Röthlisberger, Professor of Computational Chemistry and Biochemistry at EPFL, has been recognized for pioneering contributions to ab initio molecular dynamics and quantum mechanical/molecular mechanical, or QM/MM, simulation methods. These approaches allow researchers to study chemical systems by combining highly accurate quantum-mechanical calculations with larger-scale molecular models. The result is a powerful computational framework for examining molecular reactions and materials whose complexity would be impossible to capture using a single modeling technique.

“I am deeply honored to receive this award, which bears the name of one of my long-time mentors and most inspiring role models,” Röthlisberger said. “To me, this distinction represents far more than personal recognition—it is a wonderful affirmation of the scientific contributions that I have been privileged to make, together with outstanding students, postdoctoral researchers, collaborators, and colleagues, throughout my career.”

Established by MDPI in 2025, the Michele Parrinello Award commemorates the scientific legacy of Professor Michele Parrinello, whose work transformed atomistic simulation and molecular dynamics. The award carries a prize of 50,000 euros and is intended to recognize researchers whose discoveries have produced lasting advances in computational science. Parrinello’s influence is particularly evident in methods that enable scientists to predict how atoms move, bonds form and break, and complex molecular structures change over time.

Röthlisberger’s research has helped extend these computational tools to problems spanning quantum chemistry, molecular biology, materials science, and sustainable energy. In QM/MM simulations, the chemically active region of a system—such as a reaction site, catalytic center, or biological active site—is treated using quantum mechanics, while the surrounding environment is represented with a less computationally demanding molecular-mechanics model. This multiscale strategy makes it possible to investigate realistic systems containing thousands of atoms without sacrificing a detailed description of the chemistry taking place at the center.

A major focus of her recent work has been the computational design and analysis of photovoltaic materials. Working with experimental researchers around the world, Röthlisberger has investigated the mechanisms governing dye-sensitized solar cells and perovskite solar cells. Her simulations have provided insight into how light is absorbed, how electrons and positive charge carriers move through a material, and how structural defects or chemical reactions can limit device performance. Such information can help researchers design solar cells that are more efficient, durable, and environmentally sustainable.

Perovskite solar cells have attracted intense scientific interest because they can be manufactured using relatively low-temperature processes and have achieved remarkable improvements in efficiency in a short period. However, their long-term stability and sensitivity to moisture, heat, light, and structural imperfections remain major challenges. Computational chemistry can reveal atomic-scale degradation pathways that are difficult to observe directly, allowing experimental teams to test targeted strategies for protecting the materials and extending their operating lifetimes.

Professor Xin-Gao Gong, chair of the Michele Parrinello Award Committee, described Röthlisberger as an exceptional leader in computational chemistry and molecular simulation. “Her innovative research has significantly advanced the predictive modeling of complex chemical and biological systems and has created lasting impact across multiple scientific disciplines,” Gong said. He added that her scientific achievements, commitment to education, and leadership in the international research community have contributed significantly to the development of modern computational science.

The award adds to Röthlisberger’s international distinctions. She is an elected Fellow of the American Association for the Advancement of Science, a member of the International Academy of Quantum Molecular Science, and a recipient of the Dirac Medal from the World Association of Theoretical and Computational Chemists and the Ruzicka Prize. Through the Michele Parrinello Award, MDPI is highlighting not only an individual career but also the growing role of simulation in solving urgent scientific problems. As computational methods become more accurate and increasingly connected to laboratory experiments, they are turning previously invisible molecular events into actionable knowledge for energy, biology, and materials innovation.

Subject of Research: Computational chemistry, molecular simulation, quantum mechanical/molecular mechanical methods, photovoltaic materials, and sustainable energy.

Web References: MDPI; Michele Parrinello Award

Image Credits: MDPI

Keywords

Ursula Röthlisberger, Michele Parrinello Award, MDPI, computational chemistry, molecular simulation, quantum chemistry, QM/MM, ab initio molecular dynamics, perovskite solar cells, dye-sensitized solar cells, photovoltaic materials, sustainable energy, materials science, EPFL

The laboratory will be built around Georgia Tech’s Advanced Manufacturing Pilot Facility, a mixed-use research center operated through the Georgia Tech Manufacturing Institute. The facility houses equipment for materials development, manufacturing, testing, and scale-up. Through the cloud laboratory, researchers will be able to submit experimental goals remotely, receive recommendations from AI systems, and obtain data from physical experiments without traveling to the facility or becoming experts in every machine involved.

Materials research traditionally proceeds through a slow cycle of sample preparation, experimentation, analysis, and redesign. Each iteration can require expensive equipment, specialized personnel, and substantial time. The new system is intended to shorten that cycle by linking computational simulations with automated physical experiments. Researchers could pose a question about a material, while AI agents identify possible compositions or processing conditions, select appropriate equipment, organize the experiment, and return results for the next round of analysis.

