TY - GEN A1 - Döring, Sarah T1 - Vergleichende Darstellung SARS-CoV-2-spezifischer Nanobodys aus unterschiedlichen Wirtsorganismen N2 - Aufgrund der anhaltenden COVID-19-Pandemie werden neutralisierende Therapeutika benötigt. Eine Möglichkeit zur Behandlung stellt die Verwendung monoklonaler Anti-SARS-CoV-2-Immun-globuline dar. Ihre Produktion in Säugetierzellen ist jedoch schwer skalierbar, um den weltweiten Bedarf zu decken. VHH-Antikörper, auch Nanobodys genannt, bieten hierfür eine Alternative, da sie eine hohe Temperaturstabilität aufweisen und eine kostengünstige Produktion in prokaryotischen Wirtsorganismen ermöglichen. KW - E. coli KW - Corona KW - Virus KW - Spike-Protein KW - Nanobody KW - Antikörper KW - Expression KW - Fingerprint KW - Vhh KW - RBD KW - COVID-19 KW - SARS-CoV-2 KW - ELISA KW - MST KW - Halomonas elongata KW - Periplasma KW - SDS-PAGE KW - ACE2-Rezeptor PY - 2021 SP - 1 EP - 111 PB - Technische Universität Berlin CY - Berlin AN - OPUS4-54624 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Waske, Anja T1 - A unique authenticator for additively manufactured parts derived from 3D microstructural information N2 - Additive manufacturing (AM) is rapidly emerging from rapid prototyping to industrial production [1]. Thus, providing AM parts with a tagging feature that allows identification, like a fingerprint, can be crucial for logistics, certification, and anti-counterfeiting purposes since nearly any geometry can be produced by AM with stolen data or reverse engineering of an original product. However, the mechanical and functional properties of the replicated part may not be identical to the original ones and pose a safety risk [2]. Several methods are already available, which range from encasing a detector to leveraging the stochastic defects of AM parts for the identification, authentication, and traceability of AM components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface of the internal cavity of hollow components. Local manipulation of components may alter the properties. The external tagging features can be altered or even removed by post-processing treatments. Integrating electronic systems [4] in AM parts can be used to identify and authenticate components with complex or customized geometries. However, metal-based AM, especially in powder bed fusion (PBF-LB/M) techniques, has a strong shielding effect that interferes with the communication between the reader and the transponder. Our work suggests a methodology for the identification, authentication, and traceability of AM components using microstructural features in AM components. We will show a workflow that includes analysing 3D micro computed tomography data and selecting a set number of voids that fulfil the identification criteria. We will show the results this workflow produces for a series of 20 Al-based cuboid samples with identical processing parameters and discuss their prospects and limitations. The workflow can help to establish a non-tamperable connection between an additively manufactured part and its digital data and hence link the physical and the digital world. T2 - MSE Konferenz CY - Darmstadt, Germany DA - 24.09.2024 KW - Additive Manufacturing KW - Fingerprint KW - Computed tomography PY - 2024 AN - OPUS4-62288 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gupta, Kanhaiya T1 - Microstructural fingerprinting of additively manufactured components prepared by PBF LB/M N2 - Additive manufacturing (AM) is rapidly emerging from rapid prototyping to industrial production [1]. Thus, providing AM parts with a tagging feature that allows identification, like a fingerprint, can be crucial for logistics, certification, and anti-counterfeiting purposes since nearly any geometry can be produced by AM with stolen data or reverse engineering of an original product. However, the mechanical and functional properties of the replicated part may not be identical to the original ones and pose a safety risk [2]. Several methods are already available, which range from encasing a detector to leveraging the stochastic defects of AM parts for the identification, authentication, and traceability of AM components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface of the internal cavity of hollow components. Local manipulation of components may alter the properties. The external tagging features can be altered or even removed by post-processing treatments. Integrating electronic systems [4] in AM parts can be used to identify and authenticate components with complex or customized geometries. However, metal-based AM, especially in powder bed fusion (PBF-LB/M) techniques, has a strong shielding effect that interferes with the communication between the reader and the transponder. Figure 1: Selection of the few most prominent pores sorted according to decreasing volume that are suitable for tagging and authentication. Our work aims to provide a new methodology for the identification, authentication, and traceability of AM components using microstructural feathers in AM components without altering their properties. Further, we set various benchmark points that can be used in generating the fingerprints for both identification and authentication. This can help digitalize traceability information and tagging features via the link between the physical and cyber worlds through a deeper understanding of the printed object-tag-virtual twin integration. T2 - MSE Konferennz CY - Darmstadt, Germany DA - 24.09.2024 KW - Fingerprint KW - Additive Manufacturing KW - Computed tomography PY - 2024 AN - OPUS4-62286 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Waske, Anja T1 - A unique authenticator for additively manufactured parts derived from their microstructure N2 - The international research community is currently devoting extensive resources to the development of digital material data spaces and the associated digital twins and product passports of materials and components. A common weak link in these projects to date has been the connection between physical components / samples and their digital