Contributions WP3.2

• Mareen N. Warncke, Carola H. Böhmer, Philippa R. C. Böhnke, Ann-Malin Schmidt, Andreas Nocke, Johannes Mersch, Chokri Cherif”Quantifying the Human Perception: Development and Characterization of Textile-Based Capacitive Strain and Pressure Sensors” 22th AUTEX World Textile Conference (scientific.net), (2023).

 

• Chakraborthy, A., Nuthalapati, S., Escher, R., Nag, A., & Altinsoy, M. E. (2023). “Flexible Tactile Sensors Based on 3D Printed Moulds,” In Sensing Technology: Proceedings of ICST’15 (pp. 421-430). Cham: Springer Nature Switzerland.

 

• Sapra, S., Chakraborthy, A., Nuthalapati, S., Nag, A., Inglis, D. W., Mukhopadhyay, S. C., & Altinsoy, M. E. (2023). “Printed, wearable e-skin force sensor array”, Measurement, 206, 112348.

 

• Chakraborthy, A., Nuthalapati, S., Nag, A., Afsarimanesh, N., Alahi, M. E. E., & Altinsoy, M. E. (2022). “A Critical Review of the Use of Graphene-Based Gas Sensors,” Chemosensors, 10(9), 355.

 

• Nag, A., Simorangkir, R. B., Gawade, D. R., Nuthalapati, S., Buckley, J. L., O’Flynn, B., … & Mukhopadhyay, S. C. (2022). “Graphene-based wearable temperature sensors: A review,” Materials & Design, 110971.

 

• Nag, A., Afsarimanesh, N., Nuthalapati, S., & Altinsoy, M. E. (2022). “Novel surfactant-induced MWCNTs/PDMS-based nanocomposites for tactile sensing applications,” Materials, 15(13), 4504.

 

• R. Kirchner, R. Rosenkranz, and M. E. Altinsoy, “Erzeugung von Berührungsillusionen durch räumlich verteilte Vibrationen“, DAGA 2023 – 49th German Annual Conference of Acoustics. Hamburg, Germany, 2023.

 

• R. Kirchner, R. Rosenkranz, B. Gonzalez Sousa, S.-C. Li, and M. E. Altinsoy, “Phantom illusion based vibrotactile rendering of affective touch patterns”, IEEE Transactions on Haptics, https://doi.org/10.1109/TOH.2023.3315964.

 

• A. L. Fietkau, S. Stone, P. Birkholz, “Relationship between the acoustic time intervals and tongue movements of German diphthongs”, in Proc. Interspeech 2022, doi: 10.21437/Interspeech.2022-73.

 

• Li, Y., Huang, S., Peng, S., Jia, H., Pang, J., Ibarlucea, B., Hou, C., Cao, Y., Zhou, W., Liu, H., Cuniberti, G., “Toward Smart Sensing by MXene.” Small 2023, 19, 2206126. https://doi.org/10.1002/smll.202206126.

 

• Panes-Ruiz, L.A., Huang, S., Riemenschneider, L., Croy, A., Ibarlucea, B., Cuniberti, G. (2023). “Surface-Functionalized Multichannel Nanosensors and Machine Learning Analysis for Improved Sensitivity and Selectivity in Gas Sensing Applications.” In: , et al. Advances in System-Integrated Intelligence. SYSINT 2022. Lecture Notes in Networks and Systems, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-031-16281-7_66.

 

• Huang, S., Croy, A., Panes-Ruiz, L.A., Khavrus, V., Bezugly, V., Ibarlucea, B. and Cuniberti, G. (2022), “Machine Learning-Enabled Smart Gas Sensing Platform for Identification of Industrial Gases.” Adv. Intell. Syst., 4: 2200016. https://doi.org/10.1002/aisy.202200016.

 

• Schmidt, A.-M., Kyosev, K. (2023), “Particle based simulation of the polymer penetration into porous structures during the fused deposition modelling” Journal of Manufacturing Processes, 101, doi: https://doi.org/10.1016/j.jmapro.2023.06.040.

 

• S. Huang, L. Panes-Ruiz, B. Ibarlucea, G. Cuniberti. Rapid detection of SARS-CoV-2 antigen utilizing machine learning-enabled graphene-based smart gas sensors. 2023 IEEE MetroXRAINE conference. Milano, Italy, 25th-27th, October, 2023.

 

• S. Huang, L. Riemenschneider, L. Panes-Ruiz, B. Ibarlucea, G. Cuniberti. Discrimination of Complex Mixtures Using Carbon Nanotubes-based Multichannel Electronic Nose: Coffee Aromas.2023 IEEE NMDC 2023 conference, Paestum, Italy, 22th-25th, October, 2023.

 

• D. Prousalis, V. Ntinas, I. Messaris, A. S. Demirkol, A. Ascoli, and R. Tetzlaff. ”Stochastic template in cellular nonlinear networks modeling memristor induced synaptic noise”. In Proceedings of the 18th ACM International Symposium on Nanoscale Architectures NANOARCH ’23, Dresden, Germany, December 18 – 20, 2023, Article 23, 1–3. 

 

• Huang., Croy, A., Ibarlucea, B., & Cuniberti, G. (2023). Machine Learning-Driven Gas Identification in Gas Sensors. In Machine Learning for Advanced Functional Materials (pp. 21-41). Singapore: Springer Nature Singapore.

 

• Parichenko, A., S. Huang., Pang, J., Ibarlucea, B., & Cuniberti, G. (2023). Recent advances in technologies toward the development of 2D materials-based electronic noses. TrAC Trends in Analytical Chemistry, 117185.

 

• Nag, A., Chakraborthy, A., Vega, M. R. O., Nuthalapati, S., Harija, H., Özer, M. S., & Altinsoy, M. E. (2023). Ultra-low-cost graphene/fabric-based sensors: Part I-Characterization and Preliminary results. IEEE Sensors Journal.

 

• D. Prousalis, I. Messaris,A. A. Sayed, V. Ntinas, A. S. Demirkol, A. Ascoli, and R. Tetzlaff, “Image Processing with Memristor Cellular Nonlinear Networks Featuring Volatile Threshold Switches”, accepted in Intern. Conf. SMACD, 2-5 July 2024.