The system will function as a kind of self-driving research environment. Georgia Tech currently has autonomous workflow capabilities across approximately 38 pieces of equipment at the Advanced Manufacturing Pilot Facility. The project aims to expand automation and autonomous operation to more than 100 of the facility’s 160 machines. Robotic systems will move samples between stations, operate manufacturing and testing equipment, and coordinate the sequence of actions required to complete a research workflow.

Researchers will not need to specify every mechanical instruction. Instead, they may provide a high-level experimental “recipe,” such as producing a material with a particular strength, conductivity, or heat resistance. AI agents will translate that objective into a detailed series of manufacturing, testing, and analysis steps. The system will then determine which machines and robots are needed, schedule their use, and manage the flow of materials and information throughout the facility.

Digital twins will provide another layer of control. These virtual models of the laboratory and its equipment can be used to simulate workflows before they are performed in the physical facility. By testing a proposed sequence digitally, researchers and AI systems may identify conflicts, inefficient machine settings, or safety concerns in advance. Data from completed experiments can then be used to update the digital models, allowing the laboratory to learn from previous runs and improve future operations.

The project will also connect materials discovery with real-world manufacturing. Georgia Tech is integrating Duke University’s Automatic FLOW for Materials Discovery platform, led by materials scientist Stefano Curtarolo, to link computational predictions with laboratory experiments. Contextualize, led by founder and CEO Branden Kappes, will provide a data platform connecting researchers, instruments, information systems, and equipment across the distributed network. Georgia Tech AI will contribute additional expertise in artificial intelligence and machine learning.

The cloud laboratory is part of a broader NSF initiative to establish a national network of 20 AI-enabled cloud laboratories. In the long term, these facilities are expected to share capabilities and workflows, allowing researchers to combine resources located at different institutions. A scientist studying a new alloy, semiconductor, battery material, or biomedical substance could potentially use computational tools at one site, manufacturing equipment at another, and specialized testing infrastructure at a third location through a connected digital system.

Georgia Tech expects the laboratory to serve more than 400 users from approximately 150 academic, industrial, and government institutions, with more than half participating remotely. The model could be particularly valuable to startups and university groups that lack access to industrial-scale equipment. It may also help companies test emerging technologies without interrupting active production lines. By providing a controlled environment for manufacturing demonstrations and performance testing, the facility could reduce the technical and financial risks associated with adopting unproven materials or processes.

The initiative reflects a growing shift toward autonomous experimentation, in which artificial intelligence does more than analyze scientific data. AI systems are increasingly being designed to plan experiments, control laboratory instruments, interpret results, and choose the next test in a continuous feedback loop. If Georgia Tech’s cloud laboratory reaches its intended scale, researchers may be able to move from a materials concept to a validated manufacturing process with fewer delays and less trial-and-error. The result could be a faster path to technologies needed for advanced electronics, clean energy, infrastructure, medicine, and national security.

Subject of Research: AI-enabled autonomous experimentation, advanced manufacturing, materials discovery, robotics, digital twins, and remote-access laboratory infrastructure

Article Title: Georgia Tech to Lead National Cloud Laboratory That Could Transform Materials Discovery

Web References: https://ampf.research.gatech.edu/ ; https://manufacturing.gatech.edu/ ; https://www.nsf.gov/tip/updates/nsf-announces-400m-investment-new-national-network-ai ; https://www.ai4opt.org/ ; https://ai.gatech.edu/

Image Credits: Georgia Institute of Technology

Keywords

Materials engineering, artificial intelligence, materials science, autonomous experimentation, advanced manufacturing, manufacturing equipment, robotics, digital twins, cloud laboratory, manufacturing industry

Schwarzites are named after Hermann Schwarz, the 19th-century German mathematician who first described these intriguing periodic minimal surfaces characterized by intricate curvature and large surface area combined with remarkably low density. Despite their appealing mathematical elegance and theoretical allure, the physical synthesis of schwarzites has proven elusive. Unlike more familiar carbon nanostructures such as graphene and carbon nanotubes, schwarzites feature a complex arrangement of polygons that create a saddle-shaped, negatively curved surface. This inherent geometric complexity has posed a formidable challenge to chemists attempting to assemble such structures from sp²-hybridized carbon atoms.

Professor Würthner’s team has developed an innovative supramolecular approach to tackle this challenge, leveraging the unique properties of nanographene molecules incorporating heptagonal rings. Whereas standard graphene is composed purely of hexagonal carbon rings generating flat sheets, the introduction of heptagons induces curvature, creating the negative Gaussian curvature that is the hallmark of schwarzite structures. This method was recently demonstrated through assembling nanographene units around C60 fullerenes, achieving schwarzite-like arrangements exhibiting the targeted three-dimensional architecture.

