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Eingeladener Vortrag
- nein (1)
Nanopipettes are a type of solid-state nanopore with needle-like geometry. Their applications range from imaging, sensing, diagnostics, and use as injectors. The response of nanopipette sensors is highly dependent on the size, geometry and chemical properties of the sensing region. As nanopipettes are increasingly tuned and modified for specific analytes, a better understanding of the surface chemistry and morphology of the inner channel is necessary. For exploring these effects, quartz nanopipettes were modified by gas phase silanization, a well-utilised technique in the field to enhance performance of nanopipettes, and further functionalised with a metal bis thiolate complex, to aid in chemical analysis. The inner channel of the sensing region was exposed with focused ion beam (FIB) milling as a dedicated sample preparation method for nanoscale surface analysis. The sample characterisation involved scanning electron microscopy (SEM), Auger electron spectroscopy (AES) and low-energy energy dispersive x-ray spectroscopy (EDX). The results demonstrate the first steps towards full characterisation of nanopipettes at the nanoscale, notably with access to the inner channel. The methods used here can be applied to gain further understanding of the response of these sensors to complex analytes, and allow for the study of different surface functionalisation at the all-important sensing region.
Nanopipettes are a type of solid-state nanopore with needle-like geometry. Their applications range from imaging, sensing, diagnostics, and use as injectors. The response of nanopipette sensors is highly dependent on the size, geometry and chemical properties of the sensing region. As they are increasingly tuned and modified for specific analytes, a better understanding of the surface chemistry and morphology of the inner channel is necessary. With the aim of developing a comprehensive approach for characterisation of such nanopipettes, this research focuses on combining surface-sensitive analysis methods with advanced sample preparation techniques. Quartz substrates were modified by gas phase silanization, a well-utilised technique in the field to enhance performance of nanopipettes, and further functionalised with a metal bis thiolate complex, to aid in chemical analysis. The sample characterisation involved scanning electron microscopy (SEM), low-energy dispersive x-ray spectroscopy (EDX), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Auger electron spectroscopy (AES). Using focused ion beam (FIB) milling under gentle conditions, the inner surface of quartz nanopipettes was exposed whilst preserving the integrity of the overall structure (see figure). Owing to the challenging analysis conditions, modification and analysis of flat quartz substrates has been performed in parallel for optimisation purposes. The results demonstrate the first steps towards full characterisation of nanopipettes at the nanoscale, notably with access to the inner channel. The methods used here can be applied to gain further understanding of the response of these sensors to complex analytes and allow for the study of different surface functionalisations at the all-important sensing region.
Per- and polyfluoroalkyl substances (PFAS) represent a class of synthetic organofluorine chemicals extensively utilized in the manufacturing of various materials such as firefighting foams, adhesives, and stain- and oil-resistant coatings. In recent years, PFAS have been considered as emerging environmental contaminants, with particular focus on perfluoroalkyl carboxylic acids (PFCAs), the most prevalent type among PFAS. PFCAs are characterized by a fully fluorinated carbon backbone and a charged carboxylic acid headgroup. Notably, they have been designated as Substances of Very High Concern and added to the REACH Candidate List due to their persistence in the environment, non-biodegradability and toxicological effects.
Conventional techniques for the analysis of PFCA, such as GC-MS, HRMS and HPLC-based methods, are laborious, not portable, costly and require skilled personnel. In contrast, fluorescence assays can be designed as easy-to-operate, portable and cost-effective methods with high sensitivity and fast response, especially when analyte binding leads to a specific increase of a probe’s emission. Integration of such probes with a carrier platform and a miniaturized optofluidic device affords a promising alternative for PFCA monitoring.
Here, a novel guanidine BODIPY fluorescent indicator monomer has been synthesized, characterized, and incorporated into a molecularly imprinted polymer (MIP) for the specific detection of perfluorooctanoic acid (PFOA). The MIP layer was formed on tris(bipyridine)ruthenium(II) chloride doped silica core particles for optical internal reference and calibration-free assays. Such system allows selective and reliable detection of PFCA from surface water samples, with minimum interference by competitors, matrix effects and other factors. Integration of the assay into an opto-microfluidic setup resulted in a miniaturized and easy-to-operate detection system allowing for micromolar detection of PFOA in less than 15 minutes from surface water sample.