data and documents. This is where the concept of the unique identification comes in. Components produced using additive manufacturing can be marked for unique identification and secure authentication [1,2]. Serial numbers and machine-readable codes can be used to identify the component, and link digital product-related data (i.e., a digital product passport) to the actual components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface or the internal cavity of hollow components. However, local manipulation of components may alter the properties, and external tagging features can be altered or even removed by post-processing treatments. This work provides a new methodology for identification, authentication, and traceability of additively manufactured (AM) components using microstructural features that are unique to each part. X-ray computed tomography (XCT) was employed to image the microstructural features of a batch of AlSi10Mg parts. Based on size and geometry, the most prominent features were selected to create a unique digital authenticator. We implemented a framework in Python using open-access modules that can successfully create a digital object authenticator using the segmented microstructure information from XCT. We show that this method allows to authenticate individual parts from the build job based on its microstructural fingerprint. This is our contribution to enhancing the security and product protection of additively manufactured components. T2 - FEMS EUROMAT CY - Granada, Spain DA - 15.09.2025 KW - Authentication KW - Fingerprint KW - Non-destructive testing PY - 2025 AN - OPUS4-65202 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Waske, Anja T1 - A unique authenticator for additively manufactured parts derived from their microstructure N2 - Components produced using additive manufacturing can be marked for unique identification and secure authentication [1,2]. Serial numbers and machine-readable codes can be used to identify the component, and link digital product-related data (i.e., a digital product passport) to the actual components. The most prevailing solution consists of local process manipulation, such as printing a quick response (QR) code [3] or a set of blind holes on the surface of the internal cavity of hollow components. However, local manipulation of components may alter the properties, and external tagging features can be altered or even removed by post-processing treatments. This work therefore aims to provide a new methodology for identification, authentication, and traceability of additively manufactured (AM) components using microstructural features that are unique to each part. X-ray computed tomography (XCT) was employed to image the microstructural features of AlSi10Mg parts. Based on size and geometry, the most prominent features were selected to create a unique digital authenticator. We implemented a framework in Python using open-access modules that can successfully create a digital object authenticator using the segmented microstructure information from XCT. The authenticator is stored as a QR code, along with the 3D information of the selected features. T2 - MRS Spring Meeting Seattle CY - Seattle, WA, USA DA - 07.04.2025 KW - Additive Manufacturing KW - Fingerprint KW - Non-destructive testing PY - 2025 AN - OPUS4-65199 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Tscheuschner, Georg T1 - Entwicklung einer Methode zur schnellen Identifikation von Antikörpern mittels MALDI-TOF-MS N2 - Im Vergleich zu anderen Proteinen ist die Identifizierung von Antikörpern anhand ihrer Sequenz zum Beispiel mittels "peptide mass fingerprinting" schwierig. Da die Sequenzinformation eines Antikörpers aufgrund der hypersomatischen Mutation während der Affinitätsreifung nicht im Genom eines Organismus gespeichert ist, kann die Aminosäuresequenz nicht auf einfachem Weg der DNA-Sequenzierung gewonnen werden. Das ist nur in seltenen Fällen möglich, wenn dem Endanwender der Zellklon der Antikörper-produzierenden Zelle zugänglich ist. Eine Sequenzierung auf Protein-Ebene ist sehr aufwändig und teuer und wird daher fast nie für die Charakterisierung von analytischen Antikörpern verwendet. Der Mangel an Validierung dieser analytischen Antikörper, die bei Experimenten verwendeten werden, löst aber eine Reihe Probleme aus, die die Wiederholbarkeit dieser Experimente schwierig und in einigen Fällen unmöglich macht. Das sorgt jährlich für verschwendete Forschungsgelder in Milliardenhöhe und hindert den wissenschaftlichen Fortschritt. Ziel der vorliegenden Arbeit war die Entwicklung einer einfachen und schnellen Methode, die es trotzdem ermöglicht, die Identifikation von Antikörpern sicherzustellen. Dazu wurde eine Methode basierend auf dem "peptide mass fingerprinting" gewählt. Das Problem der unbekannten Aminosäuresequenz der Antikörper wurde gelöst, indem lediglich die Peptidmuster der entstehenden Fingerprint-Spektren zur Identifikation herangezogen wurden. MALDI wurde dabei als Ionisationsmethode für die Massenspektrometrie gewählt, da die resultierenden Spektren im Gegensatz zu ESI-MS einfach auszuwerten sind. Auch kann auf eine vorige Trennung der Peptide mittels LC verzichtet werden, was zusätzlich Analysenzeit spart. Für die Proteinspaltung wurde eine simple saure Hydrolyse mittels Ameisensäure gewählt. Im Vergleich zum herkömmlichen Trypsin-Verdau konnten auf zeitraubende Arbeitsschritte wie Denaturierung, Reduktion und Alkylierung der Antikörper verzichtet werden. Die Hydrolyse mittels Ameisensäure wurde bisher nur auf kleine und mittelgroße Proteine angewendet, sodass im ersten Teil dieser Arbeit mehrere Schritte optimiert wurden bevor zufriedenstellende Fingerprint-Spektren von Antikörpern erhalten wurden. KW - Peptide KW - Fingerprint KW - Peptide mass fingerprinting KW - Massenspektrometrie KW - Saure Hydrolyse KW - Festphasenextraktion KW - Protein G KW - Ameisensäure KW - ABID KW - Korrelationsmatrix PY - 2019 SP - 1 EP - 116 PB - Humboldt-Universität zu Berlin CY - Berlin AN - OPUS4-54626 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -