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Bacterial vesicles hold immense potential in various biomedical fields, including vaccines, antimicrobial agents, drug delivery systems, and cancer immunotherapy. Among these, outer membrane vesicles (OMVs) produced by Gram-negative bacteria are among the most extensively studied. While the exact mechanism of OMV production remains unclear, numerous environmental factors have been shown to influence both the yield and composition of OMVs. In this study, we investigated the effect of three different antimicrobial families on OMV production by E. coli. Interestingly, antimicrobials within the same family did not provide the same effects on OMV yield, suggesting that OMV production may not directly correlate with the antimicrobial mechanism of action.

OMVs have demonstrated tumor-inhibitory activity in multiple mouse tumor models. However, their potential toxicity poses a significant challenge, as OMVs have been shown to cause mortality in mice. To address this limitation, we developed bacterial-engineered vesicles (BEVs) as a safer alternative to OMVs. Proteomic analysis revealed that BEVs contained fewer outer membrane proteins compared to OMVs. In vitro assays, BEVs effectively repolarized pro-tumor macrophages (M2) to the anti-tumor phenotype (M1) and promoted dendritic cell maturation. Additionally, BEVs were shown to serve as a versatile platform for antigen peptide display, with the displayed peptides not interfering with BEVs' inherent immunomodulatory activity.

We further evaluated the anti-tumor efficacy of BEVs in a B16F10 melanoma model. The intravenous administration of BEVs significantly inhibited tumor growth and elicited robust immune responses. Flow cytometry analysis of spleen and lymph node samples from BEV-treated mice revealed an elevated M1/M2 macrophage ratio and an increased population of CD8+ T cells. To explore combination therapies, we generated cancer cell-derived vesicles (PD-1 CEVs) using PD-1-transfected B16F10 cells. Interestingly, while BEVs alone inhibited tumor growth effectively, the co-administration of BEVs and PD-1 CEVs resulted in comparable tumor suppression but attenuated immune responses. However, a significant decrease in regulatory T cell percentages was monitored among all vesicle-treated groups compared to the PBS control group. This unexpected immune modulation warrants further investigation to understand the mechanisms underlying PD-1 CEV-mediated immune suppression.

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Bacterial vesicles hold immense potential in various biomedical fields, including vaccines, antimicrobial agents, drug delivery systems, and cancer immunotherapy. Among these, outer membrane vesicles (OMVs) produced by Gram-negative bacteria are among the most extensively studied. While the exact mechanism of OMV production remains unclear, numerous environmental factors have been shown to influence both the yield and composition of OMVs. In this study, we investigated the effect of three different antimicrobial families on OMV production by E. coli. Interestingly, antimicrobials within the same family did not provide the same effects on OMV yield, suggesting that OMV production may not directly correlate with the antimicrobial mechanism of action.

OMVs have demonstrated tumor-inhibitory activity in multiple mouse tumor models. However, their potential toxicity poses a significant challenge, as OMVs have been shown to cause mortality in mice. To address this limitation, we developed bacterial-engineered vesicles (BEVs) as a safer alternative to OMVs. Proteomic analysis revealed that BEVs contained fewer outer membrane proteins compared to OMVs. In vitro assays, BEVs effectively repolarized pro-tumor macrophages (M2) to the anti-tumor phenotype (M1) and promoted dendritic cell maturation. Additionally, BEVs were shown to serve as a versatile platform for antigen peptide display, with the displayed peptides not interfering with BEVs' inherent immunomodulatory activity.

We further evaluated the anti-tumor efficacy of BEVs in a B16F10 melanoma model. The intravenous administration of BEVs significantly inhibited tumor growth and elicited robust immune responses. Flow cytometry analysis of spleen and lymph node samples from BEV-treated mice revealed an elevated M1/M2 macrophage ratio and an increased population of CD8+ T cells. To explore combination therapies, we generated cancer cell-derived vesicles (PD-1 CEVs) using PD-1-transfected B16F10 cells. Interestingly, while BEVs alone inhibited tumor growth effectively, the co-administration of BEVs and PD-1 CEVs resulted in comparable tumor suppression but attenuated immune responses. However, a significant decrease in regulatory T cell percentages was monitored among all vesicle-treated groups compared to the PBS control group. This unexpected immune modulation warrants further investigation to understand the mechanisms underlying PD-1 CEV-mediated immune suppression.

