TY - JOUR A1 - Manzello, Samuel L. A1 - Hofmann-Böllinghaus, Anja T1 - Editorial on special issue on wildland–urban interface (WUI) fires N2 - Research and standardization in the field of wildland fires that spread into urban areas, known as wildland–urban interface (WUI) fires, are of paramount importance globally. Recent WUI fires in Chile, Greece, Japan, and the United States of America states of California and Hawaii, following many other WUI fire disasters, have demonstrated the complex nature of this globally important problem. For these reasons, the editor in chief of Fire and Materials, Stephen Grayson, invited Samuel L. Manzello and Anja Hofmann to develop a special issue on WUI fires. In support of this effort, an open call was posted on the Fire and Materials website, soliciting papers on the following topics: • Pre- and post-fire data to understand fire spread and ignition of materials in WUI communities. • Firebrand generation from materials. • Ignition of both vegetative and human-made fuels from WUI fire exposures of direct flame contact, radiant heat, and firebrands. • Human behavior in WUI fires. • Physical modeling studies of WUI fire behavior and structure ignition. • Structure ignition mitigation strategies. • New material development to harden structures to WUI fire exposures. KW - Editorial KW - Wildfire PY - 2025 DO - https://doi.org/10.1002/fam.3308 SN - 1099-1018 SN - 0308-0501 VL - 49 IS - 5 SP - 509 EP - 511 PB - Wiley CY - New York, NY AN - OPUS4-63920 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wu, Hongyi T1 - Experimental investigating flame propagation of vegetation fire in different scales N2 - Since we are facing more extreme weathers, the occurrence of wildfire has also increased accordingly. The EU project TREEADS aims to adopt a holistic forest fire management and an adaptive, collaborative governance approach based on the deployment of a new systemic and technological framework covering all three interconnected fire management stages: prevention & preparedness, detection & response, and restoration & adaptation. As part of the task in the so-called German pilot, numerical simulations are performed to investigate the influencing factors for vegetation fires with fire dynamics simulator (FDS). The characteristics of vegetation are strongly related to the local weather and ecosystem. The investigation of the fire behavior of vegetation must be based on the local vegetation in Germany. Thus, the flame propagation of typical vegetation in Germany (pine needles, oak leaves, European beech leaves etc.) was investigated in small scale and medium scale experiments. These results are used as validation case studies for the further simulations. T2 - NFSD Nordic Fire and Safety Days CY - Lund, Sweden DA - 18.06.2024 KW - Vegetation fire KW - Flame propagation KW - Vegetation in Germany KW - SBI-test KW - Wildfire PY - 2024 UR - https://ri.diva-portal.org/smash/record.jsf?pid=diva2%3A1869356&dswid=6005 AN - OPUS4-60632 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Klippel, Andrea A1 - Hofmann-Böllinghaus, Anja A1 - Heydick, Lukas A1 - Piechnik, Kira A1 - Wu, Hongyi A1 - Köhler, Florian T1 - Experimental Analysis of Fire Behaviour in Pine Forests and Agricultural Fields Large Scale Tests conducted within the TREEADS Project N2 - In two large-scale tests fire spread mechanisms in vegetation ground fires were studied in a pine forest and a crop field. Both fires were ignited with a drip torch using a gasoline-diesel mix. The tests were part of the European TREEADS project, specifically in the research work from the German Pilot focusing on Saxony-Anhalt and Brandenburg. These regions are known for dry, sandy soil, with pine trees covering approximately 73% of forested areas in Brandenburg and 48% in Saxony-Anhalt. The results of both experiments make a substantial contribution to optimizing extinguishing methods and strategies and enhancing a continued wildfire research in Germany. The test areas included a 16 x 22 m plot in a Saxony-Anhalt pine forest and a 20 x 100 m plot on a crop field, with fires ignited along a line using a drip torch at both locations. Fire spread was monitored with video and IR cameras mounted on a drone. In the pine forest, 96 thermocouples and gas sensors were attached to trees and a mobile FTIR spectrometer was used for real-time gas measurements. A protective strip was created around the test area using a soil tiller and fire-retardant foam to prevent uncontrolled fire spread. The experiment showed a consistent temperature rise as the fire was ignited and spread. Thermocouple data captured detailed thermal dynamics, while tree-mounted gas sensors recorded significant fluctuations in combustible gases. Real-time gas spectra from the FTIR spectrometer enabled precise smoke analysis. Conducted in stable weather - 23°C, light wind, low soil moisture—this setup improved reproducibility, with a weather station monitoring temperature, humidity and wind conditions to