be exploited for microfluidic viscosimetry and elastometry. Finally, I also show briefly how we extended this system to a droplet manipulation platform by simply infusing the soft carpets with a liquid repellent oil.
Usually we think of a metal as a liquid of electrons, particles familiar as individual entities from elementary particle physics. However, in certain materials, magnetic interactions can lead to an increase of the effective mass of the charge carriers by factors of 100s or 1000. Even more striking, near a magnetic phase transition in such, so-called heavy-fermion compounds, the very concept of a particle can break down and give way to an exotic quantum fluid without quantized charge carriers with corresponding, unusual properties. In this talk we give a brief review of this physics and the resulting properties. We then show how this breakdown dynamics is monitored and analyzed by time-resolved terahertz (THz) spectroscopy developed and performed at the Materials Department of the ETH.
In-person in HCI J 4 or on Zoom: https://ethz.zoom.us/j/69001008210
There are thermodynamic reasons why solids are solid and why they can be crystalline. How this happens, however, is less evident. Classical nucleation theory extrapolates thermodynamic properties of bulk materials to systems that merely consist of dozens of atoms or even less. We are interested in studying how solids become solid and how they adopt crystallinity. We try to mimic the formation of nanocrystals in small systems that we can observe by electron microscopy and aim at monitoring the atomic mechanisms that lead to the formation of crystalline matter. We study Pt and Au atoms in the vacuum environment of the microscope and activate them by temperature and the electron beam to form clusters. Approaching more realistic systems, we use small nanoreactors made either of nanodroplets of vacuum-compatible ionic liquids or graphene-based liquid cells to study the formation of nanocrystals in liquids. Although the inevitable electron beam might complicate the data interpretation, all our observations reveal that realistic nucleation reactions are more complex than what the classical nucleation theory predicts, and this enhanced complexity is further reflected in the variety of pathways nanocrystals follow in their growth process.
Diatoms are single-celled organisms with a cell wall made of silica, called the frustule. Their elaborate patterns have fascinated scientists for years, however little is known about the biological and physical mechanisms involved in their organizations.
In this work, we take a top-down approach and examine the micron- scale organization of diatoms from the Coscinodiscus family. We find two competing tendencies of organization, which appear to be controlled by distinct biological pathways. On one hand, micron-scale pores organize locally on a triangular lattice. On the other, lattice vectors tend to point globally toward a center of symmetry. This com- petition results in a frustrated triangular lattice, populated with geo- metrically necessary defects whose density increases near the center.
In-person in HCI J 4 or on Zoom: https://ethz.zoom.us/j/66595365893
I will show several examples of the application of machine learning in materials design.
First, I discuss how screening crystal structure databases using machine learning models constructed based on compositional and structural features led to the development of two superhard materials. Further, to screen for compounds beyond the existing databases, we used an ensemble learning method to directly predict the load-dependent Vickers hardness, using the composition as input. Such a composition-based model is useful to rapidly screen through composition spaces to focus the search space; however, neglecting the influence of crystal structure limits its application. One such example is ferroelectricity. Therefore crystal structure prediction is essential to finding new ferroelectric materials.
A ferroelectric candidate possesses a polar crystal structure, is insulating and thermodynamically favorable. To search for candidates that fulfill these requirements, we developed a framework that consists of a series of machine learning models in conjunction with high-throughput DFT calculations and group theoretical analyses capable of predicting the crystal structure of any given composition. Finally, we developed a machine learning model based on distortion modes to predict new meta-stable crystal structures of BiFeO3.
The Fe-based metallic glasses (MGs) are very promising for applications. Although they are metallic alloys consisting of common chemical elements, the amorphous structure that characterizes the MGs can be obtained only upon quenching the master alloy from the molten state. The resulted samples are usually in form of ribbons, having thicknesses up to few tens of micrometers.
They are soft magnetic materials, showing extremely low coercivity and high permeability, combined with a relatively high saturation magnetization. Therefore, they possess low magnetic losses, making them attractive for electrical transformers, sensors and actuators. Moreover, the soft magnetic properties may be further enhanced upon nanocrystallization. Also, they can be tailored by a proper control of the resulting nanostructure. This particular structure can be achieved only upon annealing the amorphous precursor. A major drawback is that by nanocrystallization the MGs become mechanically brittle and difficult to manipulate. Therefore, a bulk glassy alloy would be more feasible for applications as small parts in e.g. magnetic clutches or actuators.
In the last several years we investigated the possibility to create such bulk nanocrystalline alloys, with customizable structures and magnetic properties. Although the magnetic behavior is understood, the mechanism of the nanocrystallization could not have been resolved without employing state-of-the-art investigation methods, as time-resolved X-ray diffraction in transmission configuration using synchrotron radiation, in-situ and ex-situ transmission electron microscopy and atom probe tomography. The current presentation will guide the listener through these studies and will shed light on the nanocrystallization mechanism.