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Small molecule metal complexes have diverse applications including usage as catalysts, single molecule magnets, photosensitizers and pharmaceuticals. Nature itself frequently takes advantage of such complexes for fundamental biological processes. For example, heme-based iron complexes provide O₂ for cellular respiration, while the active site of carbonic anhydrase catalyzes the hydration of CO₂. Now it is our turn to define and exploit the chemical characteristics of such metal complexes. This body of work is specific to the development and application of novel aminated ligands that, when coordinated to various metal centers, can be used for an assortment of applications. The first research project in this work reports a new benzimidazole-based ligand, which dimerizes upon coordination to afford a trinuclear Cu(I) complex. Due to the linear geometry of the Cu(I) metal centers, paired with the strong nitrogen coordinating groups, the resulting complex is resistant to oxidation in both air and water, even in the presence of strong oxidants. The complex is shown to be efficient in the copper-catalyzed azide-alkyne cycloaddition (CuAAC) reaction and used to tag anticancer drug candidates in vitro. The complex is fully characterized, and a catalytic cycle is proposed. The next project focuses on a series of amidine-based ligands featuring chiral functional groups proximal to the coordinating site. In doing so, the reaction of achiral substrates may be influenced to promote the formation of one enantiomeric product over the other. The ligands are shown to be active in catalyzing the hydroxymethylation of silyl enol ethers in the presence of bismuth chloride in aqueous solutions. The reaction is optimized and yields are reported. In the final research project, Ni(II) dimer complexes are investigated for their magnetic behavior. For octahedral Ni(II) dimers bridged by a common anion, it has previously been established that the ferromagnetic superexchange between the Ni(II) metal centers can be enhanced as the angle of the bridging anion approaches 90 degrees. Novel imidazole and pyridine-based ligands are synthesized to add to the catalogue of chlorine-bridged complexes in the literature. Further, their bromine-bridged analogues are synthesized in order to determine the effect the identity of the halide bridge has on the magnetic properties of the complex. These three projects, while functionally different with individual aims, fundamentally share the goal of probing the chemical space that influences intrinsic properties of unique metal complexes.

Small molecule metal complexes have diverse applications including usage as catalysts, single molecule magnets, photosensitizers and pharmaceuticals. Nature itself frequently takes advantage of such complexes for fundamental biological processes. For example, heme-based iron complexes provide O₂ for cellular respiration, while the active site of carbonic anhydrase catalyzes the hydration of CO₂. Now it is our turn to define and exploit the chemical characteristics of such metal complexes. This body of work is specific to the development and application of novel aminated ligands that, when coordinated to various metal centers, can be used for an assortment of applications. The first research project in this work reports a new benzimidazole-based ligand, which dimerizes upon coordination to afford a trinuclear Cu(I) complex. Due to the linear geometry of the Cu(I) metal centers, paired with the strong nitrogen coordinating groups, the resulting complex is resistant to oxidation in both air and water, even in the presence of strong oxidants. The complex is shown to be efficient in the copper-catalyzed azide-alkyne cycloaddition (CuAAC) reaction and used to tag anticancer drug candidates in vitro. The complex is fully characterized, and a catalytic cycle is proposed. The next project focuses on a series of amidine-based ligands featuring chiral functional groups proximal to the coordinating site. In doing so, the reaction of achiral substrates may be influenced to promote the formation of one enantiomeric product over the other. The ligands are shown to be active in catalyzing the hydroxymethylation of silyl enol ethers in the presence of bismuth chloride in aqueous solutions. The reaction is optimized and yields are reported. In the final research project, Ni(II) dimer complexes are investigated for their magnetic behavior. For octahedral Ni(II) dimers bridged by a common anion, it has previously been established that the ferromagnetic superexchange between the Ni(II) metal centers can be enhanced as the angle of the bridging anion approaches 90 degrees. Novel imidazole and pyridine-based ligands are synthesized to add to the catalogue of chlorine-bridged complexes in the literature. Further, their bromine-bridged analogues are synthesized in order to determine the effect the identity of the halide bridge has on the magnetic properties of the complex. These three projects, while functionally different with individual aims, fundamentally share the goal of probing the chemical space that influences intrinsic properties of unique metal complexes.

Global CO₂ emissions from industrial, power generation and transportation sources has led to the call for increased implementation of carbon capture strategies. The most developed of these is point source carbon capture, which refers to the process of capturing CO₂ directly from large (point) source emitters, before the CO₂ is released into the atmosphere. The challenge becomes separating CO₂ from the other components of the emitted gas, mainly nitrogen. Therefore, these processes typically involve the use of aqueous solutions of amines to absorb (capture) CO₂ from the gas stream, where the CO₂ and the basic amine in water react to form a carbamate and/or bicarbonate, depending on the specific amine used. An advantage when using amine solutions is that this reaction is reversible, as the absorbed CO₂ is released when the solution is heated allowing the amine to be reused in multiple cycles of absorption and regeneration.

This type of amine-based carbon capture works well, but it is not without some drawbacks. The temperature swings needed for this desorption process not only requires significant energy input but can also lead to gradual degradation of the amine, commonly referred to as thermal degradation. This can lead to solvent losses, reduced performance, and higher operational costs. In addition, the solvent can degrade due to exposure to oxygen and other contaminants present in the gas (such as SO₂, NOx). This oxidative degradation can lead to the formation of unwanted byproducts, some of which are regulated volatile organic compounds. To avoid unintended environmental effects, the amine degradation pathways need to be carefully understood and managed. Amine degradation can produce a combination of different species generating a complex matrix that when coupled with the high pH environment, can make degradation remediation challenging. This dissertation focuses on the degradation by-products of amine solvents in carbon capture systems and how the chemical differences between the amine and water impacts the volatility and the removal of these degradation compounds. A better understanding of theses impacts allows for the development of mitigation strategies minimizing any environmental impacts.

Mitigation of the unwanted degradation byproducts is achieved by either removing the contaminants from the solvent or capturing and neutralizing them within the system. First, an assessment was performed to understand the effectiveness of activated carbon adsorption, with implications for treating high pH solutions. While there were some benefits to this methodology, activated carbon adsorption was not completely effective and presented several limitations such as metal leaching from the activated carbon material. Given this, it is necessary to expand into other areas of degradation mitigation. First understanding the potential for emissions of any degradation products, including compounds such as aldehydes, is crucial given their known environmental and human health hazards. These emissions may be impacted by the composition of the amine solvent used, therefore the Henry’s volatility coefficient of acetaldehyde in relevant amine solutions were determined as a surrogate for other classes of potential degradation compounds. The volatility was determined to be significantly higher from the amine solvent when compared to water, which is critical fundamental information in aiding the development of proper mitigation strategies that can be implemented within capture systems. 

Current engineering controls within CO₂ capture plants involve the use of water wash systems to reduce amine emissions, however some degradation products are also captured by this system which allows for their targeted neutralization. The composition of the wash-water poses yet another unique challenge as the complex matrix and increased the pH make it difficult to treat via traditional water treatment methods. An electrochemical-mediated treatment method was developed and evaluated to facilitate the decomposition of N-nitrosamines and aldehydes. The experimental results showed that even in the presence of this complex matrix, highly efficient decomposition of these hazardous compounds can be achieved.

Global CO₂ emissions from industrial, power generation and transportation sources has led to the call for increased implementation of carbon capture strategies. The most developed of these is point source carbon capture, which refers to the process of capturing CO₂ directly from large (point) source emitters, before the CO₂ is released into the atmosphere. The challenge becomes separating CO₂ from the other components of the emitted gas, mainly nitrogen. Therefore, these processes typically involve the use of aqueous solutions of amines to absorb (capture) CO₂ from the gas stream, where the CO₂ and the basic amine in water react to form a carbamate and/or bicarbonate, depending on the specific amine used. An advantage when using amine solutions is that this reaction is reversible, as the absorbed CO₂ is released when the solution is heated allowing the amine to be reused in multiple cycles of absorption and regeneration.

