Open Access Publications

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Open access publications by faculty, postdocs, and graduate students in the Department of Chemical and Biomolecular Engineering

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Effects of Chitin Nano-flake Fillers on the Mechanical and Barrier Properties of Polylactic Acid Biocomposite Films
(BioResources, 2024-08-16) Kwon, Soojin; Kim, Sang Yun; Oh, Kyudeok; Han, Jung Soo
Polylactic acid (PLA) is a biodegradable polymer extensively used in packaging; however, its mechanical and barrier properties require enhancement for wider applications. Chitin-derived nanoflakes (CNFL), a two-dimensionally separated nanomaterial derived from α-chitin, possess high strength and toughness, making them ideal additives for improved PLA performance. This study investigated the effect of CNFL on the properties of PLA composite films. Incorporating CNFL significantly enhanced the mechanical properties of PLA, increasing its tensile strength and stiffness while preserving flexibility. This enhancement was attributed to the nucleating effect of CNFL, which increases crystallinity. Additionally, CNFL improved the thermal stability of the composite films by mitigating thermal deformation. Notably, the oxygen barrier properties of CNFL-filled PLA composites were also enhanced, demonstrating a significant reduction in oxygen permeability at optimal CNFL concentrations due to increased tortuosity of the oxygen diffusion path. Overall, CNFL-filled PLA composites exhibit great potential as renewable packaging materials, particularly for protecting sensitive products, such as food and pharmaceuticals, from oxidative degradation, thereby extending shelf life and maintaining quality. These findings suggest that CNFL-filled PLA composites are promising materials for advanced applications, offering a combination of enhanced mechanical performance, improved thermal stability, and superior oxygen barrier properties.
Superstructure optimization for management of low-density polyethylene plastic waste
(Green Chemistry, 2024-08-14) Hernández, Borja; Vlachos, Dionisios G.; Ierapetritou, Marianthi G.
We introduce a systematic framework centered on superstructure optimization to identify the most efficient economic and environmentally friendly approach for managing plastic waste. Applying the proposed framework to low-density-polyethylene (LDPE) plastic waste, we determine that pyrolysis is the most profitable technology followed by hydroformylation to C4–C8 olefins, and the oligomerization of higher carbon olefins. Coupling the results with geographical information, the selected superstructure has the potential to improve the economics of plastic waste management by approximately $3 per kgLDPE in countries like the United States. On the other hand, the lowest CO2 emission plastic waste management uses solvent-based recycling only when there is significant degradation during mechanical recycling. When plastic waste can be recycled mechanically more than five times, the emissions in mechanical recycling are lower. These technologies collectively contribute to emissions reductions ranging from 1.5 and 3 kgCO2eq. per kgLDPE, for mechanical and solvent-based recycling, respectively.
Biomass-derived, Target Specific, and Ecologically Safer Insecticide Active Ingredients
(Chemistry-Sustainability-Energy-Materials, 2024-08-21) Goculdas, Tejas B.; Ramirez, Maximus; Crossley, Michael; Sadula, Sunitha; Vlachos, Dionisios G.
With the continuous increase in food production to support the growing population, ensuring agricultural sustainability using crop-protecting agents, such as pesticides, is vital. Conventional pesticides pose significant environmental risks, prompting the need for eco-friendly alternatives. This study reports the synthesis of new amide-based insecticidal active ingredients from biomass-derived monomers, specifically furfural and vanillin. The process involves reductive amination followed by carbonylation. The synthesis of the furfural-based carbamate yield reaches a cumulative 88%, with catalysts Rh/Al2O3 and La(OTf)3 being recyclable at each stage. Insecticidal activity assessments reveal that the furfural carbamate exhibits competitive performance, achieving an LC50 of 6.35 μg/cm², compared to 6.27 μg/cm² for carbofuran. Ecotoxicity predictions indicate significantly lower toxicity levels toward non-target aquatic and terrestrial species. The importance of the low octanol-water partition coefficient of the biobased carbamate, attributed to the oxygen heteroatom and electron density of the furan ring, is discussed in detail. Building on these promising results, the synthesis strategy was extended to six other biobased aldehydes, resulting in a diverse portfolio of biomass-derived carbamates. A techno-economic analysis reveals a minimum selling price of 11.1$/kg, only half that of comparable carbamates, demonstrating the economic viability of these new biobased insecticides.
