Q: What initially drew you to the APS?

Tamas: My first exposure to the APS goes back to my graduate school years at Georgia Tech, when I joined a research group that regularly conducted synchrotron experiments. Seeing the facility's scale and the ambition of the science being conducted there made a strong impression.

My earliest involvement was hands-on and practical, supporting beamline operations and learning how experiments were set up. That experience sparked a lasting interest in synchrotron science and made it clear that this was a place where important questions could be addressed in ways that weren’t possible elsewhere.

As my research matured, the APS remained central to my thinking. Whether as a user or a collaborator, it was clear early on that synchrotron-based techniques would play an important role in the kinds of scientific problems I wanted to pursue.

Q: Can you describe the research you’ve conducted at the APS? 

Tamas: My work at the APS has evolved alongside my career and spans multiple research areas. Earlier in my work as a materials scientist, I focused on multiferroic materials, which are systems that exhibit both ferroelectric and magnetic properties. Using APS beamlines, I studied thin films to confirm phase stability and understand how subtle differences in atomic structure influenced material behavior.

These studies relied on X-ray spectroscopy and magnetic measurements to demonstrate the coexistence of ferroelectric and ferromagnetic properties in engineered films. That work addressed questions that could not be answered using laboratory-based techniques alone.

More recently, my focus has shifted toward environmental science. Since returning to the APS in 2018, I’ve used fluorescence imaging, X-ray absorption spectroscopy, and micro-computed tomography to study soil and plant systems. This work now feeds into a broader collaboration that integrates APS measurements into a standardized, open database of soil properties collected from across the United States.

Q: What role did the APS play in enabling or advancing your work? 

Tamas: In each phase of my research, the APS provided capabilities that were not available in conventional laboratory settings. In my materials science work, synchrotron-based spectroscopy was essential for resolving local atomic environments and magnetic behavior that could not be captured with standard diffraction methods.

In my current environmental research, the APS plays an equally critical role. High-resolution micro-CT and sensitive X-ray spectroscopy allow us to examine soil structure and chemistry at scales that connect laboratory measurements with field observations. These techniques provide insight into pore networks, mineral phases, and elemental interactions that are central to understanding soil behavior.

Across very different scientific questions, the APS consistently enabled measurements that moved projects forward by adding resolution, sensitivity, and context.

Q: Has anything unexpected come out of your work with the APS, either in your results or in the process itself?

Tamas: One memorable experience occurred during early work with fluorescence tomography on soil aggregates. Producing three-dimensional chemical maps at high resolution required extremely long measurement times, sometimes stretching over a full day for a single sample.

Even at a facility as powerful as the APS, some measurements remain challenging. That experience underscored how demanding it can be to extract high-quality, three-dimensional chemical information.

It also highlighted how improvements in beam brightness and detector performance, such as those enabled by the APS upgrade, can significantly reduce acquisition times while preserving data quality.

Q: What impact has your research at the APS had on your work so far? What are you excited about exploring next?

Tamas: One of the most exciting developments in my current work is the collaboration between user facilities. By pairing APS measurements with complementary laboratory-based data, we’re building richer, more complete datasets than would be possible using any single facility alone.

Looking ahead, I’m particularly interested in how advances in computation, machine learning, and data integration can help extract more insight from the large, multimodal datasets generated at the APS. Techniques such as AI-aided image segmentation and automated spectral analysis are becoming essential for working at this scale.

As these tools mature, they will allow us to move beyond individual experiments toward broader, data-driven understanding, benefiting both individual research programs and the wider scientific community.