This type of amine-based carbon capture works well, but it is not without some drawbacks. The temperature swings needed for this desorption process not only requires significant energy input but can also lead to gradual degradation of the amine, commonly referred to as thermal degradation. This can lead to solvent losses, reduced performance, and higher operational costs. In addition, the solvent can degrade due to exposure to oxygen and other contaminants present in the gas (such as SO₂, NOx). This oxidative degradation can lead to the formation of unwanted byproducts, some of which are regulated volatile organic compounds. To avoid unintended environmental effects, the amine degradation pathways need to be carefully understood and managed. Amine degradation can produce a combination of different species generating a complex matrix that when coupled with the high pH environment, can make degradation remediation challenging. This dissertation focuses on the degradation by-products of amine solvents in carbon capture systems and how the chemical differences between the amine and water impacts the volatility and the removal of these degradation compounds. A better understanding of theses impacts allows for the development of mitigation strategies minimizing any environmental impacts.

Mitigation of the unwanted degradation byproducts is achieved by either removing the contaminants from the solvent or capturing and neutralizing them within the system. First, an assessment was performed to understand the effectiveness of activated carbon adsorption, with implications for treating high pH solutions. While there were some benefits to this methodology, activated carbon adsorption was not completely effective and presented several limitations such as metal leaching from the activated carbon material. Given this, it is necessary to expand into other areas of degradation mitigation. First understanding the potential for emissions of any degradation products, including compounds such as aldehydes, is crucial given their known environmental and human health hazards. These emissions may be impacted by the composition of the amine solvent used, therefore the Henry’s volatility coefficient of acetaldehyde in relevant amine solutions were determined as a surrogate for other classes of potential degradation compounds. The volatility was determined to be significantly higher from the amine solvent when compared to water, which is critical fundamental information in aiding the development of proper mitigation strategies that can be implemented within capture systems. 

Current engineering controls within CO₂ capture plants involve the use of water wash systems to reduce amine emissions, however some degradation products are also captured by this system which allows for their targeted neutralization. The composition of the wash-water poses yet another unique challenge as the complex matrix and increased the pH make it difficult to treat via traditional water treatment methods. An electrochemical-mediated treatment method was developed and evaluated to facilitate the decomposition of N-nitrosamines and aldehydes. The experimental results showed that even in the presence of this complex matrix, highly efficient decomposition of these hazardous compounds can be achieved.

��ɫ��Ƶ is entering a new paradigm of automation and data-driven discovery. Automated discovery is grounded in well-curated “big data.” As generative and predictive models fueled by simulation data see growing success, emerging robotic automation enables the generation of unprecedented volumes of experimental data. Automation-powered, data-driven approaches hold tremendous potential for groundbreaking insights and innovations, particularly in the study and discovery of electroactive π-conjugated molecules. Realizing this potential, however, requires democratizing chemical data and the automation needed to generate and use it. There is a need to expand access to the tools for findable, accessible, interoperable, and reusable (FAIR) data management and experimental automation. This dissertation contends that efficient discovery in the realm of electroactive π-conjugated molecules requires a coalition of automation and data-driven design with chemists and chemical intuition; this necessitates both large-scale FAIR data and intuitive man-machine interfaces. This dissertation investigates the automation of big-data generation, management, and analysis in the context of studying small electroactive π-conjugated molecules. First, this work examines the philosophical and historical foundations underpinning chemical data ontologies upon which automation and data-driven approaches depend. It advocates for interdisciplinary collaboration between philosophers and chemists to create more realistic, intuitive, and FAIR-compliant data structures. Then, this dissertation explores data generation and management in practice by producing computational data for over 40,000 electroactive molecules via automated high-throughput quantum chemical calculations and building a management infrastructure for the resulting data. It next demonstrates the insights gained through analyzing big data with a study of dihedral angle rotations in π-conjugated systems. The results demonstrate the ability of data-empowered machine learning (ML) to inexpensively automate the estimation of experiment-aligned for mesoscale properties. Likewise, it discusses how big data can be utilized for informing the selection of similarity measures, a key metric in many automated discovery applications. This work finally transitions to the automated generation of experimental data. It overviews a software developed for translating experimental protocols to robotic actions, validating the system by reproducing well-reported electrochemical experiments. Overall, this dissertation offers a path through effective organization, generation, management, and use of chemical data towards the automated study and discovery of electroactive π-conjugated molecules.

��ɫ��Ƶ is entering a new paradigm of automation and data-driven discovery. Automated discovery is grounded in well-curated “big data.” As generative and predictive models fueled by simulation data see growing success, emerging robotic automation enables the generation of unprecedented volumes of experimental data. Automation-powered, data-driven approaches hold tremendous potential for groundbreaking insights and innovations, particularly in the study and discovery of electroactive π-conjugated molecules. Realizing this potential, however, requires democratizing chemical data and the automation needed to generate and use it. There is a need to expand access to the tools for findable, accessible, interoperable, and reusable (FAIR) data management and experimental automation. This dissertation contends that efficient discovery in the realm of electroactive π-conjugated molecules requires a coalition of automation and data-driven design with chemists and chemical intuition; this necessitates both large-scale FAIR data and intuitive man-machine interfaces. This dissertation investigates the automation of big-data generation, management, and analysis in the context of studying small electroactive π-conjugated molecules. First, this work examines the philosophical and historical foundations underpinning chemical data ontologies upon which automation and data-driven approaches depend. It advocates for interdisciplinary collaboration between philosophers and chemists to create more realistic, intuitive, and FAIR-compliant data structures. Then, this dissertation explores data generation and management in practice by producing computational data for over 40,000 electroactive molecules via automated high-throughput quantum chemical calculations and building a management infrastructure for the resulting data. It next demonstrates the insights gained through analyzing big data with a study of dihedral angle rotations in π-conjugated systems. The results demonstrate the ability of data-empowered machine learning (ML) to inexpensively automate the estimation of experiment-aligned for mesoscale properties. Likewise, it discusses how big data can be utilized for informing the selection of similarity measures, a key metric in many automated discovery applications. This work finally transitions to the automated generation of experimental data. It overviews a software developed for translating experimental protocols to robotic actions, validating the system by reproducing well-reported electrochemical experiments. Overall, this dissertation offers a path through effective organization, generation, management, and use of chemical data towards the automated study and discovery of electroactive π-conjugated molecules.

Several technologies have been developed to produce hydrocarbon biofuels – renewable diesel (RD) and sustainable aviation fuel (SAF) – from fats, oils, and greases (FOG), with the hydroprocessing of esters and fatty acids (HEFA) representing one of the most mature pathways. In its current form, HEFA is mainly reliant on the hydrodeoxygenation (HDO) reaction, which has several drawbacks since HDO requires large amounts and pressures of hydrogen, feedstocks of high purity and cost, as well as problematic sulfided catalysts that risk contaminating the biofuel product with sulfur. A process based on decarboxylation/decarbonylation (deCO_x) offers an attractive alternative to HDO, since it requires lower amounts and pressures of hydrogen, feedstocks of low purity and cost, and simple supported metal catalysts. Herein, several geographically distributed oleaginous feedstocks – ranging from municipal waste feeds (brown grease) to pine chemicals (tall oil and rosin) – were upgraded to RD and SAF via deCOx. Powdered and engineered Ni-based catalysts were used for FOG-to-RD conversion via deCO_x, evaluating deoxygenation over reducible and non-reducible oxides. 

Engineered alumina-based catalyst showed superior deoxygenation activity and stability for up to 300 hours on stream. Similarly, quantitative conversion of FOG to SAF was achieved over bifunctional Ni-Cu-based catalysts with zeolitic supports, with deCO_x and isomerization occurring in a single step. Initial screening studies performed in a semi-batch reactor revealed that upgrading distilled tall oil (DTO) over a Ni-Cu-based catalyst afforded all types of hydrocarbons comprising SAF, namely n-alkanes, iso-alkanes, cycloalkanes, and aromatics. The same combination of feed, catalyst, and reaction conditions were applied in a fixed-bed reactor for a continuous experiment, consisting of two 72-hour cycles with catalyst regeneration in between. DTO conversion remained quantitative (~100%), with aromatic yields ≥80% regardless of time-on-stream. Most liquid products fell within the carbon number and boiling point range of jet fuel across all samples. Notably, the reaction produced all hydrocarbon classes found in SAF, with particular abundance of aromatic hydrocarbons. Since ~20% aromatics are required to swell elastomeric seals and prevent leaks in aircraft fuel systems, seal compatibility testing confirmed that the aromatics-rich SAF blendstock exhibited a volume swell percentage comparable to qualified SAF blends. Catalysts used for deoxygenation reactions were characterized using various techniques – including N₂ physisorption, X-ray diffraction, X-ray photoelectron spectroscopy, microscopy, and temperature-programmed methods – to rationalize trends, propose reaction pathways, and elucidate structure-activity relationships. Finally, to evaluate the economic and environmental feasibility of this technology, techno-economic and lifecycle analyses were conducted on an integrated plant combining catalytic deoxygenation and hydrothermal gasification, producing hydrogen for converting tall oil fatty acid to SAF. The analyses revealed a minimum fuel-selling price of USD$0.39/L – lower than that of existing SAF pathways (USD$1.4/L) – with greenhouse gas emissions of 5.1g CO₂-eq/MJ, which is 94% lower than fossil jet fuel (85g CO₂-eq/MJ). 

Several technologies have been developed to produce hydrocarbon biofuels – renewable diesel (RD) and sustainable aviation fuel (SAF) – from fats, oils, and greases (FOG), with the hydroprocessing of esters and fatty acids (HEFA) representing one of the most mature pathways. In its current form, HEFA is mainly reliant on the hydrodeoxygenation (HDO) reaction, which has several drawbacks since HDO requires large amounts and pressures of hydrogen, feedstocks of high purity and cost, as well as problematic sulfided catalysts that risk contaminating the biofuel product with sulfur. A process based on decarboxylation/decarbonylation (deCO_x) offers an attractive alternative to HDO, since it requires lower amounts and pressures of hydrogen, feedstocks of low purity and cost, and simple supported metal catalysts. Herein, several geographically distributed oleaginous feedstocks – ranging from municipal waste feeds (brown grease) to pine chemicals (tall oil and rosin) – were upgraded to RD and SAF via deCOx. Powdered and engineered Ni-based catalysts were used for FOG-to-RD conversion via deCO_x, evaluating deoxygenation over reducible and non-reducible oxides. 

Engineered alumina-based catalyst showed superior deoxygenation activity and stability for up to 300 hours on stream. Similarly, quantitative conversion of FOG to SAF was achieved over bifunctional Ni-Cu-based catalysts with zeolitic supports, with deCO_x and isomerization occurring in a single step. Initial screening studies performed in a semi-batch reactor revealed that upgrading distilled tall oil (DTO) over a Ni-Cu-based catalyst afforded all types of hydrocarbons comprising SAF, namely n-alkanes, iso-alkanes, cycloalkanes, and aromatics. The same combination of feed, catalyst, and reaction conditions were applied in a fixed-bed reactor for a continuous experiment, consisting of two 72-hour cycles with catalyst regeneration in between. DTO conversion remained quantitative (~100%), with aromatic yields ≥80% regardless of time-on-stream. Most liquid products fell within the carbon number and boiling point range of jet fuel across all samples. Notably, the reaction produced all hydrocarbon classes found in SAF, with particular abundance of aromatic hydrocarbons. Since ~20% aromatics are required to swell elastomeric seals and prevent leaks in aircraft fuel systems, seal compatibility testing confirmed that the aromatics-rich SAF blendstock exhibited a volume swell percentage comparable to qualified SAF blends. Catalysts used for deoxygenation reactions were characterized using various techniques – including N₂ physisorption, X-ray diffraction, X-ray photoelectron spectroscopy, microscopy, and temperature-programmed methods – to rationalize trends, propose reaction pathways, and elucidate structure-activity relationships. Finally, to evaluate the economic and environmental feasibility of this technology, techno-economic and lifecycle analyses were conducted on an integrated plant combining catalytic deoxygenation and hydrothermal gasification, producing hydrogen for converting tall oil fatty acid to SAF. The analyses revealed a minimum fuel-selling price of USD$0.39/L – lower than that of existing SAF pathways (USD$1.4/L) – with greenhouse gas emissions of 5.1g CO₂-eq/MJ, which is 94% lower than fossil jet fuel (85g CO₂-eq/MJ).