Research

A central focus of the Terlier Research Group is the development of operando and in situ Secondary Ion Mass Spectrometry (SIMS) methodologies capable of probing materials and interfaces under active reaction conditions. While conventional SIMS is largely limited to ex situ analysis, the group advances custom experimental platforms that enable real-time control of multiple external stimuli during SIMS measurements.

Key efforts include the design and fabrication of electrochemical cells compatible with SIMS, allowing in situ electrical biasing to investigate electrochemical reactions such as ion transport, interfacial redox processes, degradation mechanisms, and reaction intermediates in batteries, catalysts, and functional interfaces. In parallel, the group develops temperature-controlled environments for studying thermally driven reactions, phase transformations, diffusion phenomena, and kinetic processes.

Beyond electrical and thermal stimuli, the group has strong interests in integrating light excitation and gas activation into operando SIMS workflows. Light-driven SIMS measurements are pursued to probe photoinduced charge transfer, photochemical reactions, and excited-state dynamics in semiconductors, photocatalysts, and optoelectronic materials. Gas activation strategies, including controlled exposure to reactive or inert gas environments, enable investigation of gas-solid interactions, adsorption/desorption processes, surface reactions, and plasma-relevant chemistries under well-defined conditions.

By combining SIMS with electrical biasing, temperature control, light excitation, and gas activation, the Terlier Research Group aims to establish comprehensive structure/chemistry/function relationships under realistic operating environments. These developments are closely tied to student-led platform design and instrumentation innovation, reinforcing the group’s commitment to training researchers capable of pushing operando surface analysis beyond established boundaries.

The group advances multimodal and correlative imaging strategies that integrate Time-of-Flight SIMS with Scanning Probe Microscopy (SPM) to achieve comprehensive nanoscale characterization. This approach combines chemical specificity with high-resolution structural, mechanical, electrical, and magnetic information.

Research activities include the development of 2D and 3D correlative workflows that link ToF-SIMS chemical maps and depth profiles with advanced SPM modalities such as Electrostatic Force Microscopy (EFM), Magnetic Force Microscopy (MFM), Kelvin Probe Force Microscopy (KPFM), and Force–distance curve spectroscopy. These combined measurements enable direct correlation between chemistry, morphology, local electrical behavior, and mechanical response.

The group places particular emphasis on data registration, quantitative correlation, and uncertainty management across modalities, enabling robust interpretation of heterogeneous and hierarchical materials. Applications span polymers, hybrid and composite materials, energy storage systems, electronic materials, and biointerfaces.

The Terlier Research Group develops artificial intelligence- and data-driven strategies to address the increasing dimensionality, scale, and complexity of modern SIMS datasets. A core emphasis is placed on transforming SIMS from a single-sample, expert-driven technique into a high-throughput, multiplexed analytical platform capable of interrogating large and chemically diverse sample sets within a single experiment.

A central research direction involves microarray-based multiplexing combined with large-area hyperspectral ToF-SIMS imaging. By engineering patterned substrates containing arrays of microscale wells, multiple distinct samples can be analyzed simultaneously. In large-area imaging mode, ToF-SIMS acquires hyperspectral datasets spanning several square millimeters, where each pixel contains a full mass spectrum. Regions of interest corresponding to individual microwells are computationally isolated, enabling parallel chemical analysis across dozens to hundreds of samples from a single measurement.

To extract meaningful chemical information from these high-dimensional datasets, the group integrates multivariate analysis (MVA), machine learning, and image recognition approaches. These tools are used to identify characteristic fragment ions, classify molecular signatures, and reveal relationships among samples based on their chemical fingerprints. Such workflows enable rapid discrimination of compounds, functional groups, and compositional trends that would be impractical to assess using conventional, sample-by-sample SIMS analysis.

This AI-enabled framework supports the creation of reference databases and spectral libraries for database matching, compositional quantification, and automated classification of unknown materials. Ongoing research explores extending these methods toward mixture analysis by evaluating species-specific ion intensities, as well as translating chemical mapping strategies into biologically and clinically relevant imaging workflows.

Overall, this thematic area aims to convert hyperspectral SIMS data into structured, interpretable, and actionable information. By combining multiplexed experimental design with robust data analytics, the Terlier Research Group advances SIMS as a scalable platform for studying complex systems, reaction pathways, and chemically heterogeneous materials, while training students at the interface of surface science, data science, and analytical chemistry.

As Lead Project Engineer for the Woodside-Rice Decarbonization Accelerator team, Dr. Terlier investigates plasma-assisted catalytic pathways as enabling technologies for decarbonization, sustainable chemical manufacturing, and advanced materials processing. By leveraging non-equilibrium plasma environments, this research explores reaction routes that are difficult or inefficient to access using conventional thermochemical approaches.

A primary focus is the integration of plasma chemistry to elucidate plasma-surface interactions, transient reaction intermediates, and catalyst evolution under operating conditions. Operando and in situ analytical strategies are employed to establish structure/chemistry/reactivity relationships that govern catalytic activity, selectivity, and long-term stability.

Beyond carbon conversion, the group actively explores plasma-enabled synthetic fuel production, including pathways for CO₂ conversion and hydrocarbon synthesis driven by activated gas-phase species. These efforts aim to reduce energy barriers and improve selectivity toward value-added fuels and chemical feedstocks under mild conditions.

The research program also addresses critical materials and supply-chain challenges, including plasma-assisted refining of critical minerals and metals. Specific interests include the development of rare-earth free (REE-free) magnetic materials, plasma-based separation and purification strategies, and alternative processing routes that reduce environmental impact compared to conventional metallurgical techniques.

In parallel, the group investigates plasma-driven nitrogen chemistry, targeting sustainable routes for nitrogen activation, ammonia synthesis, and nitrogen-containing chemical intermediates. By combining plasma catalysis with advanced surface analysis, these studies aim to clarify reaction mechanisms and identify material design principles for improved nitrogen fixation processes.

Collectively, this thematic area seeks to position plasma catalysis as a versatile platform for decarbonization, synthetic fuel production, critical mineral refining, and sustainable chemical synthesis. Through close coupling of plasma reactors, operando characterization, and data-driven analysis, the WRDA team advances both fundamental understanding and applied solutions to energy and materials challenges, while providing students with hands-on experience at the intersection of plasma science, catalysis, and advanced surface analytics.