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Large optical anisotropy over a wide spectral range is crucial for effective light control in many photonic devices. This creates a growing need for natural materials with giant anisotropy (Δn > 1) to meet both scientific and industrial demands.
Bulk transition-metal dichalcogenides (TMDCs) are highly promising in this regard due to their intrinsically anisotropic van der Waals (vdW) layered structures, which naturally produce strong intrinsic birefringence.
In our study, we trained an ALIGNN graph neural network to predict birefringence using only crystal structures and elemental compositions (Figure 1). To enable this, we collected a database of known layered vdW materials with crystal structures and optical properties calculated via density functional theory (DFT), supplemented with experimental data for a subset of samples.
We then screened crystalline materials databases (MaterialsProject and GNoME) and identified new candidate materials with high optical anisotropy. Subsequent DFT calculations and experimental measurements validated these predictions, demonstrating the effectiveness of our approach in discovering novel anisotropic materials [L. Bereznikova et al., Materials Horizons, 2025].

Although the global graphene industry is continuing to grow and deliver new real-world products, without an understanding of the properties of the materials available in the supply chain these new applications cannot be efficiently developed and improved. Thus, there is a need for reliable, accurate and precise measurements for material testing, which are standardised across the industry and therefore allow end-users to be able to compare commercially-available materials from around the world.
To this end, the underlying metrology (measurement science) enabling industry and directly leading to international standards will be discussed. The current state of international measurement standards within ISO/IEC, covering the material properties of the graphene family, will be detailed.
A key part of developing international measurement standards is the validation of protocols through international interlaboratory comparisons. As examples, the results of interlaboratory studies for Raman spectroscopy and transmission electron microscopy of chemical vapour deposition (CVD) grown graphene will be reported, which gathered data from more than a dozen participants across academia, industry (including instrument manufacturers) and National laboratories for each study, revealing key metrology issues in both the measurement and data analysis that must be considered.
Alongside international standards, industry also require rapid, inexpensive and simple techniques to be used as quality control tools. These techniques need to be verified against more accurate and precise measurements, but at the same time do not need the same level of precision themselves. Several techniques and methods developed for industry will be described, such as Nuclear Magnetic Resonance Proton Relaxation.

Nearly every corner of America’s economy is racing to find solutions to numerous existential threats, including extreme weather, degradation of water resources, ubiquitous cyberattacks, unsustainable energy costs, and geopolitical friction resulting in uncertain and insecure supply chains. At the same time, trusted business leaders, including Warren Buffett, are speaking out about the need to leverage our technological innovation to shore up America’s global leadership. Graphene-related products and services have emerged as leading elements in tackling these challenges -both the short-term problems we must solve before it is too late, and the long-term restoration of our global image, reputation, and position.

Graphene field-effect transistors (GFETs) are emerging as a powerful platform for biomedical sensing, providing ultra-sensitive, label-free, and real-time detection of molecular biomarkers. Their compatibility with flexible substrates further enables integration into wearable and implantable electronic systems, advancing continuous and minimally invasive health monitoring technologies.

Recent developments demonstrate that coupling GFET sensor outputs with artificial intelligence (AI) and machine learning algorithms can significantly enhance performance. By analyzing the complex, multidimensional data generated by GFETs, AI models can reduce signal variability, suppress noise, and improve diagnostic accuracy.

This presentation will discuss recent progress in GFET-based biosensing, focusing on fabrication strategies, signal transduction mechanisms, and data-driven analysis methods. The integration of graphene nanoelectronics, flexible device engineering, and AI-assisted signal processing will be examined as a pathway toward scalable, high-precision platforms for next-generation point-of-care and continuous monitoring applications.

AM enables the design of 3D electrodes with larger active surface areas, improving electrochemical performance beyond conventional methods. Graphene are highlighted for its electronic properties, and sustainable origin, but suitable feedstocks for AM remain limited. The work presented develops metal free conductive filaments for material thermal extrusion (MTE), using PLA composites with 15 vol% colloidal graphene. Surface modification improves dispersion and bonding, orienting the inorganic phase during printing. These filaments were characterized for thermal, mechanical, and electrical behaviour, and then used to print complex electrodes. The resulting electrodes showed enhanced electrochemical properties, with tailored microstructures that increased conduction paths and achieved high electrical conductivity (>1000 S·m⁻¹). Beyond electrochemical storage, graphene based composites fabricated by AM can be used in applications where conductivity and mechanical flexibility are critical. The integration of graphene into AM feedstocks not only advances electrochemical devices but also opens pathways toward multifunctional materials across healthcare, energy, and industrial technologies. During the presentation performance of graphene in printed devices will be described.

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