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Materials Science
Mega Webinar 

April 10th, 2024

9:00 a.m. EDT

Scientific software is a core need in today's virtual and physical Materials Science research and development. Whether capturing your scientific method or simulating your virtual experiments, the IT and Informatics capabilities are critical to your immediate and future successes. 

Speakers & Sponsors

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Citrine Logo.png
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Alaaeddin Alsbaiee_Headshot.jpeg

R&D Manager


Talk Title: Towards Closing the Loop for Polyurethane Foams: Challenges and Opportunities

Abstract: Polyurethane, a highly versatile and extensively utilized polymer class, plays a pivotal role in a wide range of industries, including construction, furniture, automotive, electronics, appliances, footwear, and packaging. In 2021, its global market volume reached 24.7 million metric tons, with a market value of USD 75.19 billion in 2022. Despite its immense popularity, the recycling of polyurethanes remains challenging due to their remarkable chemical resistance and resilience, which poses implications for plastic pollution and sustainability efforts. This talk will provide an overview of polyurethanes and their current recycling challenges and practices while shedding light on potential future directions towards closing the loop for polyurethanes.

Michael Ashley_Headshot.jpeg

Product Management


Talk Title: Electrochemistry for the Profitable Decarbonization of Chemicals

Abstract: The chemicals industry is one of the most challenging yet important to decarbonize. Currently in the United States, the production of chemicals is responsible for ~200 million metric tons of CO2 equivalent emissions per year and >30% of fossil resource consumption. One of the most promising avenues to decarbonize chemicals production is the use of renewable electrons as reagents via electrochemistry, enabling low temperature, low pressure transformations, and eliminating the need for stoichiometric oxidizing or reducing agents. Green hydrogen production via low-temperature water electrolysis has garnered significant investment as a route to decarbonization via electrochemistry, but challenging economics are resulting in slow deployment. Mattiq is developing electrolyzer technologies for cost-competitive, low-carbon chemical products, such as acetic acid and adipic acid. We anticipate that attractive economics will accelerate the adoption of clean electrochemical processes at scale.

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Citrine Informatics

Talk Title: How AI is changing the face of physical product development

Abstract: AI is driving transformational change across many domains, but there is a misperception that AI in product development is at a disadvantage. Materials development lacks large data sources and demands highly specialized knowledge of its applications. Join Kyle Killebrew, COO at Citrine Informatics, to learn how and why AI can leverage human expertise for powerful outcomes in the limited data environments of product development. From discovery of new candidate materials and formulations through commercialization and scale, AI is enabling problem solving in at least half the time of traditional methodologies. In this talk, hear about impactful examples of success in several industries, key requirements for successful introduction in product development, and why treating AI as a strategic imperative is critical to unlocking its true value.

Nicolas Onofrio_Headshot.jpeg

Technical Sales Representative

Software for Chemistry & Materials

Talk Title: Accelerating Battery Research through Atomistic Computational Chemistry

Abstract: Computational screening and simulations offer a fast and efficient pathway to developing advanced battery materials. We will discuss our efforts to help researchers to perform atomistic modeling with the Amsterdam Modeling Suite (AMS). The AMS architecture decouples the atomic-level computational engines (including DFT, DFTB, ReaxFF, ML potentials) from the driving software, facilitating the investigation of potential energy landscapes, as well as mechanical and electronic characteristics across different theoretical frameworks. The AMS driver is pivotal for sophisticated exploration of potential energy surfaces, molecular dynamics, and Grand Canonical Monte Carlo simulations, drawing on the computational power of the engines for energy and force calculations. This integrated driver-engine system enables the prediction and analysis of crucial battery material behaviors and properties. We'll highlight case studies to optimize energy density, kinetics and the stability of battery materials. Further, we will explore potential advancements in machine learning that promise to expedite the discovery of materials.

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Noel Hollingsworth


Uncountable, Inc.

Talk Title: Creating AI Ready Data Infrastructure

Abstract: While topics like Generative AI and large language models have received a lot of attention, in the R&D world, most companies still only deploy AI for a small percentage of their work. In this talk Noel Hollingsworth, CEO of Uncountable, and Forbes 30 under 30 winner for his work in Artificial Intelligence and Machine Learning, will discuss the necessary steps for preparing your team to use AI. Learn what kind of data is needed, where AI can be a fit, and just as importantly, where it might not be a fit.