Graphene and graphene-oxide (GO) are advanced materials which – similar to other graphene-related 2D materials (GR-2M) - are already used for instance in catalysis processes, biomedical applications, in inks and resins, or as composite materials for the aviation industry. The lateral/structural characterization of graphene oxide (GO) flakes is a challenging task, with steps like sample preparation, representative image selection and exact determination of the particle size distribution of well-defined size and shape descriptors being crucial for an accurate analysis. To ensure that safe-by-design principles are met within the various application fields, the commercial material must be thoroughly characterized and specified through well-known and standardized procedures.
GO flakes with different degrees of complexity were selected to assess the requirements for an accurate evaluation of their physico-chemical properties. These samples show inherent features with complex nanoscale characteristics such as porosity and edge roughness; further, the lateral size (quantified via equivalent circular diameter (ECD), minimum Feret and maximum Feret) of isolated and overlapping particles deposited on a substrate span over several orders of magnitude (nano to micron scale). The samples showed different degrees of agglomeration (and possible aggregation) with sizes ranging between submicron to a few tens of micrometers.
One focus is the automated segmentation and evaluation of images obtained by electron microscopy. The GO samples appear translucent with well-defined contrast between single and overlapping flakes both with the secondary electron detector of type InLens as well as with SEM in the transmission mode (STEM) utilizing a dedicated sample holder. To this end it is of utmost importance for the accurate image segmentation to carefully select thresholds both manually and through semi-automatic approaches using well-known threshold algorithms such as “IsoData” and pre-defined segmentation applications such as the ParticleSizer software package.
Further specific challenges in identifying and extracting key features of selected graphene oxide flakes are being discussed and approaches towards accurate and representative characterization are presented.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
This study provides insights into the properties of 316L stainless steel produced by additive manufacturing using fused filament fabrication (FFF). One key finding is particularly noteworthy: in significant contrast to cold-rolled 316L, FFF316L develops a pronounced martensite phase after fabrication. The comprehensive comparative analysis shows that FFF316L not only retains the ferrite volume content, but that this is also significantly influenced by the build-up direction. Despite the sintering process, which typically involves densification of the material, a pore volume fraction of 8.45 % remains, which influences the mechanical properties. Although FFF316L has lower elastic
modulus and tensile strength values compared to cold-rolled 316L, its ductility is still competitive. The study further reveals that deformation-induced martensite forms at the intersections of the deformation twins and ferrite islands form at the grain boundaries during the compression and sintering phases. These findings highlight the challenges associated with FFF316L in specific application fields and signal the need to continue to carefully evaluate and improve the development of manufacturing technologies.
Metallbasierte additive Fertigungsverfahren werden zunehmend industriell zur Anfertigung von komplex geformten Komponenten eingesetzt. In diesem Zusammenhang ist das Laser-Pulverbettschweißen von Metall (PBF-LB/M) ist ein weitläufig genutztes Verfahren. Im PBF-LB/M-Prozess werden lagenweise aufgetragene Metallpulverschichten selektiv mittels eines Lasers aufgeschmolzen. Die Entstehung von internen Fehlstellen (bspw. Porosität, Lunker oder Risse) während des Fertigungsvorgangs stellt ein ernstzunehmendes Risiko für die Bauteilsicherheit und somit für die weitere industrielle Etablierung des Verfahrens dar. Die Entstehung von Fehlstellen hängt eng mit lokalen Änderungen der thermischen Historie des Bauteils zusammen. Mit Hilfe von thermografischen Kameras zur Prozessüberwachung kann die thermische Historie bereits während der Fertigung erfasst werden. Damit eröffnet sich die Möglichkeit, die Entstehung von Fehlstellen anhand der thermografischen Daten vorherzusagen und somit potenziell Kosten für eine nachgelagerte Qualitätssicherung einzusparen.
In diesem Beitrag soll die Modellierung der Fehlstellenvorhersage anhand thermografischer Prozessdaten diskutiert werden. Hierbei liegt ein Schwerpunkt auf der Fragestellung, mit welcher Genauigkeit unterschiedliche Formen von Fehlstellen, im speziellen Anbindungsfehler und Keyhole-Porosität, auf lokaler Bauteilebene vorhergesagt werden können. Weiterhin werden verschiedenen Modelltypen aus dem Bereich des Maschinellen Lernens auf ihre Eignung für die Fehlstellenvorhersage verglichen. Ein weiterer zentraler Aspekt in diesem Zusammenhang ist die Untersuchung der Eingangsdaten des Modells auf ihre Relevanz für das Vorhersageergebnis.