assess fire-environment interactions. After ignition process the fire showed a slow spread and distinct combustion phases. Smouldering was more pronounced in areas with grasses and deadwood, highlighting vegetation-specific burn patterns critical to wildfire research. The experiment showed numerous smouldering and burning spots, with flames igniting and extinguishing repeatedly. However, flame height did not exceed half a meter. Due to substantial smoke production, visibility in the test field was limited and team members wore respirators to collect specific smoke gases such as benzene and formaldehyde for analysis. Field measurements showed flame temperatures exceeding 500°C. Toxic smoke gas concentrations of up to 238 ppm CO were measured, although precise gas capture appeared challenging due to wind turbulence. The second large-scale area in Nauen, a cut wheat field (stubble height approx. 30 cm) was burned, with fire spreading across approximately 700 m². A 20 m ignition line directed flames with the wind. Fire spread was observed using drones equipped with IR cameras. Experiments demonstrated how unpredictable and challenging it is to measure large outdoor fires. To enable a comprehensive theoretical and numerical description of fire dynamics in wildfires, it is essential to conduct further large-scale experiments. T2 - Interflam 2025, 16th International Fire Science and Engineering Conference CY - London, United Kingdom DA - 30.06.2025 KW - Wildfire PY - 2025 SP - 1435 EP - 1444 PB - Interscience CY - London AN - OPUS4-63926 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR ED - Manzello, Samuel L. ED - Hofmann-Böllinghaus, Anja T1 - Special issue on wildland-urban interface (WUI) fires N2 - Special issue on wild-urban interface (WUI) fires with 25 papers in total. Contributed papers came from all across the globe and included Algeria, Australia, Brazil, China, France, Germany, Japan, Poland, Norway, New Zealand, Spain, Sweden, and the United States of America. The global coverage of contributed papers demonstrated the growing nature of the WUI fire problem. KW - Wildfire PY - 2025 UR - https://onlinelibrary.wiley.com/toc/10991018/2025/49/5 SN - 1099-1018 SN - 0308-0501 VL - 49 IS - 5 SP - 507 EP - 846 PB - Wiley CY - New York, NY AN - OPUS4-63992 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Piechnik, Kira A1 - Hofmann-Böllinghaus, Anja A1 - Klippel, Andrea T1 - Characterization and assessment of smoke emissions from smouldering forest fires: a combined experimental and numerical approach N2 - This article builds upon the publication "Comprehensive Laboratory Study on Smoke Gases During the Thermal Oxidative Decomposition of Forest and Vegetation Fuels"1 in Fire and Materials, 2024, summarizing the experimental methodology and highlighting key findings. The study investigates the gas-phase composition of smoke emissions from forest and vegetation fuels. The study focuses on pine-dominated ecosystems in Eastern Germany, with the objective of improving the understanding of wildfire-related gaseous emissions, as a contribution to the German pilot activities within the EU Project TREEADS. Using a modified DIN tube furnace in a bench-scale setup, the investigation centers on gaseous emissions from five trees and two ground cover species, explicitly excluding particulate matter. T2 - Interflam 2025, 16th International Fire Science and Engineering Conference CY - London, UK DA - 30.06.2025 KW - Wildfire PY - 2025 SP - 288 EP - 294 PB - Interscience CY - London AN - OPUS4-63999 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Klippel, Andrea A1 - Hofmann-Böllinghaus, Anja T1 - Experimental Analysis of Fire Behaviour in Pine Forests and Agricultural Fields Large Scale Tests conducted within the TREEADS Project N2 - In two large-scale tests fire spread mechanisms in vegetation ground fires were studied in a pine forest and a crop field. Both fires were ignited with a drip torch using a gasoline-diesel mix. The tests were part of the European TREEADS project, specifically in the research work from the German Pilot focusing on Saxony-Anhalt and Brandenburg. These regions are known for dry, sandy soil, with pine trees covering approximately 73% of forested areas in Brandenburg and 48% in Saxony-Anhalt. The results of both experiments make a substantial contribution to optimizing extinguishing methods and strategies and enhancing a continued wildfire research in Germany. The test areas included a 16 x 22 m plot in a Saxony-Anhalt pine forest and a 20 x 100 m plot on a crop field, with fires ignited along a line using a drip torch at both locations. Fire spread was monitored with video and IR cameras mounted on a drone. In the pine forest, 96 thermocouples and gas sensors were attached to trees and a mobile FTIR spectrometer was used for real-time gas measurements. A protective strip was created around the test area using a soil tiller and fire-retardant foam to prevent uncontrolled fire spread. The experiment showed