Dimitris Karapalis_Headshot.jpeg

Digital & AI Visioneer

20/15 Visioneers

Talk Title: AI-Powered Sustainability: Revolutionizing Formulation Development in the CPG Industry

Abstract: Coming Soon

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Vice President Strategic Partnerships

Infinita Lab

Talk Title: Testing & Benchmarking for Product Value-Proposition & Pricing

Abstract: Participants will learn how to design competitive material or product testing to benchmark an offering's value-proposition vs. an incumbent offerings, to be able to successfully develop positioning and pricing against competitor's products.

Jun Liu Headshot.jpeg

Sr. Marketing Manager

Revvity Signals

Talk Title: Using Big-Data and AI to Accelerate Specialty Chemicals Product Development

Abstract: The specialty chemical industry faces numerous challenges in the new product development (NPD) process, ranging from resource-intensive research to complex formulation optimizations. Artificial Intelligence (AI) emerges as a transformative toolbox, offering unprecedented opportunities for innovation and efficiency. AI-driven algorithms can expedite the identification of novel compounds by analyzing vast datasets, accelerating the discovery phase. In formulation, machine learning models enable predictive analytics, optimizing ingredient combinations for enhanced performance and cost-effectiveness. Moreover, AI enhances process control, ensuring consistency in production and minimizing waste. Collaborative AI platforms facilitate seamless communication among multidisciplinary teams, streamlining decision-making processes. As a result, AI not only expedites time-to-market for new specialty chemicals but also significantly reduces R&D costs. In this presentation, the presenter will explore AI in the context of NPD process and explain why embracing AI promises a paradigm shift, fostering innovation, sustainability, and competitiveness in an ever-evolving market.


Markus J. Buehler, PhD

McAfee Professor of Engineering


Talk Title: Agentic Strategies for Generative AI to Connect Scales, Disciplines, and Modalities 

Abstract: For centuries, researchers have sought out ways to connect disparate areas of knowledge. While early scholars were often experts across fields, specialization took hold in recent centuries. With the advent of Artificial Intelligence (AI), we can now explore relationships across areas (e.g., mechanics and biology) or even more disparate domains (e.g., science and art). However, many existing AI methods have limited capabilities when it comes to physical intuition and often hallucinate. We propose that the key to address challenges in conventional data-driven modeling is to blur the boundary between purely physics-based and purely data-driven modeling. To achieve this, we report the development of physics-inspired multimodal graph-based generative transformer models in a hierarchical multi-agent mixture-of-experts framework. The design of these models follows a bio-inspired approach where we re-use neural network structures repeatedly arranged in different patterns and utility, implementing a manifestation of the universality-diversity-principle that has been a powerful paradigm in bioinspired materials.  As for applications, this new generation of multiscale models allows us to mimic and improve upon natural processes by which materials evolve, and how they meet changing functional needs. Applied specifically to protein materials, the talk will cover case studies covering distinct scales, from silk, to collagen, to biomineralized materials, as well as applications to food and agriculture where materials design is critical to achieve performance targets. 

Patrick Ruch_Headshot.jpeg

Senior Research Scientist


Talk Title: How multi-modal foundation models can enhance data capture and reproducibility in scientific experimentation

Abstract: Confronted with the growing scale of scientific collaboration and experimentation, ensuring continuous data and metadata capture is a key factor in order to improve reproducibility in scientific discovery. In this talk, we outline the potential benefits of large multi-modal models in general, and vision-language models in particular, in assisting with the documentation and transcription of experimentation in research laboratories. We demonstrate the infrastructure required to implement such technology with a focus on ease-of-use, automation, and flexibility, and discuss future developments that will support early adoption of this rapidly evolving technology.

Joseph DiMartino_Headshot.jpeg

Luminata Solution Area Manager


Talk Title: Utilization of Digital Twins in support of Drug Substance Physical Form Characterization

Abstract: Coming Soon

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Materials Science MEGA Webinar
MARCH 7 & 8, 2023

Scientific software is a core need in today's virtual and physical Materials Science research and development. Whether capturing your scientific method or simulating your virtual experiments, the IT and Informatics capabilities are critical to your immediate and future successes. 

Applicable Materials Science Domains

  • Polymers 

  • Formulations 

  • CASE (coatings, adhesives, sealants, elastomers) 

  • Nanoparticles 

  • Alternative proteins (alternative meat industry) 

  • Lithium-ion batteries 

  • Biomaterials 

  • Design and Manufacturing 

  • Electronic Materials 

  • Energy Materials 

  • Metals and Ceramics 

  • Nanomaterials 

  • Polymeric Materials 

  • Surface Science 


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Platinum Sponsors

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silver Sponsors

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speaker agenda

Jun Liu Headshot.jpeg
Jun Liu

Sr. Marketing Manager



Revolutionizing Product Development through Smart Data Management


In today's rapidly advancing technological landscape, effective data management plays a crucial role in material science and product development. PerkinElmer Informatics Signals Research Platform offers a comprehensive solution to these challenges by bringing together the latest in data management and material science to help R&D organizations streamline their product development workflows. In this webinar, we will explore the capabilities of the Signals Research platform, including its advanced data management tools, its robust material science database, and its intuitive interface. Participants will learn how to leverage the platform's unique features to optimize product development and reduce time-to-market. By the end of the webinar, participants will have a better understanding of the role of smart data management in driving product development success.

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Scott Simpson, PhD

Assoc. Professor of Chemistry



The Molecular Corking Effect to Store Hydrogen



Hydrogen is a versatile, energy-dense gas that can be used as an alternative to fossil fuels in many applications, including transportation and power generation. However, widespread adoption of hydrogen fuels is limited, in part, by the inability to safely store and transport hydrogen gas outside of carefully controlled industrial environments. This project will study an intriguing chemical phenomenon called the "molecular corking effect," which may prove useful as a hydrogen gas storage mechanism. The molecular corking effect has been observed when hydrogen gas (diatomic hydrogen or H2) interacts with a class of materials called single-atom alloys. Single-atom alloys consist of a relatively inert noble metal surface interspersed with single atoms of catalytically-active metals such as platinum and palladium. When diatomic hydrogen gas contacts the single-atom alloy, the bond between the two hydrogen atoms is broken by the catalytically-active metal. The individual hydrogen atoms then spill over on the inert metal surface. A "cork" molecule that preferentially binds to the catalytically-active metal can be added to prevent the hydrogen atoms from reforming gaseous hydrogen. Hydrogen can be safely stored in this manner until the temperature is increased to remove the cork molecule and release the hydrogen gas from the surface. Fundamental insights into the entire molecular corking process must be developed to fully realize the potential of single-atom alloy hydrogen storage. The research objectives of this project will examine how molecular corks interact with single-atom alloys and describe the chemical characteristics of effective molecular corks.

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Claudio Cattevelli




Fluoropolymers: Concerns and Benefits


Highlight ongoing EU Commission analysis on PFAS. To analyze health concerns and try to visualize the real situation and the problems of not having proper alternatives to Fluoropolymers which will put in danger a large number of important and useful application in everyday lifetime for all mankind.

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Neil Kershaw

Synthetic Chemist






Noel Hollingsworth_ Uncountable_CEO_Headshot.jpg
Noel Hollingsworth




Why You Need a Structured Data System for Better Decision-Making in Materials Development



Managing large amounts of data stored and shared across various applications and tools has been and continues to be challenging for Materials, Chemicals, and broader R&D teams worldwide. With so much complexity in formulation, measurement, testing, and analysis, legacy data systems and incumbent solutions limit effective data management, leading to errors and inefficiencies in decision-making. Today, new and cutting-edge structured data systems are redefining Materials and Chemical Development organizations and driving better decisions and innovation. In this webinar, we'll discuss the limitations of legacy data systems and the benefits of implementing a modern, unified solution. Discover how a structured data system can help streamline workflows, improve collaboration, and provide accurate, accessible data for better decision-making and innovation. Learn about the differences between ELNs, LIMS, and modern structured data systems. Don't miss this opportunity to take your development to the next level.

John Walzer, PhD

Scientific Advisor



Overcoming Challenges to Automated Workflow Development in Materials Science


The Materials space presents unique challenges to the Discovery-Development-Deployment pipeline when compared to drug development, be it chemical (pharma) or Life Science focused. In many cases the ultimate product is an article of commerce and Product Life Management must be considered early in the development cycle. This presentation will discuss the applicability of modern R&D approaches (High Throughput Experimentation/Screening, automation, in silico screening) for various organizations (academia, startup, mature R&D organization, cloud lab) using example workflows from development pipelines for energy materials and polymers. Particular attention will be focused on developing or optimizing automated workflows in the materials space.

