arXiv subjects

Christoph Langhammer

Publications and source records attributed to Christoph Langhammer.

8 recordsLinked to original sources

arXiv2026

Bayesian Optimization for Practical H2 Sensors: Inverse Design of Pd-based Plasmonic Metasurfaces

Hydrogen detection is becoming increasingly important as its use grows across energy and industrial systems. Optical sensing platforms based on palladium (Pd) nanoparticles are attractive for this task because hydrogen uptake directly alters their plasmonic response. Organizing such nanoparticles into periodic two-dimensional arrays, known as metasurfaces, further enhances their optical response through collective resonances. However, the large design space presented by chemical composition, nanoparticle geometry, and array structure calls for systematic approaches for optimizing complex nanoalloy metasurface geometries. Here, we develop an inverse-design framework based on Bayesian optimization that couples first-principles dielectric functions with electromagnetic simulations to identify high-performance PdAu nanodisk arrays for hydrogen sensing in the 1 to 100 mbar range where the flammability of H2 becomes a concern. We use our approach to search a five-dimensional design space, comprising nanodisk height and radius, array pitch, polymer coating thickness, and Au fraction in order to maximize the H-induced change in extinction at a single wavelength of choice. The results show that integrating first-principles optical models with data-efficient optimization yields experimentally feasible nanoparticle metasurfaces tailored for targeted hydrogen pressures, while providing a pathway to future multiobjective sensor design. They also reveal remaining gaps in the modeling methodologies that still limit the quantitative reliability of the approach.

physics.optics↗

arXiv2026

Revealing the kinetics of interfacial surfactant phase transitions through multiscale simulations and in-situ plasmonic sensing

Surfactant self-assembly at solid-liquid interfaces governs interfacial stability, transport, and reactivity across many technologies, yet resolving interfacial surfactant phases and their transition kinetics in situ remains challenging. Here, we establish an atomistically grounded plasmonic framework that quantitatively maps interfacial surfactant phases and phase transitions onto optical signatures. Distinct morphologies differ in packing and hydration, modifying the effective permittivity within the optical near field and producing surfactant phase-specific plasmonic extinction peak shifts. Using cetyltrimethylammonium bromide on silica as a prototypical surfactant-surface system, we combine atomistic simulations, electronic-structure calculations, and continuum electrodynamics to translate molecular morphologies into predicted spectral shifts for literature-reported surface phases. We experimentally confirm the predicted ordering and magnitude of steady-state peak shifts during stepwise concentration changes, and extract transition kinetics from exponential relaxations of the time-resolved peak shift. A key mechanistic signature is reversal of the spectral shift direction upon transition from an impermeable bilayer to a water-accessible, channel-containing phase, consistent with hydration-driven reduction of the local effective permittivity. Because the approach relies on dielectric contrast in the plasmonic near field and works through a dielectric overlayer, it provides a broadly applicable route for real-time identification of interfacial surfactant phases and their kinetics in aqueous conditions.

cond-mat.mtrl-sci↗

arXiv2025

Visible Light Spectroscopy of Liquid Solutes from Femto- to Attoliter Volumes inside a Single Nanofluidic Channel

UV-Vis spectroscopy is a workhorse in analytical chemistry that finds application in life science, organic synthesis and energy technologies like photocatalysis. In its traditional implementation with cuvettes, it requires sample volumes in the milliliter range. Here, we show how Nanofluidic Scattering Spectroscopy, NSS, which measures visible light scattered from a single nanochannel in a spectrally resolved way, can reduce this sample volume to the attoliter range for solute concentrations in the mM regime, which corresponds to as few as 105 probed molecules. The connection of the nanochannel to a microfluidic in-and outlet system enables such measurements in continuous flow conditions, and the integrated online optical reference system ensures their long-term stability. On the examples of the non-absorbing solutes NaCl and H2O2, and the dyes Brilliant Blue, Allura Red and Fluorescein, we demonstrate that spectral fingerprints can be obtained with good accuracy and that solute concentrations inside the nanochannel can be determined based on NSS-spectra. Furthermore, by applying a reverse Kramers-Kronig transformation to NSS-spectra, we show that the molar extinction coefficient of the dye solutes can be extracted with excellent agreement with the literature values. These results thus advertise NSS as a versatile tool for the spectroscopic analysis of solutes in situations where nanoscopic sample volumes, as well as continuous flow measurements, are critical, e.g., in single particle catalysis or nanoscale flow cytometry.