a consistent temperature rise as the fire was ignited and spread. Thermocouple data captured detailed thermal dynamics, while tree-mounted gas sensors recorded significant fluctuations in combustible gases. Real-time gas spectra from the FTIR spectrometer enabled precise smoke analysis. Conducted in stable weather - 23°C, light wind, low soil moisture—this setup improved reproducibility, with a weather station monitoring temperature, humidity and wind conditions to assess fire-environment interactions. After ignition process the fire showed a slow spread and distinct combustion phases. Smouldering was more pronounced in areas with grasses and deadwood, highlighting vegetation-specific burn patterns critical to wildfire research. The experiment showed numerous smouldering and burning spots, with flames igniting and extinguishing repeatedly. However, flame height did not exceed half a meter. Due to substantial smoke production, visibility in the test field was limited and team members wore respirators to collect specific smoke gases such as benzene and formaldehyde for analysis. Field measurements showed flame temperatures exceeding 500°C. Toxic smoke gas concentrations of up to 238 ppm CO were measured, although precise gas capture appeared challenging due to wind turbulence. The second large-scale area in Nauen, a cut wheat field (stubble height approx. 30 cm) was burned, with fire spreading across approximately 700 m². A 20 m ignition line directed flames with the wind. Fire spread was observed using drones equipped with IR cameras. Experiments demonstrated how unpredictable and challenging it is to measure large outdoor fires. To enable a comprehensive theoretical and numerical description of fire dynamics in wildfires, it is essential to conduct further large-scale experiments. T2 - Interflam 2025, 16th International Fire Science and Engineering Conference CY - London, United Kingdom DA - 30.06.2025 KW - Wildfire KW - Large scale tests PY - 2025 AN - OPUS4-63923 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Simon T1 - Predicting Wildfire Propagation in Europe, the Middle East and North Africa using Convolutional Neural Networks with an adjusted Dataset N2 - Wildfires pose a significant threat to ecology, economy, and human lives alike. Droughts and heat waves fueled many fire occurrences in the last years, and the ongoing climate change increases the risk of larger, more devastating events. As part of the TREEADS project, funded by Horizon 2020 (EU), we are developing a wildfire propagation model, which is an important part of possible counter measures to support decision makers and firefighters in their actions against uncontrolled fire spread. With recent advances, machine learning became applicable for wildfire propagation modelling. Once the time-consuming training process is finished, predictions are fast, even on devices with low computational power. On the downside, large datasets are crucial to train robust models, but temporally accurate propagation data of real fire occurrences are sparse. To solve this problem, we reconstructed wildfire propagation in 12-hour intervals for over 5500 events with varying sizes and durations in Europe, the Middle East, and North Africa. Thereto, burned area polygons from the European Forest Fire Information System (EFFIS) database were combined with active fire detection points from the Visible Infrared Imaging Radiometer Suite (VIIRS). The fire spread was reconstructed sequentially according to the revisiting times of VIIRS. This data was coupled with meteorological information from the ERA5 reanalysis product and surface information derived from Sentinel-2, as well as TanDEM-X remote sensing data. The aggregated dataset was then used to build a deep-learning convolutional neural network that captures meteorological effects, elevation, and vegetation on wildfire propagation. To account for the sequentially updated weather data from ERA5, long short-term memory (LSTM) with self-attention was included. In summary, we have constructed a novel wildfire propagation dataset suitable for machine learning purposes and developed a convolutional LSTM network for rapid prediction of fire spread. T2 - AGU24 CY - Washington D.C., USA DA - 09.12.2024 KW - Wildfire KW - Deep Learning KW - Convolutional Neural Network (CNN) KW - Remote Sensing PY - 2024 AN - OPUS4-64767 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wu, Hongyi T1 - Influence of local vegetation on ignition and fire spread of vegetation fires-Experimental and numerical approach N2 - To investigate the influence of local vegetation, it goes through two aspects. One is laboratory study, the local vegetation samples were collected and tested for the thermal properties, such as activation energy, heat content and reaction kinetic of pyrolysis and dehydration. At the same time, small and medium scale combustion experiments were conducted to investigate the burning behavior. The other aspect is using the thermal properties