MaterialsZone™

Most materials scientists don’t struggle with #AI. They struggle with where to start. Because it feels like a career shift. Like stepping into a different world. It’s not! The real starting point is much closer to your current work than you think — and it’s not another course. If you’re trying to figure out how AI actually fits into real R&D, Omri Schulman breaks it down in our new #MZInsight piece. #MaterialsScience #MachineLearning #AIGuidedRnD #MaterialsInformatics #DeepTech #Innovation #RnD #FutureOfRnD

Two recent #webinars. Two different #industries. One clear #pattern. We had hundreds of participants join us and take part in live polls during the sessions, and the results were fascinating! #AI adoption in R&D isn’t being held back by a lack of interest. It’s being held back by a perceived lack of readiness. The gap isn’t ambition. It’s #data, structure, and confidence in where to start. At MaterialsZone™, we’ve been working on exactly this. We know how to #DoItRight. Turning experimental data into structured, AI-ready assets so teams can improve data quality, lower the expertise barrier, and actually get value from AI. The webinars sparked great discussions across both industries. If you missed them, you can watch them on demand (link in the first comment). #MaterialsInformatics #AIinRnD #MaterialsScience #DigitalTransformation

Uncertainty is everywhere in #materials ML. Formulations vary by batch, measurements come from different labs, datasets are small, and the most important variables are often missing... Building predictive models in this environment requires more than algorithms. It requires understanding the data and the problem itself. Where does this uncertainty actually come from? In this #MZInsight, Avy Tahan, our AI/ML Team Lead, breaks down the main sources of uncertainty in materials development and practical ways to reduce them. Rare and great perspective from someone who deals with these challenges every day! Worth a read if you’re working with #AI in R&D. #MZInsight #MaterialsInformatics #MaterialsScience #MachineLearning #AIinRnD #MaterialsInnovation #ML

📣 We are so excited to be exhibiting at the American Coatings Show 2026, taking place May 5–7 in Indianapolis!!! Looking forward to meeting the #coatings innovation community and discussing how #AI and structured #MaterialsData are shaping the future of R&D. Many thanks to the American Coatings Association for hosting such an important industry event. 🙏 See you at Booth 229! ✍ #ACS2026 #ACS26Exhibitor #MaterialsZone #RnD #AIinRnD #MaterialsInformatics #Data

We’re going live today! 🎉 In just a few hours, we’ll be hosting our #webinar with Plastics Technology: “Making #AI Work in #Plastics.” Omri Schulman and Jeff Glickman will walk through how plastics teams are structuring R&D #data, connecting #workflows, and turning #experimentation into #SmarterDecisions. If you’re working in plastics R&D or #innovation, you’re very welcome to join us. 😊 Registration link in the repost. 🙏

🗓 Next week, March 11th | 11 AM ET, we’re collaborating with Plastics Technology to host a live webinar: “Making AI Work in Plastics.” This session is about the operational side of AI in #plastics R&D. How teams structure their data. How they connect workflows. How they move from experimentation to smarter decisions. #AI in plastics isn’t a future concept. It’s already shaping how #formulations are optimized, how #trials are reduced, and how development cycles are shortened. Omri Schulman and Jeff Glickman will walk through what that looks like in practice, and what it takes to make it sustainable inside real organizations. Register here to join live: https://lnkd.in/dkhJJHkZ #AIGuidedRnD #MaterialsInformatics #DigitalRnD #ManufacturingInnovation #Webinar #PlasticsRnD

During our webinar this past Tuesday, we asked attendees: “What is your biggest barrier to adopting AI in R&D?” The answers were insightful: • 34% — Data quality • 23% — Lack of internal expertise • 18% — Uncertainty about ROI • 16% — Budget • 6% — Change management The biggest barrier isn’t budget. Before scaling AI, most teams are struggling with something much more fundamental: Is our data structured, reliable, and usable? How do we know? That’s where real AI adoption either starts… or stalls. The full webinar recording is in the first comment. Highly recommended for those interested in seeing practical use cases of doing AI-Guided R&D right, including practical, real-world insights. #AIGuidedRnD #MaterialsInformatics #PaintsAndCoatings #DigitalRnD #RnDInnovation

🗓 Next Tuesday, February 24th | 11 AM ET We’re teaming up with Paint & Coatings Industry Magazine to talk about something very practical: what it actually takes to make AI work in paints & coatings R&D. Not theory. Real formulation challenges. Real implementation questions. Real ROI. From predicting long-term stability to reducing formulation costs and accelerating development timelines, we’ll share how coatings teams are moving from pilots to real impact. If you’re leading innovation, formulation, or R&D strategy, this session is built for you. Register to attend live: https://lnkd.in/d6-gbUDF #Webinar #MaterialsScience #AI #RnD #Innovation #DoingItRight

We’re hiring a Solutions Engineer 🧠⚙️ If you like turning messy materials data into “oh wow, that’s actually useful”, enjoy teaming up with R&D folks, and get a tiny dopamine hit from cracking technical puzzles, you’ll feel right at home here. 😉 Curious? Take a look and fill the form👇 https://lnkd.in/d_NeiCHy #Hiring #SolutionsEngineer #MaterialsScience #AI #DeepTech #RnD #TechJobs #MaterialsZone

#MaterialsRnD is changing, and so is the researcher’s role. In this #MZInsight, Omri Schulman breaks down how #AI is shifting the work from “what should I try next?” to “what should I learn next?” and why structuring #data is becoming a core R&D skill. If you’re working in formulation or materials development, this one’s definitely worth a read. Read it here 👇 #MaterialsZone #AIinRnD #MaterialsScience #DigitalRnD