Als Datengrundlage für die durchgeführten Untersuchungen dienen die Fertigungsprozesse von zwei identischen Haynes-282-Bauteilen (Nickel-Basislegierung), welche mit Hilfe einer im kurzwelligen Infrarotbereich arbeitenden Thermografiekamera überwacht wurden. Das Bauteildesign umfasste lokale Bereiche, in denen mit Hilfe einer Parametervariation die Entstehung von Fehlstellen forciert wurde. Um die Position und Größe der entstandenen Defekte zu quantifizieren, wurden beide Bauteile nach erfolgter Fertigung mittels Computertomografie (CT) geprüft. Im Rahmen der Datenvorbereitung für die Modellierung erfolgte eine Reduzierung der erhobenen Thermogramme zu physikalisch-interpretierbaren Merkmalen (bspw. Schmelzbadfläche oder Zeit-über-Schwellwert). Weiterhin erfolgte eine Registrierung der thermografischen Daten mit den Fehlstellen-Referenzdaten der CT, um eine exakte örtliche Überlagerung von thermischer Information und lokalem Fehlstellenbild zu erzielen. Zur Ermöglichung einer lokalen Fehlstellenvorhersage wurden die thermografischen Daten schichtweise in kleinteiligen Volumina angeordnet, welche als Eingangsgröße für die genutzten ML-Algorithmen dienten.
Die Ergebnisse der Untersuchungen zeigen, dass sich die Porosität auf Bauteilschichtebene mit einer hohen Genauigkeit vorhersagen lässt. Eine Vorhersage der Porosität auf lokaler Bauteilebene erweist sich noch als herausfordernd. Die erprobten ML-Algorithmen zeigen vergleichbare Ergebnisse, obwohl ihnen unterschiedliche Modellierungsannahmen zugrunde liegen und sie variierende Komplexität aufweisen. Mit Hilfe der erzielten Erkenntnisse eröffnet sich die Möglichkeit, Rückschlüsse auf die gewählte Prozessüberwachungshardware und Datenvorverarbeitung zu ziehen und somit langfristig die Leistungsfähigkeit von Modellen zur Fehlstellenvorhersage zu verbessern.
Die metallische additive Fertigung hat in den letzten Jahren in der industriellen Fertigung zunehmend an Bedeutung gewonnen. Hierbei dominiert das Laser-Pulverbettschweißen von Metallen (PBF/LB-M) die Fertigung von kleinformatigen Bauteilen mit hoher Oberflächengüte. Die anspruchsvolle und kostspielige Qualitätssicherung stellt aber weiterhin ein Hindernis für eine breitere und kostengünstigere Anwendung der additiven Fertigung dar. Dies resultiert teilweise aus fehlenden zuverlässigen In-situ-Monitoringsystemen. Belastbarere Prozessüberwachungsdaten würden eine oft erforderliche teure nachgelagerte Prüfung mittels Computertomografie entbehrlich machen. Die Aufzeichnung der thermischen Signaturen des Aufbauprozess mittels Thermografie-Kameras zeigen hier vielversprechende Ergebnisse. Eine Korrelation zu auftretender Porosität, Delaminationen und Deformationen scheinen möglich. Die geringe räumliche Auflösung und die hohen Anschaffungskosten für thermografische Kamerasysteme stehen jedoch einer größeren industriellen Nutzung im Wege.
Ein bereits industriell angewendeter Ansatz zur in-Situ Überwachung des PBF-LB/M Prozesses ist die Optische Tomografie (OT). Hierbei wird die emittierte Prozessstrahlung jeder Bauteilschicht mittels einer hochauflösenden günstigen Kamera für den sichtbaren Wellenlängenbereich in einer Langzeitbelichtung dokumentiert. Die zeitliche Information der emittierten Strahlung geht hierbei verloren. Der gesamte Bauprozess kann jedoch in einem vergleichsweise kleinen Datensatz dokumentiert werden (ein Bild pro Schicht). Eine direkte Korrelation zu auftretenden Defekten gestaltet sich aufgrund der reduzierten thermischen Informationsdichte jedoch schwierig.
In diesem Beitrag soll deshalb das Prinzip der Multispektralen Optischen Tomografie (MOT) vorgestellt und erste Messergebnisse an der Forschungsanlage SAMMIE diskutiert werden. Bei der MOT handelt es sich um eine Übertragung des Prinzips der Quotientenpyrometrie auf das etablierte Verfahren der Optischen Tomografie. Die auftretende Prozessstrahlung wird in mehreren Wellenlängenbereichen ortsaufgelöst über die gesamte Bauplattform erfasst und zeitlich in einer Langzeitbelichtung integriert. Hierbei kommen günstige Kamerasysteme für den sichtbaren Wellenlängenbereich zum Einsatz.
Das erfasste Signal I jedes Bildpixels für jeden separat erfassten Wellenlängenbereich kann als Maß für das zeitliche Integral der spezifischen Ausstrahlung M des Schmelzbades in diesem Wellenlängenbereich gesehen werden. Nach dem Stefan-Boltzmann-Gesetz hängt die abgestrahlte thermische Leistung P eines idealen Schwarzen Körpers in der vierten Potenz von dessen absoluten Temperatur T ab. Wird nur, wie z.B. bei der klassischen OT angewendet, der nahinfrarote Wellenlängenbereich betrachtet, lässt sich mit dem Planck’schen Strahlungsgesetz sogar eine Proportionalität zur siebten Potenz der Temperatur zeigen. Deshalb liegt ein starker Einfluss der maximal auftretenden Oberflächentemperatur Tmax auf das erfasste Messsignal vor.
Das erfasste Signal I wird aber auch durch die spektrale Transmission τ der verwendeten optischen Komponenten des Kamera-Setups, z.B. Filter und Objektive, durch die spektrale Sensitivität S der verwendeten Kamera-Sensoren und den nur sehr schwer zu bestimmenden Emissionsgrad ε der emittierenden (flüssigen) Oberfläche beeinflusst.
In einer ersten Näherung wird das Schmelzbad hier als Graukörper, also ein Körper mit wellenlängenunabhängigem Emissionsgrad ε, betrachtet. Basierend auf dieser Annahme und vermessenen optischen Eigenschaften des verwendeten Systems ist es möglich, eine erste Schätzung der maximalen Oberflächentemperatur Tmax vorzunehmen, selbst ohne genaue Kenntnis des tatsächlichen Emissionsgrades ε. Dies wird durch die Anwendung des Planck‘schen Strahlungsgesetzes und die Quotienten Bildung aus den einzelnen erfassten Signalen I ermöglicht.
Auch bei diesem Verfahren geht die zeitliche Information einer Schicht, also das Aufwärm- und Abkühlverhalten des Schmelzbades, verloren. Zudem sind die Messergebnisse in Hinblick auf tatsächlich gemessene „maximal auftretende Oberflächentemperatur“ mit gebotener Zurückhaltung zu interpretieren. Trotzdem konnten erste Ergebnisse bereits zeigen, dass die MOT-Daten auch in Bereichen mit Doppelbelichtungen (das teilweise notwendige mehrfache Scannen eines Bereiches mittels des Fertigungslasers) im Gegensatz zur klassischen OT erwartbare Maximaltemperaturen liefern. Abbildung 1 zeigt das erfasste Messergebnis für drei aufeinanderfolgende Schichten eines Bauteils einmal mit MOT (links) und einmal mit einfacher OT (rechts). Deutlich zu erkennen ist das durch die doppelte Belichtung hohe Signal bei der OT. Die Daten der MOT zeigen hier keine erhöhten Werte.
Um die ermittelten Temperaturwerte mittels MOT besser einordnen zu können, sind u.a. vergleichende Messungen an Referenzmaterialien geplant. Um die Auswertung der gemessenen Daten zu verbessern, wird zudem der Zeitverlauf des Abkühlens und Aufheizens des Schmelzbades sowie die Einflüsse von Prozessbeiprodukten wie Schmauch und Spritzer näher untersucht. Auch werden Messungen zum Emissionsgrad ε an additiv gefertigten Proben und Metallschmelzen vorgenommen.