Sustainable Aviation Fuel Molecules from (Hemi)Cellulose: Computational Insights into Synthesis Routes, Fuel Properties, and Process Chemistry Metrics
(ACS Sustainable Chemistry and Engineering, 2024-08-13) Chang, Chin-Fei; Paragian, Kristin; Sadula, Sunitha; Rangarajan, Srinivas; Vlachos, Dionisios G.
Production of sustainable aviation fuels (SAFs) can significantly reduce the aviation industry’s carbon footprint. Current pathways that produce SAFs in significant volumes from ethanol and fatty acids can be costly, have a relatively high carbon intensity (CI), and impose sustainability challenges. There is a need for a diversified approach to reduce costs and utilize more sustainable feedstocks effectively. Here, we map out catalytic synthesis routes to convert furanics derived from the (hemi)cellulosic biomass to alkanes and cycloalkanes using automated network generation with RING and semiempirical thermochemistry calculations. We find >100 energy-dense C8–C16 alkane and cycloalkane SAF candidates over 300 synthesis routes; the top three are 2-methyl heptane, ethyl cyclohexane, and propyl cyclohexane, although these are relatively short. The shortest, least endothermic process chemistry involves C–C coupling, oxygen removal, and hydrogen addition, with dehydracyclization of the heterocyclic oxygens in the furan ring being the most endothermic step. The global warming potential due to hydrogen use and byproduct CO2 is typically 0.7–1 kg CO2/kg SAF product; the least CO2 emitting routes entail making larger molecules with fewer ketonization, hydrogenation, and hydrodeoxygenation steps. The large number of SAF candidates highlights the rich potential of furanics as a source of SAF molecules. However, the structural dissimilarity between reactants and target products precludes pathways with fewer than six synthetic steps, thus necessitating intensified processes, integrating multiple reaction steps in multifunctional catalytic reactors.
Cu Based Dilute Alloys for Tuning the C2+ Selectivity of Electrochemical CO2 Reduction
(Small, 2024-07-12) Crandall, Bradie S.; Qi, Zhen; Foucher, Alexandre C.; Weitzner, Stephen E.; Akhade, Sneha A.; Liu, Xin; Kashi, Ajay R.; Buckley, Aya K.; Ma, Sichao; Stach, Eric A.; Varley, Joel B.; Jiao, Feng; Biener, Juergen
Electrochemical CO2 reduction is a promising technology for replacing fossil fuel feedstocks in the chemical industry but further improvements in catalyst selectivity need to be made. So far, only copper-based catalysts have shown efficient conversion of CO2 into the desired multi-carbon (C2+) products. This work explores Cu-based dilute alloys to systematically tune the energy landscape of CO2 electrolysis toward C2+ products. Selection of the dilute alloy components is guided by grand canonical density functional theory simulations using the calculated binding energies of the reaction intermediates CO*, CHO*, and OCCO* dimer as descriptors for the selectivity toward C2+ products. A physical vapor deposition catalyst testing platform is employed to isolate the effect of alloy composition on the C2+/C1 product branching ratio without interference from catalyst morphology or catalyst integration. Six dilute alloy catalysts are prepared and tested with respect to their C2+/C1 product ratio using different electrolyzer environments including selected tests in a 100-cm2 electrolyzer. Consistent with theory, CuAl, CuB, CuGa and especially CuSc show increased selectivity toward C2+ products by making CO dimerization energetically more favorable on the dominant Cu facets, demonstrating the power of using the dilute alloy approach to tune the selectivity of CO2 electrolysis.
Age-dependent changes in phagocytic activity: in vivo response of mouse pulmonary antigen presenting cells to direct lung delivery of charged PEGDA nanoparticles
(Journal of Nanobiotechnology, 2024-08-12) Sudduth, Emma R.; Ruiz, Aida López; Trautmann-Rodriguez, Michael; Fromen, Catherine A.