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Alysia Garmulewicz

Co-CEO & Founder



RegenLab: Materiom’s Autonomous Platform for biomaterial Synthesis and Testing


Materiom’s mission is to grow the biomaterials sector by 10x over the next decade. Using open data and AI, we empower scientists, entrepreneurs and companies to accelerate R&D and spur massive market entry. Materiom’s goal is for the autonomous platform to become a network of metrology equipment that synthesises and tests novel biofilms and biomaterials for material performance and manufacturability, including: mechanical performance (tensile and compression), rheology, barrier properties, and tests to assess a material’s compatibility with key biomaterial manufacturing processes (e.g. biofilm casting, thin film extrusion, etc.). The platform is used by Materiom to generate novel biomaterial recipes which are then shared open access on our platform. The platform is also used by biomaterial producers to rapidly develop and fine-tune biomaterial recipes in response to specific product-market niches across coatings and films, packaging, textiles, and other consumer goods.

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Nikolay Fateev

Head of Implementation



SciOps: A Transformational Framework for Accelerating Scientific Research


Scientific research is often hampered by low reproducibility rates, data loss, administrative burdens, and poor collaboration. These challenges can be overcome by adopting SciOps, a framework that applies best practices from other industries (such as design and software engineering) to optimize scientific workflows. In this talk, we will introduce the five pillars of SciOps: 1) Continuous improvement; 2) Sharing & collaboration; 3) Workflow automation; 4) Work in small batches; 5) Security & compliance. We will also demonstrate how SciOps can help scientific teams eliminate waste, speed up research, and increase output.

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Jilles Langeveld

Mechanical Engineer



The Magnetic Revolution of Cooling


A large proportion of the emissions related to cooling are hard to abate. The emissions of refrigerant gasses could account for 0.4 °C of global warming in 2100 (IEA, 2020). To reduce the climate impact of cooling, there is a need for an alternative, more efficient technology. At Magneto, we develop materials for a heating or cooling cycle based on the magnetocaloric effect, using metals instead of refrigerant gasses. We strive to create durable, efficient cooling and heating systems, with a lower total cost of ownership. Our technology will be 30% more energy-efficient than current cooling systems, without the use of polluting refrigerants. To gain a better understanding of the materials, and optimally use our R&D resources, we aim to create a data-driven model, using machine learning. In this webinar, we will share some of our challenges and our roadmap to contribute to a carbon-neutral future.

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Jonathan Pistorino




Battery Material Technology Scale-Up and Commercialization



Agenda - Tuesday, March 7th, 2023

Nick Reyonlds

Industry Process Consultant Director



Driving Innovation in Battery Materials Development with Computational Materials Science and Laboratory Informatics


The development of the next generation of batteries requires materials with improved properties.  Modeling and simulation methods at the molecular scale have advanced over the years for the prediction of the structure and properties of materials.  These methods provide a “Virtual Materials Lab” to accelerate materials development and guide experimental efforts.


Simulation methods allow researchers to study how changing cathode material structure affects open cell voltage, how anode molecular structure changes as Li ions diffuse in and out during charge/discharge cycles, and how the solid – electrolyte interface layer is built up and is stabilized.  This information helps guide materials selection and experimentation.


By connecting the length scales from the atomistic to the engineering scale, scientists and engineers are now able now able to, for example, study changes in battery electrolyte chemistry, predict the effect on Li ion diffusion, and from this predict changes in battery discharge curves.  Advances in Laboratory Informatics allow the creation of battery formulation recipes, and execution of lab workflows for the creation and testing of battery cells.


Examples of the use of computational materials science methods and laboratory testing for the development of improved battery materials will be highlighted, and attendees will see how the application of multi-scale modeling helps guide experimentation and accelerate battery materials development.

Markus Buehler, PhD

McAfee Prof. of Engineering



Digital Materials: From Ideation to Technology


Digital materials are designed through an integrated approach of large-scale computational modeling, material informatics, and artificial intelligence/machine learning to optimize and leverage novel smart material manufacturing for advanced mechanical properties, to create advanced products. Through the use of nanotechnology and additive manufacturing, and bio-inspired methods, we can now mimic and improve upon natural processes by which materials evolve, are manufactured, and how they meet changing functional needs. In this talk we show how we use mechanics to fabricate innovative materials from the molecular scale upwards, with built-in bio-inspired intelligence and novel properties, while sourced from sustainable resources, and breaking the barrier between living and non-living systems. This integrated materiomic approach is revolutionizing the way we design and use materials, and impacts many industries, as we harness data-driven modeling and manufacturing across domains and applications. The talk will cover several case studies covering distinct scales, from composites to biomaterials to food and agriculture, including hierarchical engineering.

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Craig Sterling






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Ian Stacey

Specials Projects & Advisor



SECOS Biopolymers – a disruptor to

conventional plastic use



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Agenda - Wednesday, March 8th, 2023

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