TY - CHAP A1 - Rabin, Ira A1 - Hahn, Oliver ED - Michel, C. ED - Friedrich, M. T1 - Detection of Fakes: The Merits and Limits of Non-Invasive Materials Analysis N2 - This paper addresses the sensitive issue of authenticating unprovenanced manuscripts of high monetary value to certify they are genuine. Over the last decade, the popularity of material studies of manuscripts using non-destructive testing (NDT) has increased enormously. These studies are held in especially high esteem in the case of suspicious writings due to the methodological rigour they are reputed to contribute to debate. We would like to stress that materials analysis alone cannot prove that an object is genuine. Unfortunately, audiences with a humanities background often tend to disregard the technical details and treat any published interpretation of instrumental analysis as an objective finding. Four examples are outlined here to illustrate what questionable contributions the natural sciences can make in describing manuscripts that have actually been forged. KW - Fakes KW - Non-invasive analysis KW - Limitations PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-517202 SN - 978-3-11-071422-7 DO - https://doi.org/10.1515/9783110714333 SN - 2365-9696 VL - 20 SP - 281 EP - 290 PB - Walter de Gruyter GmbH CY - Berlin/Boston AN - OPUS4-51720 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Hahn, Oliver A1 - Golle, U. A1 - Wintermann, Carsten A1 - Laurenza, D. ED - Quenzer, J. B. T1 - Scientific Analysis of Leonardo’s Manuscript with Anatomic Drawings and Notes N2 - In this paper, we discuss the importance of scientifically investigating cultural artefacts in a non-invasive way. Taking as test case Leonardo da Vinci’s Manuscript with anatomic drawings and notes, which is stored in Weimar, we clarify fundamental steps in the chronology of this folio. By means of microscopy, infrared reflectography, UV photography, and X-ray fluorescence analysis, we were able to identify various types of sketching material and several varieties of iron gall ink. For his sketches, Leonardo used two different sketching tools, a lead pencil and a graphite pencil, as well as several types of ink for developing these sketches into drawings. With regard to ink, it is important to observe that there is no difference between the ink Leonardo used for drawing and the ink he used for writing text. Based on the materials analysed, we suggest a chronology for the creation of this unique folio. KW - Archaeometry KW - Non-invasive analysis KW - Drawings KW - Leonardo da Vinci PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543460 SN - 978-3-11-074545-0 DO - https://doi.org/10.1515/9783110753301-011 VL - 25 SP - 213 EP - 228 PB - Walter de Gruyter GmbH CY - Berlin/Boston AN - OPUS4-54346 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Colini, Claudia A1 - Shevchuk, I. A1 - Huskin, K. A. A1 - Rabin, Ira A1 - Hahn, Oliver ED - Quenzer, J. B. T1 - A New Standard Protocol for Identification of Writing Media N2 - Our standard protocol for the characterisation of writing materials within advanced manuscript studies has been successfully used to investigate manuscripts written with a pure ink on a homogeneous writing surface. However, this protocol is inadequate for analysing documents penned in mixed inks. We present here the advantages and limitations of the improved version of the protocol, which now includes imaging further into the infrared region (1100−1700 nm). KW - Archaeometry KW - Manuscripts KW - Non-destructive testing PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543454 SN - 978-3-11-074545-0 DO - https://doi.org/10.1515/9783110753301-009 VL - 25 SP - 161 EP - 182 PB - Walter de Gruyter GmbH CY - Berlin/Boston AN - OPUS4-54345 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Helman-Wasny, Agnieszka ED - Martin, E. ED - Brox, T. ED - Lange, D. T1 - What makes ‘Tibetan paper’ Tibetan? Understanding the materiality of Tibetan paper N2 - Paper, as a writing support, is an integral element of the materiality of Tibetan books together with the technologies of their production. Analysis of the material features of the paper used in Tibetan written artefacts can help us to unravel their provenance, which is often unknown. First, however, we need a relatively clear understanding of the characteristic features of paper produced within particular book cultures and geographical regions at particular periods of time. This chapter offers a starting point by discussing the general characteristics of paper that originated in Tibet. Drawing on macro- and microscopic studies, it highlights the wide variety of paper types that have been used as writing supports in Tibetan written artefacts, before examining in more detail the raw