ScholarWorks

ScholarWorks is an open access repository for the capture of the intellectual work of Montana State University (MSU) in support of its teaching, research and service missions. MSU ScholarWorks is a central point of discovery for accessing, collecting, sharing, preserving, and distributing knowledge to the Montana State University community and the world.

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A collection of archaeal 16S rRNA Clone-FISH cultures for probe validation in fluorescence in situ hybridization experiments
(American Society for Microbiology, 2025-11)
van Beek, J. M.
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De Robles, Gabriela
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Blaby, Ian K.
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Hatzenpichler, Roland
We present a collection of 30 Escherichia coli cultures (Clone-FISH cultures), each carrying a plasmid for the heterologous expression of a (near) full-length 16S rRNA gene from 1 of 30 lineages of archaea, including 17 yet uncultured ones. We make these clones available for use as controls in fluorescence in situ hybridization experiments.
Cultivation of Methanonezhaarchaeia, the third class of methanogens within the phylum Thermoproteota
(American Association for the Advancement of Science, 2025-12)
Kohtz, Anthony J.
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Nupp, Sylvia
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Hatzenpichler, Roland
Methane is a potent greenhouse gas, largely produced by methanogenic archaea, contributing to Earth’s dynamic climate and biogeochemical cycles. In the past decade, metagenomics revealed that lineages outside of the Euryarchaeota superphylum encode genes for methanogenesis. This was recently confirmed through the cultivation of two classes of methanogenic Thermoproteota. Thus far, all methanogens within the Thermoproteota are predicted or were shown to be methylotrophic. The only exception to this are the Nezhaarchaea, for which metagenomic predictions suggest they are CO 2 -reducing methanogens. Here, we demonstrate methanogenic activity in a third class of Thermoproteota, the Methanonezhaarchaeia. Contrary to genomic predictions for this class, we cultivated a methylotrophic species, Candidatus Methanonezhaarchaeum fastidiosum YNP3N, highlighting the importance of testing metagenomic hypotheses through experimentation. We investigate the metabolic diversity of Methanonezhaarchaeia, including metabolic modifications accompanying frequent loss of methanogenesis in this class. This highlights gaps in our understanding of the biochemistry, diversity, and evolution of thermoproteotal methanogens and their contributions to carbon cycling.
Photoreactive Capture and Conversion of Dilute Carbon Dioxide into Synthetic Natural Gas
(American Chemical Society, 2025-09)
Halingstad, Sawyer
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Leick, Noémi
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Huang, Zhe
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Crawford, James M.
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Carroll, Gerard M.
This study introduces a photoreactive system that integrates the capture of dilute CO2 streams with their catalytic conversion to synthetic natural gas (CH4), utilizing a Ru nanoparticle (NP)-doped TiO2 composite loaded with linear polyethylenimine (L-PEI) and enhanced with plasmonic titanium nitride (TiN). This light-driven approach mitigates challenges that have plagued traditional thermal reactive carbon capture (RCC) methods, such as CO2 slip and amine degradation. We demonstrate that L-PEI enables stable CO2 capture and conversion, achieving ∼70% conversion of captured CO2 to CH4 across multiple reaction cycles using nonflammable forming gas (∼5% H2) as the reductant. In contrast, branched PEI (B-PEI)-loaded composites exhibited significant catalyst deactivation after several RCC cycles. Scanning transmission electron microscopy (STEM) imaging confirms that significant sintering of the Ru NPs occur in the B-PEI sample under RCC conditions, whereas their size remains stable in more rigid L-PEI composites. Technoeconomic analysis (TEA) estimates that CH4 production using this system could cost less than $5/kg based on current electrocatalytic H2 prices. These results represent one of the most promising demonstrations of amine-based RCC employing dilute CO2 sources to date.
Application of Solid-Supported Amines for Thermocatalytic Reactive CO2 Capture
(American Chemical Society, 2025-01)
McNeary, W. Wilson
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Ellebracht, Nathan C.
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Jue, Melinda L.
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Rasmussen, Matthew J.
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Crawford, James M.
Reactive CO2 capture (RCC) is a promising strategy for process intensification of carbon capture and conversion for production of low-carbon fuels and chemicals. As state-of-the-art sorbent materials in point source and direct air capture systems, solid-supported amines are a natural choice to pair with supported CO2 hydrogenation catalysts (e.g., metallic nanoparticles) for developing high-capacity sorbent-catalyst materials for use in RCC. In this Perspective, we summarize the relevant literature combining solid-supported amines with metallic nanoparticles for thermocatalytic RCC and detail two of our own case studies using RCC to synthesize methane and methanol. Our observations suggest that the temperature mismatch between CO2 desorption and reaction, along with potential catalyst site poisoning by grafted aminosilanes, is a significant obstacle to realizing the potential of amine-based RCC materials in the decarbonization of chemical production. This stands in contrast to literature detailing successful RCC using liquid amines and solid catalysts, which may benefit from more favorable mass transfer dynamics, as well as early stage reports into RCC solid-phase amine-Pd materials, whose findings we were not able to replicate. More judicious reaction selection and synthetic design strategies to match materials with process conditions offer alternative pathways for future research.
Integrating Computational Text Analysis into Risk and Crisis Communication Development
(IEEE, 2025-08)
Munro, Madison
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Ruiz-Aravena, Manuel
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Shanahan, Elizabeth A.
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Washburn, Savanna
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Reinhold, Ann Marie
Qualitative textual analysis is advancing with the integration of Natural Language Processing (NLP) and Large Language Models (LLMs). Although many multidisciplinary researchers adopt these analysis tools, Risk and Crisis Communication (RCC) researchers have not taken full advantage of such tools in content analysis tasks. We investigate computational tools' ability to replicate human analysis in RCC research. We integrate NLP and ChatGPT into content analysis steps performed on insider threat source text. The first content analysis step tasks ChatGPT with coding insider threat text as character types defined by the Narrative Policy Framework (NPF), and the second step leverages select NLP tools to derive meaning in the coded sentences. Content coding with ChatGPT varies in performance based on the amount of detail present in prompts. Select NLP tools have varying degrees of success when processing and analyzing coded text. Both ChatGPT and NLP require human intervention when performing content analysis, thus a mixed method approach is necessary for future RCC research.