Im additiven Fertigungsprozess Laser-Pulverbettschweißen wird Metallpulver lagenweise mittels eines Lasers aufgeschmolzen, um Bauteile zu generieren. Hierbei werden die Eigenschaften der Bauteile zu einem großen Teil durch die im Verlauf des Prozesses vorliegenden Temperaturen bestimmt. Dies beinhaltet unter anderem Materialeigenschaften wie Mikrostruktur, Härte, thermische und elektrische Leitfähigkeiten sowie die Ausbildung von Defekten wie z.B. Anbindungsfehler, Keyhole-Porosität (Gaseinschlüsse) oder auch die Ausbildung von Rissen. Zur Überwachung bzw. Vorhersage dieser Eigenschaften sowie zum Abgleich von Simulationen ist eine orts- und zeitaufgelöste Messung der Temperaturverteilung im Prozess daher von herausragender Bedeutung. In der Industrie kommen optische Verfahren, die auf der Messung der thermischen Strahlung basieren, regelmäßig zum Einsatz. Allerdings dienen diese bislang nur der statistischen Auswertung und der Identifikation von Abweichungen vom Normalprozess. Der quantitativen Auswertung zur Temperaturbestimmung stehen aktuell noch eine Vielzahl von Herausforderungen entgegen. Einerseits stellt der Prozess an sich hohe Anforderungen an die Datenerfassung und -auswertung: der Emissionsgrad verändert sich dynamisch im Prozess und lokale Schmauchbildung sorgt für potenzielle Absorption oder Streuung der thermischen Strahlung oder auch des Fertigungslasers. Weiterhin stellt der hochdynamische Prozess hohe Anforderungen an Orts- und Zeitauflösung der eingesetzten Sensorik (z.B. Kameratechnik). Andererseits erschweren an üblichen kommerziell erhältlichen Fertigungsanlagen praktische Hindernisse wie eine eingeschränkte optische Zugänglichkeit und der fehlende Zugriff auf die Anlagensteuerung sowie fehlende Möglichkeiten der Synchronisation der Messtechnik mit dem Prozess eine eingehende Untersuchung dieser Effekte.
Um letztere Hindernisse zu umgehen, wurde an der BAM die Forschungsanlage SAMMIE (sensor-based additive manufacturing machine) entwickelt. Einerseits bietet das System alle Möglichkeiten, die auch übliche kommerzielle Systeme bieten. Dies beinhaltet die Fertigung ganzer Bauteile (maximale Größe ca. 65mm x 45 mm x 30 mm) und den Einsatz einer Inertgasatmosphäre inkl. gefiltertem Schutzgasstrom. Andererseits bietet es aber auch einen besonders kompakten Bauraum, um die Sensorik möglichst nah an den Prozess führen zu können, sechs optische Fenster zur Prozessbeobachtung aus unterschiedlichen Winkeln und die Möglichkeit der Prozessbeobachtung koaxial zum Fertigungslaser. Des Weiteren besteht eine einfache Austauschbarkeit aller Fenster, Spiegel und Strahlteiler, um den gesamten optischen Pfad der aktuellen Messaufgabe flexibel anzupassen. Die komplette Anlagensteuerung ist eine Eigenentwicklung und bietet daher auch völlige Anpassbarkeit. Eine synchrone und frei konfigurierbare Triggerung diverser Sensoriken und synchrone Datenerfassung bieten maximale Kontrolle über die Sensorsteuerung.
Dieser Beitrag gibt einen Überblick über die Fertigungsanlage SAMMIE. Wissenschaftliche Ergebnisse sowie laufende Arbeiten an der Anlage werden in weiteren Beiträgen vorgestellt.
Lithium-ion batteries are a key technology for tackling challenges in energy and climate crisis, but up to 30 % are discarded right after production. Quality is closely related to the homogeneity of the used materials and coatings. Fluorine compounds, both in the polymer and from degradation of the electrolyte, are of special interest for the formation and aging of LIBs. Glow-discharge optical emission spectroscopy (GD-OES) emerged as a fast and convenient method for depth-profiling of battery materials. However, fluorine remains a spectroscopic challenge due to a high excitation energy and only few strong emission lines in the UV/Vis spectral range.
We investigated the partial substitution of argon with neon in the plasma gas. The main emission line at 685.603 nm was monitored by both photo multiplier tube (PMT) with Czerny-Turner monochromator at 20 µm slit-size, and charge-coupled device (CCD) with 1200 lines/mm grating. For calibration, we used a set of hot-pressed copper cylinders with varying calcium fluoride amount fraction, ranging from 1.6 % to 4.4 %. Plasma gas mixtures with a mole fraction of 5 %, 10 % and 20 % neon in argon were used. Sensitivity in comparison to pure argon was increased by factor 4, 7 and 14, respectively. In general, PMT detection was more sensitive than CCD. As expected, sputter rates decreased with higher neon content in the plasma gas. Depth-profiling of the cathodes was performed in pulsed mode at constant voltage and pressure, which resulted in stable plasma conditions. We achieve matrix-independent quantitative information on fluorine distribution by correction based on sputter rates.
This advancement in GD-OES provides a more accurate analytical approach for evaluating the homogeneity of lithium-ion battery materials, potentially leading to more sustainable and cost-effective manufacturing processes.