materials, papermaking technologies and processes, and writing surface preparations that might justify the descriptor ‘Tibetan’ and thus grant Tibetan identity to paper. KW - Written artefacts KW - Paper KW - Tibet PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-649288 SN - 978-3-98887-016-2 DO - https://doi.org/10.11588/hasp.1522 SP - 113 EP - 146 PB - Heidelberg Asian Studies Publishing (HASP) CY - Heidelberg AN - OPUS4-64928 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Lange, D. A1 - Hahn, Oliver ED - Martin, E. ED - Brox, T. ED - Lange, D. T1 - Materials and materiality as keys to understanding a map of Mount Kailash N2 - While graphic and linguistic content is central to the identification of maps and can provide insights into the concepts and systems of rules, ideas and beliefs that led to their production, the materials that constitute maps may speak about manufacturing processes, the provenance of raw materials, the practical and technical knowledge of the mapmakers, and the use of the maps. This contribution underscores how the materials employed in Tibetan maps reveal aspects of their context and trajectory. Furthermore, materiality, conceptualized as a convergence of matter and imagination, can yield even more profound insights into artefacts like maps. Through a detailed case study of a map of Mount Kailash in the tangkha format and a specialized material-scientific analysis of the colourants employed in its creation, this contribution explores how a map can ‘talk’ through its materiality. With this case study it will show how Tibetan Studies can benefit from interdisciplinary collaboration. Crossing the field’s traditional boundaries and working with other disciplines, we argue, is absolutely essential for serious research. KW - Archaeometry KW - Non-destructive analysis KW - Cultural heritage PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-648625 SN - 978-3-98887-016-2 DO - https://doi.org/10.11588/hasp.1522 SP - 147 EP - 176 PB - Heidelberg Asian Studies Publishing (HASP) CY - Heidelberg AN - OPUS4-64862 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Ghigo, Tea A1 - Rabin, Ira ED - Buzi, P. T1 - Detecting Early Medieval Coptic literature in Dayr Al-Anba Maqar, Between textual conservation and literary rearrangement: The case of Vat. Copt. 57 N2 - The study of the VAt.Copt. 57 at the Vatican Library. Codicological, palaeographical, textual and archaeometrical considerations. KW - Coptic KW - Archaeometry KW - Ink KW - Manuscripts PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-494004 SN - 978-88-210-1025-5 SP - 77 EP - 83 PB - Biblioteca Apostolica Vaticana AN - OPUS4-49400 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Chand, Keerthana A1 - Fritsch, Tobias A1 - Hejazi, Bardia A1 - Poka, Konstantin A1 - Bruno, Giovanni T1 - Deep Learning Based 3D Volume Correlation for Additive Manufacturing Using High-Resolution Industrial X-Ray Computed Tomography N2 - Quality control in Additive Manufacturing (AM) is vital for industrial applications in areas such as the automotive, medical, and aerospace sectors. Geometric inaccuracies caused by shrinkage and deformations can compromise the life and performance of additively manufactured components. Such deviations can be quantified using Digital Volume Correlation (DVC), which compares the Computer-Aided Design (CAD) model with the X-ray Computed Tomography (XCT) geometry of the components produced. However, accurate registration between the two modalities is challenging due to the absence of a ground truth or reference deformation field. In addition, the extremely large data size of high-resolution XCT volumes makes computation difficult. In this work, we present a deep learning-based approach for estimating voxel-wise deformations between CAD and XCT volumes. Our method uses a dynamic patch-based processing strategy to handle high-resolution volumes. In addition to the Dice score, we introduce a Binary Difference Map (BDM) that quantifies voxel-wise mismatches between binarized CAD and XCT volumes to evaluate the accuracy of the registration. Our approach shows a 9.2% improvement in the Dice score and a 9.9% improvement in the voxel match rate compared to classic DVC methods, while reducing the interaction time from days to minutes. This work sets the foundation for deep learning-based DVC methods to generate compensation meshes that can then be used in closed-loop correlations during the AM production process. Such a system would be of great interest to industry, as it would make the manufacturing process more reliable and efficient, saving time and material. KW - Deep learning PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-646293 DO - https://doi.org/10.3233/FAIA251475 SN - 0922-6389 VL - 413 SP - 5368 EP - 5375 PB - IOS Press AN - OPUS4-64629 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Hejazi, Bardia A1 - Chand, Keerthana A1 - Fritsch, Tobias A1 - Bruno, Giovanni T1 - D-CNN and VQ-VAE Autoencoders for Compression and Denoising of Industrial X-Ray Computed Tomography Images N2 - The ever-growing volume of data in imaging sciences stemming from advancements in imaging technologies, necessitates efficient and reliable storage solutions for such large datasets. This study investigates the compression of industrial X-ray computed tomography (XCT) data using deep learning autoencoders and examines how these compression algorithms affect the quality of the recovered data. Two network architectures with different compression rates were used, a deep convolution neural network (D-CNN) and a vector quantized variational autoencoder (VQ-VAE). The XCT data used was from a sandstone sample with a complex internal pore network as a good test case for the importance of feature preservation. The quality of the decoded images obtained from the two different deep learning architectures with different compression rates were quantified and compared to the original input data. In addition, to improve image decoding quality metrics, we introduced a metric sensitive to edge preservation, which is crucial for three-dimensional data analysis. We showed that different architectures and compression rates are required depending on the specific characteristics needed to be preserved for later analysis. The findings presented here can aid scientists in determining the requirements and strategies needed for appropriate data storage and analysis. T2 - 28th European Conference on Artificial Intelligence – Including 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025) CY - Bologna, Italy DA - 25.10.2025 KW - Data Compression KW - Deep Learning KW - X-ray Computed Tomography PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-644758 UR - https://ebooks.iospress.nl/doi/10.3233/FAIA251480 DO - https://doi.org/10.3233/FAIA251480 SN - 0922-6389 SP - 1 EP - 8 PB - IOS Press AN - OPUS4-64475 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Krebber, Katerina ED - Harun, S.W. ED - Arof, H. T1 - Smart technical textiles based on fiber optic sensors N2 - Smart technical textiles are by definition textiles that can interact with their environment. They can sense and react to environmental conditions and external stimuli from mechanical, thermal, chemical or other sources. Such textiles are multifunctional or even “intelligent” which is fulfilled by a number of sensors incorporated in the textiles. The embedded sensors are sensitive to various parameters such as temperature, strain, chemical, biological and other substances. PY - 2013 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-289397 SN - 978-953-51-1148-1 DO - https://doi.org/10.5772/54244 IS - Section 3 / Chapter 12 SP - 319 EP - 344 PB - InTech AN - OPUS4-28939 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Sproesser, G. A1 - Change, Y.-J. A1 - Pittner, Andreas A1 - Finkbeiner, M. A1 - Rethmeier, Michael ED - Stark, R. ED - Bonvoisin, J. ED - Seliger, G. T1 - Sustainable technologies for thick metal plate welding N2 - Welding is the most important joining technology. In the steel construction industry, e.g. production of windmill sections, welding accounts for a main part of the manufacturing costs and resource consumption. Moreover, social issues attached to welding involve working in dangerous environments. This aspect has unfortunately been neglected so far, in light of a predominant focus on economics combined with a lack of suitable assessment methods. In this chapter, exemplary welding processes are presented that reduce the environmental and social impacts of thick metal plate welding. Social and environmental Life Cycle Assessments for a thick metal plate joint are conducted for the purpose of expressing and analysing the social and environmental impacts of welding. Furthermore, it is shown that state-of-the-art technologies like Gas Metal Arc Welding with modified spray arcs and Laser Arc-Hybrid Welding serve to increase social and environmental performance in contrast to common technologies, and therefore offer great potential for sustainable manufacturing. KW - Human health G. KW - Life cycle assessment (LCA) KW - Arc welding KW - Laser arc-hybrid welding KW - Resource efficiency KW - Social life cycle assessment (SLCA) PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-390025 SN - 978-3-319-48513-3 SN - 978-3-319-48514-0 DO - https://doi.org/10.1007/978-3-319-48514-0 SN - 2194-0541 SN - 2194-055X SP - 71 EP - 84 PB - Springer CY - Cham, Switzerland AN - OPUS4-39002 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -