TY - CONF A1 - Radtke, Martin T1 - Machine learning: examples from BAMline N2 - Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from BAMline will be presented. After a short introduction to synchrotron radiation, artificial intelligence algorithms for the quantification of X-ray fluorescence measurement are discussed. In the second example, information retrieval by natural language processing is discussed. T2 - Analytical Academy CY - Online meeting DA - 02.06.2020 KW - Machine learning KW - BAMline KW - XRF KW - Synchrotron PY - 2020 AN - OPUS4-51898 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - Illuminating the Past, Shaping the Future: Advanced Technologies in Gold Analysis and Beamline Control N2 - The presentation explores how synchrotron radiation is used for non-destructive and highly precise analysis of gold artifacts. It explains how synchrotron radiation provides extremely bright and tunable X-rays that can examine very small areas with great accuracy. These features make it ideal for studying cultural heritage objects without damaging them. The presentation highlights case studies such as the Nebra Sky Disk, the Hiddensee gold jewelry, Phoenician ivory, and Egyptian gold from Abydos. These examples show how synchrotron-based techniques reveal details about the origin, composition, and manufacturing of ancient gold. A major focus is the Bernstorf gold discovery in Bavaria. Over several years, different analytical methods, including synchrotron X-ray fluorescence, were applied to test whether the gold was genuinely ancient. The studies found nearly pure gold, sparking debate about whether such purity could be achieved in the Bronze Age. In the final part, the presentation connects this research with modern developments in automation and artificial intelligence. It describes how beamline experiments can be controlled through the EPICS system, Python scripting, and AI tools such as ChatGPT and Whisper, enabling intelligent and voice-assisted operation. T2 - Seminar Strahlenphysikalische Anwendungen in Technik und Medizin CY - Wien, Austria DA - 29.01.2025 KW - Synchrotron KW - BAMline KW - AI KW - Gold KW - XRF PY - 2025 AN - OPUS4-64477 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - X-Ray fluorescence with synchrotron radiation basics and applications N2 - In this talk, the features of X-ray fluorescence analysis with synchrotron radiation will be presented. First, the basics of the origin of synchrotron radiation and X-ray fluorescence analysis and the experimental setup will be discussed. Then, examples of trace element detection, micrometer resolution, and application of the X-ray color camera will be shown. T2 - HZB Photon school 2020 CY - Berlin, Germany DA - 09.03.2020 KW - Synchrotron KW - BAMline KW - XRF KW - Machine learning PY - 2020 AN - OPUS4-51894 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - From Egypt to Hiddensee – Analysis of Gold with Synchrotron Radiation V N2 - Gold is one of the seven metals already known in antiquity and was used from time immemorial as a medium of exchange and for the production of jewelry because of its luster and rarity. In addition, it is easy to work and largely resistant to chemical influences. Investigations of gold using synchrotron radiation excited X-ray fluorescence analysis are non-destructive and provide information about the chemical elements present in the sample under investigation. The investigations presented here at BAMline focus on questions such as the origin, manufacturing process, and association of gold findings. The different questions are explained by a number of examples ranging from the Viking treasure from Hiddensee to the Nebra Sky Disk and finds from Egypt. The find from Bernstorf is discussed in detail. A Bayesian treatment of the authenticity is shown. T2 - Ringvorlesung Einführung in die Archäometrie CY - Berlin, Germany DA - 01.11.2024 KW - Gold KW - Synchrotron KW - XRF KW - BAMline KW - Bayes PY - 2024 AN - OPUS4-61699 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - Von Ägypten bis Hiddensee Analyse von Gold mit Synchrotronstrahlung III N2 - Gold ist eines der sieben schon im Altertum bekannten Metalle und wurde wg. seines Glanzes und seiner Seltenheit von alters her als Tauschmittel und zur Herstellung von Schmuck benutzt. Außerdem ist es einfach bearbeitbar und weitestgehend gegen chemische Einflüsse resistent. Die Untersuchungen von Gold mit synchrotronstrahlungsangeregter Röntgenfluoreszenzanalyse sind zerstörungsfrei und geben Auskunft über die in der untersuchten Probe vorhandenen chemischen Elemente. Bei den hier vorgestellten Untersuchungen an der BAMline stehen Fragestellungen wie Herkunft, Herstellungsverfahren und Zusammengehörigkeit von Goldfunden im Vordergrund. Die verschiedenen Fragestellungen werden an einer Reihe von Beispielen erläutert die vom Wikingerschatz aus Hiddensee über die Himmelsscheibe von Nebra bis hin zu Funden aus Ägypten langen. Der Fund von Bernstorf wird ausführlich diskutiert. T2 - Vorlesung FU Berlin Einführung in die Archäometrie CY - Berlin, Germany DA - 06.11.2020 KW - Synchrotron KW - BAMline KW - XRF KW - Gold KW - Archäometrie PY - 2020 AN - OPUS4-51893 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - Decoding the Elemental Fingerprints of Ancient Gold: A Synchrotron-based Approach N2 - This contribution focuses on the application of synchrotron radiation X-ray fluorescence (SR XRF) for the analysis of ancient gold objects at the BAMline, showcasing several noteworthy examples. One prominent artifact is the Sky Disc of Nebra, which presented a relatively straightforward