Background Current needle-based vaccination for respiratory viruses is ineffective at producing sufficient, long-lasting local immunity in the elderly. Direct pulmonary delivery to the resident local pulmonary immune cells can create long-term mucosal responses. However, criteria for drug vehicle design rules that can overcome age-specific changes in immune cell functions have yet to be established. Results Here, in vivo charge-based nanoparticle (NP) uptake was compared in mice of two age groups (2- and 16-months) within the four notable pulmonary antigen presenting cell (APC) populations: alveolar macrophages (AM), interstitial macrophages (IM), CD103+ dendritic cells (DCs), and CD11b+ DCs. Both macrophage populations exhibited preferential uptake of anionic nanoparticles but showed inverse rates of phagocytosis between the AM and IM populations across age. DC populations demonstrated preferential uptake of cationic nanoparticles, which remarkably did not significantly change in the aged group. Further characterization of cell phenotypes post-NP internalization demonstrated unique surface marker expression and activation levels for each APC population, showcasing heightened DC inflammatory response to NP delivery in the aged group. Conclusion The age of mice demonstrated significant preferences in the charge-based NP uptake in APCs that differed greatly between macrophages and DCs. Carefully balance of the targeting and activation of specific types of pulmonary APCs will be critical to produce efficient, age-based vaccines for the growing elderly population.
Effect of defects and framework Sn on the stability and activity of Pt clusters for ethane dehydrogenation in chabazite zeolite
(Reaction Chemistry and Engineering, 2024-08-06) Srinivas, Sanjana; Vlachos, Dionisios G.; Caratzoulas, Stavros
With increasing interest in new catalytic materials based on atomically dispersed transition metals on various supports (e.g., zeolites or oxides), it is necessary to have an atomic level understanding of the factors that determine their structural and electronic properties as well as catalytic activity. Encapsulated Pt atoms and sub-nanometer Pt clusters in Sn-substituted zeolitic frameworks have demonstrated extended catalytic stability and remarkable selectivity for alkane dehydrogenation to alkenes. Despite efforts to characterize these materials, the bonding environment of the dispersed atoms in the presence of framework Sn or of defect silanols is uncertain. We have employed ab initio molecular dynamics simulations and electronic structure calculations to identify and characterize electronically stable Pt active site motifs in chabazite (CHA) and Sn-CHA at low Pt loadings. The activity of several active site motifs was assessed by microkinetic simulations. We demonstrate that framework Sn and silanol defects can promote the dispersion of Pt species. Unexpectedly, we find that in the presence of silanol nests, the dispersed Pt species statistically prefer to coordinate with the silanols and not with the framework Sn. We show that Pt and Sn are bonded via a 3-center-4-electron bond (O:–Sn–:Pt), affirm the absence of Pt–O–Sn bonding, and thus resolve the ambiguity related to the coordination of Pt to framework Sn. We predict that the O:–Sn–:Pt and Sn–O–Pt–Pt–Si bonding motifs in Sn-CHA are stable and active for ethane dehydrogenation. We relate our findings and conclusions to recent experimental characterization of Pt in Sn-BEA zeolite, point out the close alignment in several aspects and suggest that the effect of framework Sn on the dispersion of low nuclearity Pt species and on the formation of stable and efficient active sites should be largely independent of the framework itself.
Process intensified lauric acid self-ketonization and its economic and environmental impact on biolubricant base oil production
(Green Chemistry, 2024-07-03) Goculdas, Tejas; Yuliu, Zhifei; Sadula, Sunitha; Zheng, Weiqing; Saha, Basudeb; Nanduri, Arvind; Ierapetritou, Marianthi; Vlachos, Dionisios G.
Lubricant base oils, traditionally derived from non-renewable petroleum, contribute significantly to greenhouse gas emissions. In contrast, oils sourced from furfural and long-chain ketones through aldol condensation and hydrodeoxygenation present a renewable, cost-effective, and environmentally friendly alternative, offering superior cold flow properties. However, the production of long-chain ketones, a crucial component, currently relies on solvent dewaxing in refineries, which is costly and non-selective. One promising biobased approach involves self-ketonization of long-chain fatty acids derived from coconut or palm kernel oils. This method typically employs high boiling point solvents like dodecane or is done in a batch configuration, limiting its scale and industrial viability. This study addresses this bottleneck by eliminating solvents, transitioning to a continuous flow reactor, and achieving kilogram-scale production of long-chain ketones with exceptional selectivity (90%). The lab-scale setup can yield up to 25 kg of 12-tricosanone per month, utilizing earth-abundant MgO as a catalyst. The catalyst underwent slight deactivation due to carbonate formation. Catalyst stabilization, using mixed metal oxides, and regeneration via simple calcination in air are also discussed. Techno-economic analysis (TEA) indicates a 29% lower minimum selling price than the commercial synthetic poly alpha olefin (PAO). Life cycle assessment (LCA) evaluates the global warming potential (GWP) under different environmental assumptions. Under the carbon-neutral assumption for lauric acid production, an 8.9% reduction in GWP was achieved compared to petroleum-based lubricants.
Cycloaddition–dehydration continuous flow chemistry for renewable para-xylene production from 2,5-dimethylfuran and ethylene over phosphorous-decorated zeolite beta
(Green Chemistry, 2024-07-03) Wang, Zhaoxing; Goculdas, Tejas; Hsiao, Yung Wei; Fan, Wei; Vlachos, Dionisios G.
Continuous manufacturing of platform chemicals from lignocellulose is highly desirable for a fossil fuel independent future. We demonstrate highly selective production of para-xylene (pX) from ethylene and 2,5-dimethylfuran (DMF) in a packed bed microreactor using phosphorous-decorated zeolite beta (P-BEA), with pX selectivity up to 97% at 80% DMF conversion. We map the effect of reactor temperature, space velocity, concentration, gas-to-liquid ratio, and process pressure. Time-on-stream (TOS) and in situ regeneration studies show minimal productivity degradation over ∼5 h TOS and full productivity restoration upon regeneration for multiple cycles. Most non-selective Brønsted acidity occurs at low TOS and is attributed to the remaining trace Al bridge site. External mass transfer limitations are implicated at low space velocities. We combine the TOS data with NMR, XRD, and Raman to develop structure–performance insights into the catalyst behavior. A comparison with mesoporous P-supported materials illustrates that P-BEA is an excellent catalyst for size selectivity and long-term stability.
Engineering lignin-derivable diacrylate networks with tunable architecture and mechanics
(Materials Advances, 2024-07-03) Wong, Yu-Tai; Korley, LaShanda T. J.
Network engineering strategies offer a promising pathway toward tunable thermomechanical properties of bio-derivable, aromatic (meth)acrylate thermosets to expand their application library. In this work, a series of acrylate thermosets, synthesized from lignin-derivable vanillyl alcohol/bisguaiacol F diacrylates (VDA/BGFDA) and a bio-based n-butyl acrylate (BA), were designed as a sustainable platform to explore structure-architecture-property relationships. Using this approach, we examined a series of processable, fully bio-derivable acrylates. Increasing the diacrylate content across all networks improved storage moduli at 25 °C (E′25) by up to 2 GPa (1.1 GPa for VDA/BA-25/75 vs. 3.1 GPa for VDA/BA-75/25, and 1.5 GPa for BGFDA/BA-25/75 vs. 1.7 GPa for BGFDA/BA-50/50), and led to a more inhomogeneous network as evidenced by lower acrylate group conversion and a broader tan δ peak, indicating heterogeneous relaxation modes. Modifying the aromatic content of the starting diacrylate impacted the final inhomogeneity of the network, with increasing inhomogeneity observed for the bis-aromatic BGFDA relative to the mono-aromatic VDA. Similarly, combining the mono- and bis-aromatic diacrylates generated a network with a biphasic-like thermal relaxation mode. By correlating network architecture and material performance, the increasing architectural complexity suggested a more convoluted thermal relaxation mode while the enhancement of thermomechanical properties could still be achieved for potential application as damping materials. Overall, we presented a design strategy utilizing bio-derivable acrylates to expand the suite of renewable material platforms from a network engineering perspective.
Supramolecular Gelation of Cadmium Oleate in the Synthesis of Nanocrystals for Applications in Photonics and Optoelectronics
(ACS Applied Nano Materials, 2024-05-22) Welsch, Tory A.; Cleveland, Jill M.; Thomas, Jessica A.; Schyns, Zoé Odile Georgette; Korley, LaShanda T. J.; Doty, Matthew F.
Cadmium oleate is widely used as a cation precursor in the synthesis of cadmium chalcogenide nanocrystal quantum dots (QDs) for a broad range of photonic and optoelectronic applications. Cd oleate can noncovalently assemble to form a supramolecular coordination gel, or metallogel, in solvents commonly used to disperse oleate-capped QDs. The gelation severely impedes the purification of oleate-capped QDs from excess Cd oleate, resulting in a gelled product that cannot be reliably characterized or used in further synthesis reactions. Here, we investigate the Cd oleate gel to gain insights into its viscoelastic properties and behavior under conditions relevant to QD synthesis, purification, and storage. We then examine how to effectively mitigate gelation by adding oleylamine as an additional ligand to disrupt noncovalent assembly. We synthesize PbS/CdS core/shell QDs via cation exchange as a case study to illustrate gelation of the reaction product and further demonstrate how this issue can be resolved through a better understanding of the supramolecular gel.
Modeling Study on Heat Capacity, Viscosity, and Density of Ionic Liquid–Organic Solvent–Organic Solvent Ternary Mixtures via Machine Learning
(Processes, 2024-07-07) Shu, You; Du, Lei; Lei, Yang; Hu, Shaobin; Kuang, Yongchao; Fang, Hongming; Liu, Xinyan; Chen, Yuqiu
Physicochemical properties of ionic liquids (ILs) are essential in solvent screening and process design. However, due to their vast diversity, acquiring IL properties through experimentation alone is both time-consuming and costly. For this reason, the creation of prediction models that can accurately forecast the characteristics of IL and its mixtures is crucial to their application. This study proposes a model for predicting the three important parameters of the IL-organic solvent–organic solvent ternary system: density, viscosity, and heat capacity. The model incorporates group contribution (GC) and machine learning (ML) methods. A link between variables such as temperature, pressure, and molecular structure is established by the model. We gathered 2775 viscosity, 6515 density, and 1057 heat capacity data points to compare the prediction accuracy of three machine learning methods, namely, artificial neural networks (ANNs), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). As can be observed from the findings, the ANN model produced the best results out of the three GC-based ML methods, even though all three produced dependable predictions. For heat capacity, the mean absolute error (MAE) of the ANN model is 1.7320 and the squared correlation coefficient (R2) is 0.9929. Regarding viscosity, the MAE of the ANN model is 0.0225 and the R2 is 0.9973. For density, the MAE of the ANN model is 7.3760 and the R2 is 0.9943. The Shapley additive explanatory (SHAP) approach was applied to the study to comprehend the significance of each feature in the prediction findings. The analysis results indicated that the R-CH3 group of the ILs, followed by the imidazolium (Im) group, had the highest impact on the heat capacity property of the ternary system. On the other hand, the Im group and the R-H group of ILs had the most effects on viscosity. In terms of density, the Im group of the ILs had the greatest effect on the ternary system, followed by the molar fraction of the organic solvent.
Dynamic reporters for probing real-time activation of human fibroblasts from single cells to populations
(APL Bioengineering, 2024-06-24) Cassel, Samantha E.; Huntington, Breanna M.; Chen, Wilfred; Lei, Pedro; Andreadis, Stelios T.; Kloxin, April M.