A central element of this endeavor is the polymerization of these heptagon-containing nanographene building blocks into extended three-dimensional pi-conjugated frameworks. By advancing the synthetic sophistication of these components and fine-tuning their chemical environment, the research seeks to generate bulk schwarzite materials that embody the theorized electronic and mechanical properties. Such materials could offer exceptional electrical conductivity due to their fully delocalized electron systems spanning multiple dimensions, a feat unachieved by planar graphene or tubular nanotubes.

From a physical standpoint, schwarzites distinguish themselves through their unique topological electronic characteristics. Theorists predict that certain schwarzite lattices host Dirac cones—linear energy-momentum dispersions that are foundational to phenomena such as high electron mobility and exotic quantum phases of matter. If experimentally realized, these properties could unlock new physics and potential applications in quantum materials and electronic devices, positioning schwarzites as the next frontier for carbon-based nanotechnology.

The University of Würzburg’s Center for Nanosystems Chemistry, under Würthner’s leadership, is at the heart of this ambitious project. The center benefits from cutting-edge instrumentation and advanced facilities, courtesy of prior investments by the Free State of Bavaria. These resources will facilitate detailed characterization of newly synthesized schwarzites, ranging from structural analysis via electron microscopy to probing electronic behavior through spectroscopic methods. Understanding structure-property relationships in such novel materials is essential to harness their potential for practical applications.

This ERC-funded project represents Würthner’s second Advanced Grant, underscoring his position as a leading figure in organic and supramolecular chemistry. His earlier grant supported pioneering work in artificial photosynthesis, focusing on developing catalysts capable of splitting water molecules efficiently to produce clean hydrogen fuel. That success demonstrates his team’s capacity to address major scientific challenges by melding fundamental chemistry with visionary technological goals.

Würthner’s strategic approach integrates molecular design, supramolecular assembly, and polymer chemistry, pushing the boundary where synthetic chemistry meets materials science. By meticulously controlling the molecular architecture of nanographenes and their assembly into three-dimensional networks, the research aims to fabricate schwarzites with customizable properties. Such control over curvature and electronic conjugation could herald a new class of carbon materials tailored for specific applications in energy, filtration, and electronics.

The implications of successfully synthesizing schwarzites extend far beyond academic curiosity. Porous three-dimensional carbon frameworks with superior electrical conductivity and stability may revolutionize battery electrodes by enhancing charge transport and enabling faster ion diffusion. Similarly, their large internal surface area combined with tunable chemical functionality could make them ideal candidates for selective gas separation or water purification systems, addressing urgent environmental needs.

Yet, despite these exciting prospects, challenges remain immense. The synthetic routes to carefully incorporate heptagonal defects into extended carbon networks must be exquisitely precise to ensure desired curvature and connectivity. Additionally, ensuring the scalability and reproducibility of such complex materials will be crucial for transitioning from laboratory samples to practical technological components.

Professor Würthner’s vision exemplifies the synergy between mathematical theory and chemical innovation. By translating Schwarz’s 19th-century geometric abstractions into real, functional materials, this project blurs the boundary between abstract science and applicative technology. The successful realization of schwarzite materials would not only validate decades of theoretical predictions but also open transformative pathways in nanomaterial design and functional carbon architectures.

As the SCHWARZITE project unfolds over the coming five years, the scientific community will keenly watch Würthner’s progress. With robust ERC funding and a pioneering research team, the prospects for overcoming longstanding obstacles to schwarzite synthesis have never looked more promising. This work heralds a new era in carbon nanomaterials, potentially reshaping technologies across sectors from sustainable energy to environmental remediation.

In sum, Professor Frank Würthner’s ERC-funded pursuit of schwarzite carbon materials epitomizes cutting-edge research at the interface of chemistry, physics, and materials science. Harnessing molecular design and supramolecular chemistry, his project aspires to manifest exotic carbon allotropes long confined to mathematical theory into the tangible realm of high-performance nanomaterials. Their realization would mark a milestone in carbon materials science, paving the way for unprecedented technological innovations.

Subject of Research:
Synthesis and characterization of schwarzite carbon nanomaterials through supramolecular chemistry approaches for advanced energy and filtration applications.