question to be addressed: Do the gold inlays belong together, and can we glean insights about their origin? In contrast, the analysis of the Bernstorf gold, an alleged Bronze Age treasure composed of exceptionally pure gold, posed a more intricate challenge. The debate surrounding its authenticity prompted an in-depth investigation utilizing SR XRF with different experimental conditions. This approach, involving the analysis of trace elements, played a pivotal role in elucidating the nature and age of the gold, offering valuable insights into its production Platinum emerges as a crucial trace element for gold analysis, given its typically low concentration in gold artifacts, often in the range of a few parts per million (ppm). Accurately measuring Platinum in the presence of overlapping emission lines from gold is arduous. To overcome this challenge, BAMline developed a wavelength dispersive set-up known as D2XRF, employing a pixelated energy-dispersive X-ray detector (pnCCD). This innovative approach enables the resolution of overlapping emission lines, leading to a remarkable detection limit of 1 ppm for Platinum in gold samples. Furthermore, the application of the pnCCD for imaging element distributions on a Phoenician ivory artifact will be showcased. This technique allows for the visualization and mapping of various elements, which opens the possibility to reconstruct the original appearance. The comprehensive analysis of ancient gold artifacts at BAMline has provided valuable insights into the craftsmanship, trade, and technological advancements of ancient civilizations. By unraveling the complex stories these artifacts carry, our studies contributed significantly to the fields of archaeology, history, and materials science. It underscores the importance of interdisciplinary approaches in piecing together the puzzle of human history, revealing the interconnectedness of cultures through the lens of non-destructive analysis. T2 - Denver X-ray Conference 2024 CY - Denver, CO, USA DA - 04.08.2024 KW - Gold KW - Synchrotron KW - XRF KW - BAMline PY - 2024 AN - OPUS4-61701 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - ChatGPT and EPICS: LLM-Enhanced Control Systems for Synchrotron Beamlines N2 - The BAMline at BESSY II represents a hard X-ray spectroscopy facility enabling non-destructive analysis across diverse research areas like materials science, chemistry, biology, and cultural heritage studies. As a multipurpose beamline serving users from various disciplines, it underscores the necessity of adaptable and efficient control systems to maximize beamline utilization and scientific output. In this contribution, we detail the innovative integration of ChatGPT , OpenAI’s state-of-the-art Large Language Model (LLM), with the Experimental Physics and Industrial Control System (EPICS) which underpins the operational framework of the BAMline. This integration leverages the advanced natural language processing (NLP) capabilities of ChatGPT, presenting a revolutionary approach to beamline control that markedly simplifies user interaction. Through this, we facilitate a user-friendly pathway to executing complex experimental setups, eliminating the barrier imposed by conventional scripting languages and the often-challenging graphical user interfaces. This innovation promises to significantly streamline experimental workflows, thereby enhancing the efficiency of scientific research conducted at the beamline. Further enhancing this user-centric approach, we introduce an advanced graphical user interface (GUI) application. This novel application seamlessly melds the LLM’s NLP capabilities with EPICS, thereby enabling researchers to articulate experimental requirements through simple textual or voice commands. This interface interprets these commands to manipulate various beamline components, including but not limited to the Double Crystal Monochromator (DCM), Double Multilayer Monochromator (DMM), as well as various filters and slits. By parsing user input, extracting pertinent parameters, and generating a structured JSON object that reflects the desired device positions and experimental settings, the GUI application bridges the gap between complex control commands and intuitive user interactions. This advancement not only lowers the entry threshold for new users but also streamlines the operational workflow for experienced researchers. Looking ahead, we aim to extend the system to cover the entire experimental cycle, from setup to data analysis. Using LLMs, one could translate plain-language experiment descriptions into precise operational commands, revolutionizing the research process and making advanced scientific exploration more accessible to a wider community. T2 - European X-ray Spectrometry Conference CY - Athens, Greece DA - 24.06.2024 KW - EPICS KW - ChatGPT KW - BAMline KW - Synchrotron PY - 2024 AN - OPUS4-61702 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - ChatGPT and EPICS: LLM-Enhanced Control Systems for Synchrotron Beamlines N2 - The BAMlineat BESSY II represents a hard X-ray spectroscopy facility enabling non-destructive analysis across diverse research areas like materials science, chemistry, biology, and cultural heritage studies. As a multipurpose beamline serving users from various disciplines, it underscores the necessity of adaptable and efficient control systems to maximize beamline utilization and scientific output. In this contribution, we detail the innovative integration of ChatGPT, OpenAI’s state-of-the-art Large Language Model (LLM), with the Experimental Physics and Industrial Control System (EPICS) which underpins the operational framework of the BAMline. This integration leverages the advanced natural language processing (NLP) capabilities of ChatGPT, presenting a revolutionary approach to beamline control that markedly simplifies user interaction. Through this, we facilitate a user-friendly pathway to executing complex experimental setups, eliminating the barrier imposed by conventional scripting languages and the often-challenging graphical user interfaces. This innovation promises to significantly streamline experimental workflows, thereby enhancing the efficiency of scientific research conducted at the beamline. Further enhancing this user-centric approach, we introduce an advanced graphical user interface (GUI) application. This novel application seamlessly melds the LLM’s NLP capabilities with EPICS, thereby enabling researchers to articulate experimental requirements through simple textual or voice commands. This interface interprets these commands to manipulate various beamline components, including but not limited to the Double Crystal Monochromator (DCM), Double Multilayer Monochromator (DMM), as well as various filters and slits. By parsing user input, extracting pertinent parameters, and generating a structured JSON object that reflects the desired device positions and experimental settings, the GUI application bridges the gap between complex control commands and intuitive user interactions. This advancement not only lowers the entry threshold for new users but also streamlines the operational workflow for experienced researchers. Looking ahead, we aim to extend the system to cover the entire experimental cycle, from setup to data analysis. Using LLMs, one could translate plain-language experiment descriptions into precise operational commands, revolutionizing the research process and making advanced scientific exploration more accessible to a wider community. T2 - International Conference on Synchrotron Radiation Instrumentation (SRI) CY - Hamburg, Germany DA - 26.08.2024 KW - Chatgpt KW - EPICS KW - BAMline KW - Synchrotron PY - 2024 AN - OPUS4-61700 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - Artificial intelligence for spectroscopy examples from BAMline N2 - Various applications for artificial intelligence in the context of spectroscopy will be presented. in particular, examples from bamline will be featured. After a short introduction to synchrotron radiation, artificial intelligence algorithms for the quantification of X-ray fluorescence measurement are discussed. In the second example, information retrieval by natural language processing is reviewed. As a last example the reconstruction of measurements with the X-ray color camera and coded apertures is presented. T2 - Seminar Strahlenphysikalische Anwendungen in Technik und Medizin CY - ATi Wien, Austria DA - 22.01.2020 KW - Machine learning KW - Natural language processing KW - Neural networks KW - Synchrotron KW - BAMline PY - 2020 AN - OPUS4-51891 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Radtke, Martin T1 - Getting more efficient – The use of Bayesian optimization and Gaussian processes at the BAMline N2 - The BAMline, a beamline for material science research at BESSY II, has been operated by the Bundesanstalt für Materialforschung und -prüfung for over two decades. In the last few years, Bayesian optimization (BO) with Gaussian processes (GP) has been introduced as a transformative method in this setting. This contribution highlights the integration and impact of BO and GP in refining BAMline operations. We will explore the impact of integrating Bayesian methods, especially when combined with Gaussian processes, on the operational efficiency of the BAMline. Our discussion commences with an overview of the fundamental concepts of active learning and optimization. This is followed by an in-depth analysis of specific case studies, drawing on our direct experience with these innovative methods. For this our focus is on three key applications: Alignment of Optical Elements (DCM and DMM): The implementation of Bayesian optimization using Gaussian processes has revolutionized the alignment process for the Double Crystal Monochromator (DCM) and the Double Multilayer Monochromator (DMM). This approach greatly reduced manual effort and enhanced the efficiency and effectiveness of the alignment procedure. Optimal Spot Selection for Spatial Mapping in XRF Studies: In X-ray fluorescence (XRF) experiments, determining the most informative sampling spots is crucial. The introduction of BO, informed by GP, has significantly improved the selection process, especially in large or heterogeneous samples. This methodology ensures maximum information gain, optimizing the balance between comprehensive mapping and resource management. Selection of Optimal Energies for XANES Measurements in GEXANES Geometry: In the specific context of X-ray Absorption Near Edge Structure (XANES) studies using Grazing Exit (GEXANES) geometry, the Bayesian approach with Gaussian processes is now utilized to identify the most effective energy settings. This results in detailed spectral data acquired in a much shorter time. We also address challenges and limitations encountered during implementation. Additionally, the versatility of this approach in addressing a range of different research questions will be demonstrated. T2 - Machine Learning Conference for X-Ray and Neutron-Based Experiments CY - Garching bei München, Germany DA - 08.04.2024 KW - BAMline KW - Synchrotron KW - XRF KW - Bayes PY - 2024 AN - OPUS4-61703 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -