Jonathan Bean is the CEO & Co-Founding father of Supplies Nexus. With expertise spanning both theoretical and practical aspects of textile science, Jonathan quickly identified the opportunity to develop a novel materials modeling platform. During his tenure as a researcher at the University of Cambridge, he founded Supplies Nexus to expedite the distribution of cutting-edge supplies and mitigate the devastating impact of local weather disasters.
Jonathan’s PhD research at the University of York focused on developing superior modeling techniques for polycrystalline materials.
As a dual role holder, Jonathan serves as both a key figure at Supplies Nexus and a valued mentor through World Expertise Mentoring, while also participating in the esteemed Leaders in Innovation Fellowships program administered by the prestigious Royal Academy of Engineering. Additionally, he instructs Supply Chain Science for Engineers at Trinity College, Cambridge, and serves as a Visiting Fellow at London South Bank University.
Is a company leveraging AI to produce top-notch products faster than previously possible?
The ultimate limitation on what can be built lies in the materials and resources employed in its construction, which was the driving force behind my exploration of supply chain science. During my tenure at Cambridge University, I collaborated with my co-founder, Robert Forrest, whose shared vision drove our pivot towards developing machine learning algorithms. The foundation of Supplies Nexus’ technological expertise was laid through this experience.
This potential analysis could undoubtedly have a profound and optimistic impact on our planet, necessitating a swift acceleration of its adoption. The efficiency of products is limited by supply, as are our advancements towards a net-zero goal. What specifically caught our attention was the discovery of this innovative company.
As a driving force behind our organization, we are propelled by the urgent imperative to positively impact the world on three interconnected fronts: environmental sustainability, geopolitical stability, and ethical integrity. We aim to transform the supply chain industry by creating innovative products that balance escalating demands for both environmental sustainability and operational efficiency.
Through this identical approach, it also transforms materials discovery, refining what was once a trial-and-error-based methodology into an intentional design process. While pharmaceutical analysis presents its own set of challenges, the search for answers may require a broader range of chemical compounds across the entire periodic table. At Supplies Nexus, our scope extends across the entire materials spectrum, encompassing everything from the quantum realm to bulk materials – a comprehensive approach that goes beyond mere quantum mechanics-based composition prediction, as we also develop models for processing and synthesis methodologies. This permits us to not solely establish, but additionally bodily produce high-performance supplies precisely, in a matter of months reasonably than many years, considerably dashing up the R&D course of.
By leveraging AI for supply chain discovery, organizations can experience significant benefits, including accelerated search times, reduced costs, and environmentally sustainable practices. Our AI-powered platform efficiently processes vast datasets to accurately forecast material properties before laboratory testing, thereby streamlining the process and reducing waste by minimizing the need for costly, resource-heavy experiments. With our platform, previously time-consuming laboratory procedures could potentially be completed within just hours.
This finally unlocks a fresh set of options featuring concentrated resources: “Design” versus discovery. By incorporating customizable parameters such as CO2 emissions, cost, or weight, researchers can actively seek out compositions that meet specific requirements, effectively reversing the traditional “discovery” process.
By harnessing the power of artificial intelligence and machine learning, manufacturers gain access to a vast array of innovative materials through the development process. During the manufacturing process, the impact is twofold: firstly, it stems from the fundamental composition of raw materials, and secondly, from the specific conditions under which they are processed. AI supplies discovery can facilitate identifying and excluding specific areas of high environmental significance, for instance, Uncommon Earth elements may exhibit reduced partitioning into these minerals or scale back their compositional shares. As the technology continues to evolve, it can be used to have a glance at processing methods (for example, What are the specific temperatures, stresses, and impurity levels required to manufacture this fabric while implementing energy-efficient methods? The quality and quantity of raw materials used in fabric production can significantly impact initial emissions. Notwithstanding this, it’s crucial to acknowledge that environmental impact extends far beyond the realm of manufacturing exclusively. The application of superior supplies, each boasting exceptional efficiency or affordability, can have a profoundly positive secondary environmental impact by increasing accessibility to sustainable technologies, for instance. affordable electric vehicles), even more environmentally friendly (for instance, Higher-performing laptop chips designed specifically for AI-intensive applications, coupled with reduced toxicity in their end-of-life disposal methods, for instance? changing hydrofluorocarbons).
Prior to conducting a single experiment in the laboratory, our platform enabled us to computationally screen over 100 million hypothetical configurations of rare-earth-free magnets. Since progressing to the synthesis stage, our predictive models had accurately forecasted the composition’s properties.
The significance of this magnetic innovation extends far beyond its own creation, heralding a profound shift in material science that promises to revolutionize centuries-old practices. As our platform continues to evolve and become increasingly sophisticated, we can anticipate predicting compositions with greater ease and across multiple material spheres. With 10100 Compositions of elements on the periodic table, the possibilities are seemingly endless.
AI-powered materials discovery holds significant promise in establishing and developing diverse supplies for a wide range of applications beyond magnets.
Our goal on this occasion was to identify an alternative magnet composition devoid of rare-earth components; however, our machine learning-based search algorithms are designed to be applied to any material class without restriction. We’re developing a unified platform for designing common supplies.
Currently, our platform’s core capabilities focus on the development of innovative alloys and ceramics, with a specific emphasis on creating practical materials for applications in high-impact green technologies such as electrical motors, semiconductors, superconductors, and green hydrogen fuel cells.
Through partnerships with leading institutions like the Henry Royce Institute and the University of Sheffield, we gain access to cutting-edge facilities and expertise in advanced materials science. Through strategic partnerships, we accelerate the development and verification of our predictions.
Artificial intelligence-driven supplies discovery has the potential to revolutionize every materials class. At Supplies Nexus, our focus is on the most challenging and costly supplies that have the greatest potential for positive impact when improved. Numerous industries can be impacted by each trade, including power generation, aviation, high-performance computing, transportation systems, and many others. Within the power sector, AI may also aid in developing additional environmentally friendly and sustainable sources for battery and solar cell production. The rapid advancement in supercomputing may lead to the development of cutting-edge semiconductor technologies, thereby significantly enhancing data storage and processing capacities. By fostering rapid expansion in cutting-edge materials, artificial intelligence has the potential to propel revolutionary advancements and environmentally conscious practices across nearly every sector.
As we drive progress forward, our relentless pursuit of excellence will shatter conventional barriers, unlocking new possibilities that meet the demands of a rapidly evolving future. The long-run possibilities are virtually unlimited by human imagination.