as the input parameters for the development of numerical simulation in the computational fluid dynamics (CFD) tool. These models were then be validated with the combustion experiments, as a baseline for the further scaling up of the models, in order to investigate how the parameters influencing the fire spread in a large-scale case numerically. T2 - Interflam 2025, 16th International Fire Science and Engineering Conference CY - London, United Kingdom DA - 30.06.2025 KW - Wildfire PY - 2025 AN - OPUS4-63933 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klippel, Andrea A1 - Hofmann‐Böllinghaus, Anja A1 - Piechnik, Kira A1 - Heydick, Lukas A1 - Wu, Hongyi A1 - Köhler, Florian A1 - Klaffke, Benjamin T1 - Experimental Analysis of Fire Behavior in Pine Forests and Agricultural Fields: Large‐Scale Tests Conducted Within the European TREEADS Project N2 - Two large‐scale experiments investigated fire spread mechanisms in vegetation ground fires in a pine forest and an agricultural field within the European TREEADS project. The tests, conducted in Saxony‐Anhalt and Brandenburg, targeted regions with dry, sandy soils and extensive pine stands and aim to improve suppression strategies and wildfire research. The forest experiment was conducted on a 16 × 22 m plot with line ignition using a gasoline‐diesel mix. Fire spread was documented with drone‐based video and infrared imaging. Ninety‐six thermocouples and two gas sensors were mounted on trees, and a mobile FTIR spectrometer enabled real‐time smoke analysis. A tilled and foam‐treated strip prevented uncontrolled spread. Under stable weather conditions (23°C, light wind, low soil moisture), a consistent temperature rise and distinct combustion phases were observed. Smoldering dominated in areas with mosses, grasses, and deadwood, with intermittent flaming, limited flame heights (< 0.5 m), and substantial smoke production. Peak temperatures exceeded 500°C, and CO concentrations reached 238 ppm, though wind turbulence complicated gas sampling. The second experiment on a cut agricultural field near Nauen involved burning approximately 700 m2 using a 20 m ignition line aligned with wind direction. Drone‐based infrared monitoring captured rapid spread on the stubble surface. The results underscore the variability and measurement challenges of outdoor fires and highlight the necessity of continued large‐scale experiments to support physical and numerical wildfire modeling. These findings provide essential empirical data for evaluating vegetation‐specific burning behavior, improving sensor deployment strategies, and refining validation approaches for next‐generation wildfire spread models under central European fuel and weather conditions, and supporting decision‐making in wildfire management. KW - Wildfire KW - Pine KW - Crop PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-654199 DO - https://doi.org/10.1002/fam.70045 SN - 0308-0501 SP - 1 EP - 11 PB - Wiley AN - OPUS4-65419 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Piechnik, Kira A1 - Heydick, Lukas A1 - Hofmann-Böllinghaus, Anja A1 - Klippel, Andrea T1 - Comprehensive laboratory study on smoke gases during the thermal oxidative decomposition of forest and vegetation fuels N2 - AbstractThis study investigates the composition of smoke gases in forest and vegetation samples to draw conclusions about the actual smoke gas composition during wildfires. The focus is particularly on regions with extensive pine forests, like in Eastern Germany. The relevance of smoke gases is well illustrated by the example of wildfires in Québec, influencing air quality in New York, in 2023. By employing a modified DIN tube furnace, a bench‐scale test set‐up, the research emphasizes the examination of smoke composition from tree species and ground cover, prioritizing gases while disregarding particles. Key smoke gases are identified as CO, CO2, SO2, HCN, C3H4O (acrolein) and CH2O (formaldehyde) and their concentrations are compared with Acute Exposure Guideline Levels (AEGL) limits. Acknowledging the limitations of AEGL usage and the problem with direct quantitative comparison of toxicant concentrations (cf. ISO 29903‐1:2020), the study highlights variations in smoke composition across different samples. The results of the studies reveal a significant disparity in CO concentration between dry and fresh pine needles. Frequently, the AEGLs of key gases are exceeded significantly. The elemental analysis of the barks indicates distinct differences in composition, reflecting in the concentrations of smoke gases. The ratio of 1 mole of substance turnover to the identified key components will be used to determine input parameters for the subsequent numerical simulation. KW - Forest KW - Wildfire KW - Ignition PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-617744 DO - https://doi.org/10.1002/fam.3253 SP - 1 EP - 12 PB - Wiley online library AN - OPUS4-61774 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Wu, Hongyi A1 - Buhk, Frederik