<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">BMT</journal-id><journal-title-group><journal-title>Biomaterials Translational</journal-title></journal-title-group><issn>TBA</issn><eissn>2096-112X</eissn><publisher><publisher-name>Biomaterials Translational</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.12336/biomatertransl.2024.01.001</article-id><article-categories><subj-group subj-group-type="heading"><subject>Editorial</subject></subj-group></article-categories><title>Generation artificial intelligence (GenAI) and  Biomaterials Translational: steering innovation  without misdirection</title><url>https://artdesignp.com/journal/BMT/5/1/10.12336/biomatertransl.2024.01.001</url><author>BaiLong,XiaZhidao,TriffittJames T.,SuJiacan</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>5</volume><issue>1</issue><history><date date-type="pub"><published-time>2024-03-28</published-time></date></history><abstract/><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>1. Szymanski, N. J.; Rendy, B.; Fei, Y.; Kumar, R. E.; He, T.; Milsted, D.; McDermott, M. J.; Gallant, M.; Cubuk, E. D.; Merchant, A.; Kim, H.; Jain, A.; Bartel, C. J.; Persson, K.; Zeng, Y.; Ceder, G. An autonomous laboratory for the accelerated synthesis of novel materials. Nature. 2023, 624, 86-91.
2. Leeman, J.; Liu, Y.; Stiles, J.; Lee, S.; Bhatt, P.; Schoop, L.; Palgrave, R. Challenges in high-throughput inorganic material prediction and autonomous synthesis. ChemRxiv. 2024. doi:10.26434/chemrxiv-2024-5p9j4.
3. Jiang, Y.; Salley, D.; Sharma, A.; Keenan, G.; Mullin, M.; Cronin, L. An artificial intelligence enabled chemical synthesis robot for exploration and optimization of nanomaterials. Sci Adv. 2022, 8, eabo2626.
4. Grisoni, F.; Huisman, B. J. H.; Button, A. L.; Moret, M.; Atz, K.; Merk, D.; Schneider, G. Combining generative artificial intelligence and on-chip synthesis for de novo drug design. Sci Adv. 2021, 7, eabg3338.
5. Lutz, I. D.; Wang, S.; Norn, C.; Courbet, A.; Borst, A. J.; Zhao, Y. T.; Dosey, A.; Cao, L.; Xu, J.; Leaf, E. M.; Treichel, C.; Litvicov, P.; Li, Z.; Goodson, A. D.; Rivera-S&amp;aacute;nchez, P.; Bratovianu, A. M.; Baek, M.; King, N. P.; Ruohola-Baker, H.; Baker, D. Top-down design of protein architectures with reinforcement learning. Science. 2023, 380, 266-273.
6. Kavungal, D.; Magalh&amp;atilde;es, P.; Kumar, S. T.; Kolla, R.; Lashuel, H. A.; Altug, H. Artificial intelligence-coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases. Sci Adv. 2023, 9, eadg9644.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