Activation of fibroblasts is pivotal for wound healing; however, persistent activation leads to maladaptive processes and is a hallmark of fibrosis, where disease mechanisms are only partially understood. Human in vitro model systems complement in vivo animal models for both hypothesis testing and drug evaluation to improve the identification of therapeutics relevant to human disease. Despite advances, a challenge remains in understanding the dynamics of human fibroblast responses to complex microenvironment stimuli, motivating the need for more advanced tools to investigate fibrotic mechanisms. This work established approaches for assessing the temporal dynamics of these responses using genetically encoded fluorescent reporters of alpha smooth muscle actin expression, an indicator of fibroblast activation. Specifically, we created a toolset of human lung fibroblast reporter cell lines from different origins (male, female; healthy, idiopathic pulmonary fibrosis) and used three different versions of the reporter with the fluorescent protein modified to exhibit different temporal stabilities, providing temporal resolution of protein expression processes over a range of timescales. Using this toolset, we demonstrated that reporters provide insight into population shifts in response to both mechanical and biochemical cues that are not detectable by traditional end point assessments with differential responses based on cell origin. Furthermore, individual cells can also be tracked over time, with opportunities for comparison to complementary end point measurements. The establishment of this reporter toolset enables dynamic cell investigations that can be translated into more complex synthetic culture environments for elucidating disease mechanisms and evaluating therapeutics for lung fibrosis and other complex biological processes more broadly.
RNASeq highlights ATF6 pathway regulators for CHO cell engineering with different impacts of ATF6β and WFS1 knockdown on fed-batch production of IgG1
(Scientific Reports, 2024-06-19) Rives, Dyllan; Peak, Caroline; Blenner, Mark A.
Secretion levels required of industrial Chinese hamster ovary (CHO) cell lines can challenge endoplasmic reticulum (ER) homeostasis, and ER stress caused by accumulation of misfolded proteins can be a bottleneck in biomanufacturing. The unfolded protein response (UPR) is initiated to restore homeostasis in response to ER stress, and optimization of the UPR can improve CHO cell production of therapeutic proteins. We compared the fed-batch growth, production characteristics, and transcriptomic response of an immunoglobulin G1 (IgG1) producer to its parental, non-producing host cell line. We conducted differential gene expression analysis using high throughput RNA sequencing (RNASeq) and quantitative polymerase chain reaction (qPCR) to study the ER stress response of each cell line during fed-batch culture. The UPR was activated in the IgG1 producer compared to the host cell line and our analysis of differential expression profiles indicated transient upregulation of ATF6α target mRNAs in the IgG1 producer, suggesting two upstream regulators of the ATF6 arm of the UPR, ATF6β and WFS1, are rational engineering targets. Although both ATF6β and WFS1 have been reported to negatively regulate ATF6α, this study shows knockdown of either target elicits different effects in an IgG1-producing CHO cell line. Stable knockdown of ATF6β decreased cell growth without decreasing titer; however, knockdown of WFS1 decreased titer without affecting growth. Relative expression measured by qPCR indicated no direct relationship between ATF6β and WFS1 expression, but upregulation of WFS1 in one pool was correlated with decreased growth and upregulation of ER chaperone mRNAs. While knockdown of WFS1 had negative impacts on UPR activation and product mRNA expression, knockdown of ATF6β improved the UPR specifically later in fed-batch leading to increased overall productivity.
Computational insights into steady-state and dynamic Joule-heated reactors
(Reaction Chemistry and Engineering, 2024-06-10) Mittal, Arnav; Ierapetritou, Marianthi; Vlachos, Dionisios G.
Joule-heated reactors could drive high-temperature endothermic reactions without heat transfer limitations to the catalyst and with high energy efficiency and fast dynamics under suitable conditions. We use 3D computational fluid dynamics (CFD) to investigate the power distribution, temperature field, and flow patterns in continuous steady-state and rapid-pulse Joule heated reactors with carbon fiber paper as the heating element. The model is in good agreement with published experimental data. We demonstrate flow recirculation under typical conditions and derive criteria for their suppression. We showcase rapid (seconds or shorter) and uniform heating to very high temperatures (>1500 °C) with minimal heating of the flowing gas, which could reduce undesired gas-phase chemistry. A simple energy model indicates that a high applied voltage and heating elements of high electrical conductivity and low volumetric heat capacity accelerate heating. We report heat transfer enhancement during rapid pulsing, a form of process intensification enabled by dynamic operation.
Suppression of Segmental Chain Dynamics on a Particle’s Surface in Well-Dispersed Polymer Nanocomposites
(ACS Macro Letters, 2024-06-18) Kim, Jihyuk; Thompson, Benjamin R.; Tominaga, Taiki; Osawa, Takahito; Egami, Takeshi; Förster, Stephan; Ohl, Michael; Senses, Erkan; Faraone, Antonio; Wagner, Norman J.
The Rouse dynamics of polymer chains in model nanocomposite polyethylene oxide/silica nanoparticles (NPs) was investigated using quasielastic neutron scattering. The apparent Rouse rate of the polymer chains decreases as the particle loading increases. However, there is no evidence of an immobile segment population on the probed time scale of tens of ps. The slowing down of the dynamics is interpreted in terms of modified Rouse models for the chains in the NP interphase region. Thus, two chain populations, one bulk-like and the other characterized by a suppression of Rouse modes, are identified. The spatial extent of the interphase region is estimated to be about twice the adsorbed layer thickness, or ≈2 nm. These findings provide a detailed description of the suppression of the chain dynamics on the surface of NPs. These results are relevant insights on surface effects and confinement and provide a foundation for the understanding of the rheological properties of polymer nanocomposites with well-dispersed NPs.
A color prediction model for mending materials of the Yuquan Iron Pagoda in China based on machine learning
(Heritage Science, 2024-06-06) Liu, Xuegang; Liu, Yuhang; Wang, Ke; Zhang, Yang; Lei, Yang; An, Hai; Wang, Mingqiang; Chen, Yuqiu
During the restoration of iron cultural relics, the removal of rust from these artifacts is necessary. However, this rust removal process may lead to inconsistent local color on the iron relics. To address this, mending materials are applied to treat the surface, ensuring consistent local color. In the surface treatment of iron cultural relics, a significant challenge lies in modulating the color of these mending materials. The corrosion products of Yuquan Iron Pagoda are mainly Fe3O4, γ-FeO(OH), α-FeO(OH) and α-Fe2O3, with contents of 13.1, 16.1, 40.2 and 30.6%, respectively. Due to their structural stability and suitable color characteristics, Fe3O4 and α-Fe2O3 are selected as the primary raw materials for the repair material. This study employs machine learning methods to predict the color of mending materials corresponding to varying contents of α-Fe2O3, Fe3O4, and epoxy resin. The Artificial Neural Network (ANN), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boost Machine (LightGBM) algorithms are utilized to develop the model, and the predictive performance of these three algorithms is compared. XGBoost exhibits the best prediction performance, achieving a square correlation coefficient (R2) of 0.94238 and a mean absolute error (MAE) of 0.68485. Additionally, the SHapley Additive exPlanations (SHAP) method is employed to analyze the most crucial raw material affecting the color of mending materials, which is identified as Fe3O4. The study illustrates the specific process of employing this model by applying it to the surface treatment of the Yuquan Iron Pagoda, demonstrating the practicality of the model. This model can be applied to assist in the surface treatment of other iron cultural relics.
Effect of Dynamic and Preferential Decoration of Pt Catalyst Surfaces by WOx on Hydrodeoxygenation Reactions
(Journal of the American Chemical Society, 2024-05-22) Marlowe, Justin; Deshpande, Siddharth; Vlachos, Dionisios G.; Abu-Omar, Mahdi M.; Christopher, Phillip
Catalysts containing Pt nanoparticles and reducible transition-metal oxides (WOx, NbOx, TiOx) exhibit remarkable selectivity to aromatic products in hydrodeoxygenation (HDO) reactions for biomass valorization, contrasting the undesired aromatic hydrogenation typically observed for metal catalysts. However, the active site(s) responsible for the high selectivity remains elusive. Here, theoretical and experimental analyses are combined to explain the observed HDO reactivity by interrogating the organization of reduced WOx domains on Pt surfaces at sub-monolayer coverage. The SurfGraph algorithm is used to develop model structures that capture the configurational space (∼1000 configurations) for density functional theory (DFT) calculations of a W3O7 trimer on stepped Pt surfaces. Machine-learning models trained on the DFT calculations identify the preferential occupation of well-coordinated Pt sites (≥8 Pt coordination number) by WOx and structural features governing WOx–Pt stability. WOx/Pt/SiO2 catalysts are synthesized with varying W loadings to test the theoretical predictions and relate them to HDO reactivity. Spectroscopy- and microscopy-based catalyst characterizations identify the dynamic and preferential decoration of well-coordinated sites on Pt nanoparticles by reduced WOx species, consistent with theoretical predictions. The catalytic consequences of this preferential decoration on the HDO of a lignin model compound, dihydroeugenol, are clarified. The effect of WOx decoration on Pt nanoparticles for HDO involves WOx inhibition of aromatic ring hydrogenation by preferentially blocking well-coordinated Pt sites. The identification of preferential decoration on specific sites of late-transition-metal surfaces by reducible metal oxides provides a new perspective for understanding and controlling metal–support interactions in heterogeneous catalysis.
Biphasic Plasma Microreactor for Oxyfunctionalization of Liquid Hydrocarbons
(Industrial & Engineering Chemistry Research, 2024-05-22) Nguyen, Darien K.; Cameli, Fabio; Dimitrakellis, Panagiotis; Vlachos, Dionisios G.
Oxyfunctionalization of linear alkanes is important but challenging to achieve. Herein, we demonstrate a biphasic gas–liquid modular plasma microreactor utilizing Ar/O2 gas to selectively oxidize liquid n-dodecane (C12) in an electrified, catalyst-free fashion. C12 secondary alcohols and ketones are the major products, with selectivities of 45–60% and a maximum yield of 23%. Fine-tuning gas and liquid flow rates enhance the plasma–liquid interfacial area, leading to a conversion of >50%. Difunctional and oligomerized oxygenates, alongside lighter hydrocarbons stemming from carbon–carbon cleavage, form at higher conversions. The energy efficiency (0.189 μmol/J) of the modular microreactor is the highest reported among plasma systems. Alkane conversion can be further improved by increasing the length of the plasma region while maintaining excellent energy efficiencies. Similarly, sequential processing/recirculation can enhance the extent of the reaction. This system is also amenable to treating mixtures of liquid n-alkanes, where smaller hydrocarbons are oxidized preferentially to a certain extent. The vapor pressure and liquid temperature are the key parameters. The chemistry occurs primarily in the gas phase for the lighter hydrocarbons and switches to interfacial reactions for the larger ones.
CKineticsDB─An Extensible and FAIR Data Management Framework and Datahub for Multiscale Modeling in Heterogeneous Catalysis
(Journal of Chemical Information and Modeling, 2023-07-24) Lambor, Siddhant M.; Kasiraju, Sashank; Vlachos, Dionisios G.
A great advantage of computational research is its reproducibility and reusability. However, an enormous amount of computational research data in heterogeneous catalysis is barricaded due to logistical limitations. Sufficient provenance and characterization of data and computational environment, with uniform organization and easy accessibility, can allow the development of software tools for integration across the multiscale modeling workflow. Here, we develop the Chemical Kinetics Database, CKineticsDB, a state-of-the-art datahub for multiscale modeling, designed to be compliant with the FAIR guiding principles for scientific data management. CKineticsDB utilizes a MongoDB back-end for extensibility and adaptation to varying data formats, with a referencing-based data model to reduce redundancy in storage. We have developed a Python software program for data processing operations and with built-in features to extract data for common applications. CKineticsDB evaluates the incoming data for quality and uniformity, retains curated information from simulations, enables accurate regeneration of publication results, optimizes storage, and allows the selective retrieval of files based on domain-relevant catalyst and simulation parameters. CKineticsDB provides data from multiple scales of theory (ab initio calculations, thermochemistry, and microkinetic models) to accelerate the development of new reaction pathways, kinetic analysis of reaction mechanisms, and catalysis discovery, along with several data-driven applications. Abstract Graphic available at: https://doi.org/10.1021/acs.jcim.3c00123

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