physics.chem-ph↗

arXiv2025

Femtoliter Batch Reactors for Nanofluidic Scattering Spectroscopy Analysis of Catalytic Reactions on Single Nanoparticles

Macroscopic batch reactors are a core concept in chemical synthesis and catalysis due to their ability to ensure high conversion rates of the used reactants. At the nanoscale, such reactors hold promise due to their potential to enable chemistry in confinement under well-controlled mass transport conditions, and as enablers for the characterization of catalytic reactions on tiny active surface areas, such as single nanoparticles. However, their practical implementation and the readout of reaction products if used for the study of catalytic reactions is challenging due to their tiny volume and the requirement of being able to transiently open and close such nanoscopic batch reactors. Here, we introduce a liquid phase nanofluidic batch reactor concept with a volume of 4.8 femtoliters that conveniently can be opened and closed using a bypassing N2 gas stream, and that in combination with nanofluidic scattering spectroscopy readout enables the characterization of a catalytic reaction on a single nanoparticle inside the reactor, as we demonstrate on the catalytic reduction of fluorescein by sodium borohydride on a Au catalyst.

physics.chem-ph↗

arXiv2023

Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning

The ability to rapidly detect hydrogen gas upon occurrence of a leak is critical for the safe large-scale implementation of hydrogen (energy) technologies. However, to date, no technically viable sensor solution exists that meets the corresponding response time targets set by stakeholders at technically relevant conditions. Here, we demonstrate how a tailored Long Short-term Transformer Ensemble Model for Accelerated Sensing (LEMAS) accelerates the response of a state-of-the-art optical plasmonic hydrogen sensor by up to a factor of 40 in an oxygen-free inert gas environment, by accurately predicting its response value to a hydrogen concentration change before it is physically reached by the sensor hardware. Furthermore, it eliminates the pressure dependence of the response intrinsic to metal hydride-based sensors, while leveraging their ability to operate in oxygen-starved environments that are proposed to be used for inert gas encapsulation systems of hydrogen installations. Moreover LEMAS provides a measure for the uncertainty of the predictions that is pivotal for safety-critical sensor applications. Our results thus advertise the use of deep learning for the acceleration of sensor response, also beyond the realm of plasmonic hydrogen detection.

physics.comp-ph↗

arXiv2023

Label-free Imaging of Catalytic H2O2 Decomposition on Single Colloidal Pt Nanoparticles using Nanofluidic Scattering Microscopy

Single particle catalysis aims at determining factors that dictate nanoparticle activity and selectivity. Existing methods often use fluorescent model reactions at low reactant concentrations, operate at low pressures, or rely on plasmonic enhancement effects. Hence, methods to measure single nanoparticle activity at technically relevant conditions, and without fluorescence or other enhancement mechanisms, are still lacking. Here, we introduce nanofluidic scattering microscopy to fill this gap. By detecting minuscule refractive index changes in a liquid flushed through a nanochannel, we demonstrate that local H2O2 concentration changes in water can be accurately measured. Applying this principle, we analyze the H2O2 concentration profiles adjacent to single colloidal Pt nanoparticles during catalytic H2O2 decomposition into O2 and H2O and derive the particles individual turnover frequencies from the growth rate of O2 gas bubbles formed in their respective nanochannel during reaction.

physics.chem-ph↗

arXiv2023

Roadmap on Deep Learning for Microscopy

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

physics.optics↗

arXiv2012

Oscillatory optical response of amorphous plasmonic nanoparticle arrays

The optical response of metallic nanoparticle arrays is dominated by localized surface plasmon excitations and is the sum of individual particle contributions modified by inter-particle coupling depending on specific array geometry. Here we scrutinize how experimentally measured properties of large scale (30 mm$^{2}$) amorphous Au nanodisk arrays stem from single particle properties and their interaction. They give rise to a distinct oscillatory behavior of the plasmon peak position, full-width at half-maximum, and extinction efficiency which depends on the minimum particle center-to-center (CC) distance.

physics.optics↗