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In this regard, additive printed electronics (PE) offer a viable alternative with their flexibility and ultra-low-cost manufacturing. printed analog neuromorphic circuits (pNCs) are well-suited for these target applications, especially for classification tasks, as their low device count can efficiently meet the needs of the technology. However, low-cost additive manufacturing comes with higher defect rates, such as misprints, broken connections, and defective components, posing significant challenges to the reliability of printed circuits. This article presents a novel co-design of training algorithm and hardware for fault-tolerant pNCs using fault-aware training (FAT). The proposed method introduces a fault-tolerant version of printed nonlinear transformation circuits, combined with a bespoke training process that selects different types of printed activation functions (AFs) for different neurons to optimize both fault endurance and hardware costs. Experiments on benchmark datasets demonstrate an improvement in the accuracy of fault-tolerant (FT) pNCs from 62.1% to 79.4% under a 10% fault rate. Moreover, combining both normal and fault-tolerant versions of activation functions (AFs) using\n            <jats:italic toggle=\"yes\">gumble-softmax<\/jats:italic>\n            distribution shows an acceptable accuracy drop with an average reduction in power and area of 54.5% and 6.54%, respectively, while reducing the training time significantly by 56.2%, compared to only using FT-AFs.\n          <\/jats:p>","DOI":"10.1145\/3758096","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:13:16Z","timestamp":1754565196000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["PRINT-SAFE: Printed Ultra-Low-Cost Electronic X-Design with Scalable Adaptive Fault Endurance"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2977-8471","authenticated-orcid":false,"given":"Priyanjana","family":"Pal","sequence":"first","affiliation":[{"name":"Department of Computer Science-CDNC - Chair of Dependable Nano Computing, Karlsruhe Institute of Technology","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6893-6318","authenticated-orcid":false,"given":"Tara","family":"Gheshlaghi","sequence":"additional","affiliation":[{"name":"Department of Computer Science-CDNC - Chair of Dependable Nano Computing, Karlsruhe Institute of Technology","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7018-1159","authenticated-orcid":false,"given":"Haibin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Computer Science-Chair of Pervasive Computing Systems, Karlsruhe Institute of Technology","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7583-2376","authenticated-orcid":false,"given":"Michael","family":"Hefenbrock","sequence":"additional","affiliation":[{"name":"RevoAI GmbH, RevoAI GmbH","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5009-2327","authenticated-orcid":false,"given":"Michael","family":"Beigl","sequence":"additional","affiliation":[{"name":"Department of Computer Science-Chair of Pervasive Computing Systems, Karlsruhe Institute of Technology","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8829-5610","authenticated-orcid":false,"given":"Mehdi","family":"Tahoori","sequence":"additional","affiliation":[{"name":"Department of Computer Science-Chair of Dependable Nano Computing, Karlsruhe Institute of Technology","place":["Karlsruhe, Germany"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3390\/s21041509"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","unstructured":"Qizeng Sun Li Wang Guozhang Ren Linrong Zhang Huixiang Sheng Yameng Zhu Hongchen Wang Gang Lu Hai-Dong Yu and Wei Huang. 2022. 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