Article Title:
Professor Frank Würthner’s Quest to Synthesize Schwarzite Carbon Nanostructures Powered by ERC Advanced Grant

News Publication Date:
Not provided

Web References:
https://mediasvc.eurekalert.org/Api/v1/Multimedia/43b03666-166c-477c-949e-8eb612c9e6af/Rendition/low-res/Content/Public

Image Credits:
Christoph Weiss / University of Würzburg

Keywords

Supramolecular chemistry, Nanostructures, Carbon allotropes

A recent study led by researchers at Peking University highlights the profound effects of varying intercalation ratios on the atomic ordering and intrinsic properties of iron selenide (Fe1+xSe2). The work published in the prestigious journal National Science Review outlined compelling methodologies, synthesizing a series of nanoflakes with different intercalation ratios. It demonstrated how even slight changes in concentration impact the ordering of atomic structures, from disordered to half-ordered and fully ordered forms, profoundly influencing the accompanying electrical and magnetic attributes.

At the core of the study lies the principle of self-intercalation, wherein additional Fe atoms are strategically inserted into the van der Waals gaps of TMDs. This technique is not only a method for creating new materials but also unlocks new properties while retaining the advantageous traits of the parent material. The research has uncovered a systematic approach to intercalation, establishing a general rule that governs the relationships between intercalation ratios, atomic structures, and magnetic behaviors.

In the experiments conducted, scientists created nanoflakes of varying compositions of Fe1+xSe2, encompassing a range of intercalated forms from Fe1.18Se2 as disordered, through Fe1.25Se2, and into ordered structures like Fe1.75Se2. The breakthrough method employed was a space confinement-assisted chemical potential regulation strategy, which afforded precise control over intercalation levels. This innovation not only guarantees the successful synthesis of different structural types but also addresses the broader issue of controlling properties through design.

The aberration-corrected scanning transmission electron microscopy (STEM) provided critical insights into the atomic configurations formed through varying intercalation ratios. With the imaging capabilities at their disposal, the researchers confirmed the structural transitions and established the correlation between intercalation ratio and atomic order, setting the stage for subsequent inquiries into magnetism and electronic conductivity.

Notably, the results revealed that the synthesized materials showcased remarkable changes in magnetic properties contingent on their intercalation states. While the disordered form (Fe1.18Se2) was found to be nonmagnetic, the ordered versions exhibited robust room-temperature magnetic ordering. This transformation can be attributed to the charge transfer dynamics involving the intercalated Fe atoms, suggesting that careful manipulation of intercalation can lead to desired magnetic characteristics.

The research further elucidated on the phenomenon of magnetic structure transitions, which evolved from single-domain states to multi-domain configurations as the intercalation ratio was incrementally increased. One particularly striking outcome was the emergence of room-temperature magnetic half-metals, which exhibited favorable magnetoresistance behaviors. Specifically, Fe1.5Se2 displayed a crossover from negative to positive magnetoresistance below saturation fields with decreasing temperatures, showcasing the complex interplay between atomic structure and electron transport.

In summary, the findings from this study illuminate how self-intercalation can serve as a powerful tool in the design and synthesis of new materials with tunable properties. By controlling the intercalation ratios, it is possible to tailor both structural and magnetic characteristics, which presents a promising avenue for future research and applications in electronics and spintronics.

As scientists continue to explore the depths of material manipulation, this study lays a significant cornerstone for understanding how atomic-level changes can revolutionize the design of next-generation materials. With the allure of discovering novel intercalated structures and their corresponding properties, the potential applications extend across a plethora of fields, opening an exciting chapter in material science.

The opportunities that arise from understanding the relationships between structure and property in intercalated TMDs are boundless. The established intercalation rule serves as a guiding principle for researchers aiming to create materials with desired properties tailored for specific applications. This work not only enhances fundamental knowledge but also stimulates future pursuits in functional material development.

In conclusion, the work conducted by researchers from Peking University underscores the importance of innovative strategies in material science. By exploiting the properties of intercalated materials, scientists are not just creating new composites, but are also ushering in a new era of exploration in 2D materials that can potentially transform industries reliant on advanced electronic and magnetic materials.

The progress made in the study of intercalated transition metal dichalcogenides affirms the immense potential resting at the intersection of chemistry, materials science, and physics. As ongoing research delves further into this fascinating area, the landscape of functional materials will continue to expand, revealing new capabilities that push the boundaries of current technology.

The implications of this research extend far beyond academic interest; they hint at future innovations in technology that may enhance daily life through improved electronic devices and magnetic applications. As we advance, the technical achievements and new methodologies developed here will undoubtedly inspire further exploration into the diverse realm of materials science.

Subject of Research: The impact of intercalation ratios on the atomic structure and physical properties of Fe1+xSe2.
Article Title: The evolution of chemical ordering and property in Fe1+xSe2 upon intercalation ratios.
News Publication Date: Not specified.
Web References: 10.1093/nsr/nwae430.
References: None provided.
Image Credits: ©Science China Press.

Keywords

Self-intercalation, Transition Metal Dichalcogenides, Magnetic Properties, Electrical Properties, Nanoflakes, Atomic Structure, Chemical Ordering.