A1 - Christiani, Ricardo A1 - Hofmann-Böllinghaus, Anja T1 - Influence of local vegetation on ignition and fire spread of vegetation fires-Experimental and numerical approach N2 - Within the framework of the European TREEADS project, Brandenburg and Saxony-Anhalt were designated as model regions. This designation facilitated the investigation of vegetation types, soil structure, and soil dryness. Brandenburg and Saxony-Anhalt are identified as the driest regions in Germany according to the annual mean soil moisture data. In these regions, 48% to 73% of the forests are composed of pine species. The soil profile is characterized by a relatively thin organic layer, measuring between 0.2 and 0.3 meters, underlain by sandy substrates. Consequently, surface and ground fires are more prevalent in these areas compared to other types of fires, such as crown fires. To investigate the influence of local vegetation, it goes through two aspects. One is laboratory study, the local vegetation samples were collected and tested for the thermal properties, such as activation energy, heat content and reaction kinetic of pyrolysis and dehydration. At the same time, small and medium scale combustion experiments were conducted to investigate the burning behavior. The other aspect is using the thermal properties as the input parameters for the development of numerical simulation in the computational fluid dynamics (CFD) tool. These models were then be validated with the combustion experiments, as a baseline for the further scaling up of the models, in order to investigate how the parameters influencing the fire spread in a large-scale case numerically. T2 - Interflam 2025, 16th International Fire Science and Engineering Conference CY - London, United Kingdom DA - 30.06.2025 KW - Wildfire PY - 2025 SP - 2221 EP - 2225 PB - Interscience CY - London AN - OPUS4-63932 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Müller, Simon T1 - FireSpread_MedEU N2 - Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 313 consecutive burned area maps from 102 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling. KW - Wildfire KW - Spread KW - Machine Learning PY - 2025 DO - https://doi.org/10.5281/zenodo.16813435 PB - Zenodo CY - Geneva AN - OPUS4-64768 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Piechnik, Kira A1 - Hofmann-Böllinghaus, Anja A1 - Klippel, Andrea T1 - Self‐ignition of forest soil samples demonstrated through hot storage tests N2 - AbstractThe increasing threat of forest fires on a global scale is not only a matter of concern due to the potential harm they may cause to both human and animal life but also due to their significant role in exacerbating climate change. In light of these circumstances, one might inquire as to whether forest soil can self‐ignite and, if so, under what conditions and at what temperatures this phenomenon may occur. This question is being addressed in the German pilot “Fire science of wildfires and safety measures” of the EU project TREEADS, and the first results are presented below. The importance of basic research into the self‐ignition of forest soil cannot be underestimated, as it provides crucial knowledge to prevent forest fires and protect human and animal health. Furthermore, mitigating the occurrence of forest fires can also play a role in reducing greenhouse gas emissions, contributing to global efforts to combat climate change. The procedure of the hot storage test is an effective means of determining whether a material can self‐ignite. During the investigation of six soil samples, it was found that five of them were indeed capable of self‐ignition. In addition to determining whether the material ignites, the modified hot storage test also analyzed the resulting smoke gases and measured their concentration. The research question of whether regional forest soil is capable of self‐ignition can be answered with yes based on these initial tests. Further experiments are needed to determine if self‐ignition causes forest fires. KW - FTIR KW - Hot storage KW - Ignition KW - Soil KW - Wildfire PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-594617 DO - https://doi.org/10.1002/fam.3198 SN - 1099-1018 VL - 48 IS - 4 SP - 495 EP - 507 PB - Wiley CY - New York, NY AN - OPUS4-59461 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Müller, Simon A1 - Hofmann-Böllinghaus, Anja A1 - Chen, Zhimin A1 - Vogel, Kristin A1 - Benner, Philipp T1 - A high-resolution spatiotemporal wildfire propagation dataset for the Mediterranean and Europe N2 - Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 320 consecutive burned area maps from 103 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling. KW - Wildfire KW - Remote Sensing KW - Data PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-657294 DO - https://doi.org/10.1038/s41597-026-06965-2 SN - 2052-4463 VL - 13 IS - 1 SP - 1 EP - 7 PB - Springer Science and Business Media LLC AN - OPUS4-65729 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -