Scholarly Works, Chemical Engineering

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Patient-derived ovarian cancer models demonstrate the influence of tumor-associated macrophages on therapeutic response
Nikeghbal, Parisa; Burke, Danielle; Armijo, Dalet; Aldarondo-Quiñones, Samuel; Lidke, Diane S.; Steinkamp, Mara P. (Taylor & Francis, 2025-12)
While most ovarian cancer (OC) patients respond to front-line platinum/taxane chemotherapy and surgical debulking, the majority will develop platinum-resistance and recur. Our study investigated how tumor-associated macrophages (TAMs) within the tumor microenvironment (TME) affect chemotherapy outcomes using OC patient-derived organoids and humanized patient-derived xenografts (huPDX). In vitro macrophage migration assays demonstrated the selective recruitment of M2 macrophages to organoids. M2 macrophages, but not M1, increase organoid viability and reduce their sensitivity to paclitaxel in co-culture assays. Furthermore, BMS777607, a receptor tyrosine kinase inhibitor capable of repolarizing M2 macrophages in vitro, reduced organoid viability via a macrophage-dependent mechanism. In a platinum-sensitive huPDX model, the presence of human immune cells increased between-mouse variability in response to paclitaxel with two of four mice demonstrating tumor regrowth after two weeks. A TAM-targeted CSF-1 R inhibitor, BLZ945, combined with paclitaxel reduced tumor burden with no regrowth, suggesting that TAMs promote paclitaxel resistance in this model. Our study demonstrates that TAMs influence response to paclitaxel in both patient-derived OC organoids and huPDX. These models are useful for evaluating immunomodulatory therapy effects and could serve as a robust platform for preclinical testing of novel anti-cancer treatments, providing insights into the complex interplay between immune cells and cancer therapeutics.
Auranofin Synergizes with Cisplatin in Reducing Tumor Burden of NOTCH-Dependent Ovarian Cancer
Lake, Robert J.; Nikeghbal, Parisa; Lagutina, Irina V.; Leslie, Kimberly K.; Steinkamp, Mara P.; Fan, Hua-Ying (American Association for Cancer Research, 2025-10)
The NOTCH pathway regulates cell proliferation, differentiation, and stem cell maintenance. Thus, aberrant NOTCH activation plays a key role in cancer initiation, progression, and chemoresistance. Mutations and amplification of NOTCH pathway genes have been identified in high-grade serous ovarian cancers and are associated with poor clinical outcomes. Among the four NOTCH receptors, NOTCH3 alterations were strongly correlated with poor overall survival. Previously, we identified auranofin, an oral gold salt therapeutic compound, as a novel NOTCH pathway inhibitor that disrupts the DNA binding of RBPJ, the major downstream transcriptional effector of the NOTCH pathway. In this study, we surveyed the response of eight ovarian cancer cell lines to auranofin and found IC50 values ranging from 1.7 to 12 μmol/L, with NOTCH3-negative SKOV3 cells having the highest IC50 value. In NOTCH-dependent OVCAR3 cells, auranofin synergized with cisplatin to enhance cell death. Importantly, auranofin treatment led to a dose-dependent decrease in RBPJ occupancy at the NOTCH-dependent promoters, HES1 and HES4. Furthermore, knocking down NOTCH3 in OVCAR3 cells significantly decreased sensitivity to auranofin, further supporting the notion that NOTCH3 signaling is a major target of auranofin. Moreover, auranofin increased cisplatin efficacy in an OVCAR3-derived xenograft mouse model. Using eight patient-derived cancer organoid models, we found that auranofin increased cisplatin efficacy in killing cancer organoids generated from clinically platinum-sensitive patients but also restored platinum response in a subset of organoid models developed from platinum-resistant patients. These studies underscore the potential of auranofin to improve platinum-based cancer therapy, particularly in NOTCH3-expressing cancers.
Significance
NOTCH signaling underlies cancer initiation, progression, and chemoresistance. Our study revealed the potential of auranofin as a NOTCH pathway inhibitor to enhance the efficacy of platinum-based ovarian cancer therapy.
Organoid models established from primary tumors and patient-derived xenograft tumors reflect platinum sensitivity of ovarian cancer patients
Nikeghbal, Parisa; Zamanian, Dorsa; Burke, Danielle; Steinkamp, Mara P. (Springer, 2025-09)
BACKGROUND: Ovarian cancer (OC) remains the deadliest gynecological cancer, primarily due to late-stage diagnosis and high rates of chemotherapy resistance and recurrence. Lack of representative preclinical models complicate the challenges of discovering effective therapies, especially for platinum-resistant OC. Patient-derived xenograft (PDX) models maintain the genetic characteristics of the original tumor and are ideal for testing candidate therapies in vivo, but their high cost limits their feasibility for high-throughput drug screening. Organoid models mimic the tumor’s 3D structure and preserve intra-tumoral heterogeneity. While organoids established directly from primary patient tumors are the optimal model for personalized drug response studies, the supply of primary tissue is often limited. Patient-derived xenograft tumors can be passaged in mice and provide a renewable source of cancer cells for organoids. This study aimed to determine if PDX-derived organoids (PDXOs) can reflect patient responses to chemotherapy similarly to primary patient-derived organoids (PDOs). METHODS: 3D Organoid models were established from the malignant ascites of five high grade serous ovarian cancer patients: two platinum-sensitive, two platinum-resistant, and one platinum-refractory, along with their matched PDX samples from ascites and solid tumor. Organoid viability after 72-hour treatment with paclitaxel (PTX), carboplatin (CBDCA), or their combination was compared between organoids derived directly from the patient or from the PDX models. The in vitro drug responses of PDXOs and PDOs were then compared to defined patient clinical responses: platinum-sensitive (initial response to standard platinum/paclitaxel therapy lasting > 6 months post-treatment), platinum-resistant (initial response to standard chemotherapy lasting < 6 months), or platinum-refractory (no initial response to standard chemotherapy). RESULTS: In drug response assays, PDXOs and PDOs demonstrated similar sensitivity to standard chemotherapy and also reliably reflected patient responses based on the clinical designation of platinum sensitivity. While organoids derived from the ascites were smaller with a denser morphology, their drug response mirrored that of the organoids derived from solid tumor. Platinum-sensitive cases exhibited significant reductions (around 50% reduction) in organoid viability when treated with carboplatin, paclitaxel, or their combination. Platinum-resistant or refractory organoids showed little to no reduction in viability with carboplatin or paclitaxel monotherapy or the combination. Organoids derived from one platinum-resistant case did show a small but significant reduction in viability with single-agent paclitaxel, suggesting that organoid models might predict response to second-line paclitaxel therapy. CONCLUSION: This study demonstrates that PDXOs respond to drugs similarly to PDOs and confirms that both models effectively mirror patient response to standard chemotherapy. This highlights the potential of PDXOs as renewable models for screening novel therapies and developing personalized strategies in OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-025-14811-8.
Influence of visible photon fluxes on reactions of co-adsorbed CO and H on Pt surfaces
Samira, Samji; Marino, Silvia; Jalil, Anika; Gordon, Michael; Christopher, Phillip (2025-06-09)
Tuning Polyacrylate Composition to Recognize and Modulate Fluorescent Proteins
Gomez, Darwin C.; Seth, Swarnadeep; Mondal, Ronnie; Koehler, Stephen J.; Baker, Jared G.; Plate, Charles; Anderson, Ian C.; Smith, Mikayla R.; Gloriod, Joey; Gunter, Morgan; Welborn, Valerie Vaissier; Deshmukh, Sanket A.; Figg, C. Adrian (Wiley-VCH, 2026-01-09)
Molecular definition is usually regarded as a prerequisite to achieve protein recognition and functional modulation, particularly for macromolecular interactions. Herein, we report that polymers with specific combinations of monomers arranged into random sequences [random hetero oligomers (RHOs)] can selectively bind to a model protein. Using green fluorescent protein (GFP) as a target, polyacrylates were developed that bound with nanomolar affinity and enhanced fluorescence by >100%. Purification of the polymerization product revealed subpopulations of compositions with distinct affinities and selectivity for GFP over a competing protein. Experimental and computational binding analyses confirmed that there are distinct RHO–GFP interactions, which are influenced by RHO chemical composition. These findings show that sequence-defined structures are not a prerequisite for selective protein recognition. Synthetic polymers can instead serve as scalable, tunable platforms for molecular recognition—representing a significant leap towards next-generation sensing, therapeutic, responsive, and catalytic materials in domains previously dominated by biologics or complex peptide scaffolds.
Methodology for contamination detection and reduction in fermentation processes using machine learning
Nguyen, Xuan Dung James; Liu, Y. A.; McDowell, Christopher C.; Dooley, Luke (Springer, 2025-09-01)
This paper demonstrates an accurate and efficient methodology for fermentation contamination detection and reduction using two machine learning (ML) methods, including one-class support vector machine and autoencoders. We also optimize as many hyperparameters as possible prior to the training of the ML models to improve the model accuracy and efficiency, and choose a Python platform called Optuna, to enable the parallel execution of hyperparameter optimization (HPO). We recommend using Bayesian optimization with hyperband algorithm to carry out HPO. Results show that we can predict contaminated fermentation batches with recall up to 1.0 without sacrificing the precision and specificity of non-contaminated batches, which read up to 0.96 and 0.99, respectively. One-class support vector machine outperforms autoencoders in terms of precision and specificity even though they both achieve an outstanding recall of 1.0. These models demonstrate high accuracy in detecting contamination without requiring labeled contaminated data and are suitable for integration into real-time fermentation monitoring systems with minimal latency and retraining needs. In addition, we benchmark our ML methods against a traditional threshold-based contamination detection approach (mean ± 3 σ rule) to quantify the added value of using data-driven models. Finally, we identify important independent variables contributing to the contaminated batches and give recommendations on how to regulate them to reduce the likelihood of contamination.
Time-Resolved Killing of Individual Bacterial Cells by a Polycationic Antimicrobial Polymer
Benmamoun, Zachary; Chandar, Prem; Jankolovits, Joe; Ducker, William A. (American Chemical Society, 2024-03-29)
Polycationic polymers are widely studied antiseptics, and their efficacy is usually quantified by the solution concentration required to kill a fraction of a population of cells (e.g., by Minimum Bactericidal Concentration (MBC)). Here we describe how the response to a polycationic antimicrobial varies greatly among members of even a monoclonal population of bacteria bathed in a single common antimicrobial concentration. We use fluorescence microscopy to measure the adsorption of a labeled cationic polymer, polydiallyldimethylammmonium chloride (PDADMAC, M-w approximate to 4 x 10(5) g mol(-1)) and the time course of cell response via a cell permeability indicator for each member of an ensemble of either Escherichia coli, Staphylococcus aureus, or Pseudomonas aeruginosa cells. This is a departure from traditional methods of evaluating synthetic antimicrobials, which typically measure the overall response of a collection of cells at a particular time and therefore do not assess the diversity within a population. Cells typically die after they reach a threshold adsorption of PDADMAC, but not always. There is a substantial time lag of about 5-10 min between adsorption and death, and the time to die of an individual cell is well correlated with the rate of adsorption. The amount adsorbed and the time-to-die differ among species but follow a trend of more adsorption on more negatively charged species, as expected for a cationic polymer. The study of individual cells via time-lapse microscopy reveals additional details that are lost when measuring ensemble properties at a particular time.
Viscosity of Mono- and Polydisperse Mixtures of Photopolymer and Rigid Spheres for Manufacturing of Engineered Composite Materials Using Vat Photopolymerization
Reynolds, John; Unterhalter, John; Francoeur, Mathieu; Bortner, Michael; Raeymaekers, Bart (Wiley-V C H Verlag, 2024-05-01)
Vat photopolymerization (VP) additive manufacturing involves selectively curing low-viscosity photopolymers via exposure to ultraviolet light in a layer-wise fashion. Dispersing filler materials in the photopolymer enables tailored end-use properties, but also increases the viscosity and the timescale associated with interparticle network structural recovery postshear. These rheological properties influence self-leveling and recoating of the liquid photopolymer mixture during VP. Herein, viscosity of photopolymer and rigid spherical glass microparticles (filler) is experimentally determined as a function of filler fraction, filler size distribution (mono- and polydisperse), shear rate, and temperature, which are important VP process parameters. Employing existing viscosity models for mono- and polydisperse polymer mixtures demonstrates that particle-particle interactions and the formation of nonspherical clusters of particles strongly affect the viscosity of both monodisperse and polydisperse mixtures with particle volume fractions > 0.05 due to agglomeration/deagglomeration of clusters at elevated shear rates. Consequently, unmodified viscosity models, which assume uniformly dispersed, rigid, spherical particles, are applicable only for mixtures with particle volume fractions < 0.05. It is shown that modifying model parameters such as the fluidity limit and intrinsic viscosity, which explicitly account for nonspherical clusters of particles, improves agreement between viscosity models and experiments, in particular when using a fractal approach.
Evaluation of Sampling Algorithms Used for Bayesian Uncertainty Quantification of Molecular Dynamics Force Fields
Sose, Abhishek T.; Gustke, Troy; Wang, Fangxi; Anand, Gaurav; Pasupuleti, Sanjana; Savara, Aditya; Deshmukh, Sanket A. (American Chemical Society, 2024-06-26)
New Bayesian parameter estimation methods have the capability to enable more physically realistic and reliable molecular dynamics (MD) simulations by providing accurate estimates of uncertainties of force-field (FF) parameters and associated properties. However, the choice of which Bayesian parameter estimation algorithm to use has not been widely investigated, despite its impact on the effective exploration of parameter space. Here, using a case example of the Embedded Atom Method (EAM) FF parameters, we investigated the ramifications of several of the algorithm choices. We found that Ensemble Slice Sampling (ESS) and Affine-Invariant Ensemble Sampling (AIES) demonstrate a new level of superior performance, culminating in more accurate parameter and property estimations with tighter uncertainty bounds, compared to traditional methods such as Metropolis-Hastings (MH), Gradient Search (GS), and Uniform Random Sampler (URS). We demonstrate that Bayesian Uncertainty Quantification with ESS and AIES leads to significantly more accurate and reliable predictions of the FF parameters and properties. The results suggest that ESS and AIES should be used to obtain more accurate parameter and uncertainty estimations while providing deeper physical insights.
Unraveling Reactivity Origin of Oxygen Reduction at High-Entropy Alloy Electrocatalysts with a Computational and Data-Driven Approach
Huang, Yang; Wang, Shih-Han; Wang, Xiangrui; Omidvar, Noushin; Achenie, Luke E. K.; Skrabalak, Sara E.; Xin, Hongliang (American Chemical Society, 2024-06-29)
High-entropy alloys (HEAs), characterized as compositionally complex solid solutions with five or more metal elements, have emerged as a novel class of catalytic materials with unique attributes. Because of the remarkable diversity of multielement sites or site ensembles stabilized by configurational entropy, human exploration of the multidimensional design space of HEAs presents a formidable challenge, necessitating an efficient, computational and data-driven strategy over traditional trial-and-error experimentation or physics-based modeling. Leveraging deep learning interatomic potentials for large-scale molecular simulations and pretrained machine learning models of surface reactivity, our approach effectively rationalizes the enhanced activity of a previously synthesized PdCuPtNiCo HEA nanoparticle system for electrochemical oxygen reduction, as corroborated by experimental observations. We contend that this framework deepens our fundamental understanding of the surface reactivity of high-entropy materials and fosters the accelerated development and synthesis of monodisperse HEA nanoparticles as a versatile material platform for catalyzing sustainable chemical and energy transformations.
Electrospun Lithium Porous Nanosorbent Fibers for Enhanced Lithium Adsorption and Sustainable Applications
Pan, Yanan; Zhang, Yue; Thompson, Connor; Liu, Guoliang; Zhang, Wencai (American Chemical Society, 2024-09-30)
Electrospun nanosorbent fibers specifically designed for efficient lithium extraction were developed, exhibiting superior physicochemical properties. These fibers were fabricated using a polyacrylonitrile/dimethylformamide matrix, with viscosity and dynamic mechanical analysis showing that optimal interactions were achieved at lower contents of layered double hydroxide. This meticulous adjustment in formulation led to the creation of lithium porous nanosorbent fibers (Li-PNFs-1). Li-PNFs-1 exhibited outstanding mechanical attributes, including a yield stress of 0.09 MPa, a tensile strength of 2.48 MPa, and an elongation at a break of 19.7%. Additionally, they demonstrated pronounced hydrophilicity and hierarchical porous architecture, which greatly favor rapid wetting kinetics and lithium adsorption. Morphologically, they exhibited uniform smoothness with a diameter averaging 546 nm, indicative of orderly crystalline growth and a dense molecular arrangement. X-ray photoelectron spectroscopy and density functional theory using Cambridge Serial Total Energy Package revealed modifications in the spatial and electronic configurations of polyacrylonitrile due to hydrogen bonding, facilitating lithium adsorption capacity up to 13.45 mg/g under optimal conditions. Besides, kinetics and isotherm showed rapid equilibrium within 60 min and confirmed the chemical and selective nature of Li+ uptake. These fibers demonstrated consistent adsorption performance across multiple cycles, highlighting their potential for sustainable use in industrial applications.
Reaction-Type-Dependent Behavior of Redox-Hopping in MOFs-Does Charge Transport Have a Preferred Direction?
Yan, Minliang; Bowman, Zaya; Knepp, Zachary J.; Peterson, Aiden; Fredin, Lisa A.; Morris, Amanda J. (American Chemical Society, 2024-11-21)
Redox hopping is the primary method of electron transport through redox-active metal-organic frameworks (MOFs). While redox hopping adequately supports the electrocatalytic application of MOFs, the fundamental understandings guiding the design of redox hopping MOFs remain nascent. In this study, we probe the rate of electron and hole transport through a singular MOF scaffold to determine whether the properties of the MOF promote the transport of one carrier over the other. A redox center, [RuII(bpy)2(bpy-COOH)]2+, where bpy = 2,2 '-bipyridine and bpy-COOH = 4-carboxy-2,2 '-bipyridine, was anchored within NU-1000. The electron hopping coefficients (D e ) and ion diffusion coefficients (D i ) were calculated via chronoamperometry and application of the Scholz model. We found that electrons transport more rapidly than holes in the studied MOF. Interestingly, the correlation between D e and self-exchange rate built in previous research predicted reversely. The contradicting result indicates that spacing between the molecular moieties involved in a particular hopping process dominates the response.
Gelation during Ring-Opening Reactions of Cellulosics with Cyclic Anhydrides: Phenomena and Mechanisms
Petrova, Stella P.; Zheng, Zhaoxi; Heinze, Daniel Alves; Welborn, Valerie Vaissier; Bortner, Michael J.; Schmidt-Rohr, Klaus; Edgar, Kevin J. (American Chemical Society, 2024-11-21)
Cellulose esters are used in Food and Drug Administration-approved oral formulations, including in amorphous solid dispersions (ASDs). Some bear substituents with terminal carboxyl moieties (e.g., hydroxypropyl methyl cellulose acetate succinate (HPMCAS)); these omega-carboxy ester substituents enhance interactions with drug molecules in solid and solution phases and enable pH-responsive drug release. However, the synthesis of carboxyl-pendent cellulose esters is challenging, partly due to competing reactions between introduced carboxyl groups and residual hydroxyls on different chains, forming either physically or covalently cross-linked systems. As we explored ring-opening reactions of cyclic anhydrides with cellulose and its esters to prepare polymers designed for high ASD performance, we became concerned upon encountering gelation. Herein, we probe the complexity of such ring-opening reactions in detail, for the first time, utilizing rheometry and solid-state 13C NMR spectroscopy. Gelation in these ring-opening reactions was caused predominantly by physical interactions, progressing in some cases to covalent cross-links over time.
Scalable Accelerated Materials Discovery of Sustainable Polysaccharide-Based Hydrogels by Autonomous Experimentation and Collaborative Learning
Liu, Yang; Yue, Xubo; Zhang, Junru; Zhai, Zhenghao; Moammeri, Ali; Edgar, Kevin J.; Berahas, Albert S.; Al Kontar, Raed; Johnson, Blake N. (American Chemical Society, 2024-12-11)
While some materials can be discovered and engineered using standalone self-driving workflows, coordinating multiple stakeholders and workflows toward a common goal could advance autonomous experimentation (AE) for accelerated materials discovery (AMD). Here, we describe a scalable AMD paradigm based on AE and "collaborative learning". Collaborative learning using a novel consensus Bayesian optimization (BO) model enabled the rapid discovery of mechanically optimized composite polysaccharide hydrogels. The collaborative workflow outperformed a non-collaborating AMD workflow scaled by independent learning based on the trend of mechanical property evolution over eight experimental iterations, corresponding to a budget limit. After five iterations, four collaborating clients obtained notable material performance (i.e., composition discovery). Collaborative learning by consensus BO can enable scaling and performance optimization for a range of self-driving materials research workflows driven by optimally cooperating humans and machines that share a material design objective.
Copper Oxidation-Induced Nanoscale Deformation of Electromechanical, Laminate Polymer/Graphene Thin Films during Thermal Annealing: Implications for Flexible, Transparent, and Conductive Electrodes
Croft, Zacary L.; Valenzuela, Oscar; Thompson, Connor; Whitfield, Brendan; Betzko, Garrett; Liu, Guoliang (American Chemical Society, 2024-12-12)
The transfer of large-area, continuous, chemical vapor deposition (CVD)-grown graphene without introducing defects remains a challenge for fabricating graphene-based electronics. Polymer thin films are commonly used as supports for transferring graphene, but they typically require thermal annealing before transfer. However, little work has been done to thoroughly investigate how thermal annealing affects the polymer/graphene thin film when directly annealed on the growth substrate. In this work, we demonstrate that under improper annealing conditions, thermal annealing of poly(ether imide)/single-layer graphene (PEI/SLG) thin films on Cu causes detrimental nanoscale structural deformations, which permanently degrade the mechanical properties. Furthermore, we elucidate the mechanisms of PEI/SLG deformation during thermal annealing and find that permanent deformations and cracking are caused by Cu substrate oxidation. This study provides an understanding of annealing-induced deformation in polymer/graphene thin films. We anticipate that this knowledge will be useful for further developing defect-free, graphene-based thin film electronics.
nMOWChIP-seq: low-input genome-wide mapping of non-histone targets
Liu, Zhengzhi; Naler, Lynette B.; Zhu, Yan; Deng, Chengyu; Zhang, Qiang; Zhu, Bohan; Zhou, Zirui; Sarma, Mimosa; Murray, Alexander; Xie, Hehuang; Lu, Chang (Oxford University Press, 2022-03-31)
Genome-wide profiling of interactions between genome and various functional proteins is critical for understanding regulatory processes involved in development and diseases. Conventional assays require a large number of cells and high-quality data on tissue samples are scarce. Here we optimized a low-input chromatin immunoprecipitation followed by sequencing (ChIP-seq) technology for profiling RNA polymerase II (Pol II), transcription factor (TF), and enzyme binding at the genome scale. The new approach produces high-quality binding profiles using 1,000-50,000 cells. We used the approach to examine the binding of Pol II and two TFs (EGR1 and MEF2C) in cerebellum and prefrontal cortex of mouse brain and found that their binding profiles are highly reflective of the functional differences between the two brain regions. Our analysis reveals the potential for linking genome-wide TF or Pol II profiles with neuroanatomical origins of brain cells.
Dislocation Transformations at the Common 30°⟨0001⟩ Grain Boundaries During Plastic Deformation in Magnesium
Zhu, Yulong; Sun, Yaowu; Huang, An; Wang, Fangxi; Chen, Peng (MDPI, 2025-01-31)
After the thermal-mechanical processing of Mg alloys, extensive 30°⟨0001⟩ grain boundaries (GBs) are present in the recrystallized structure, which strongly affects the mechanical properties via interactions with lattice dislocations. In this work, we systematically investigate how the 30°⟨0001⟩ GBs influence the slip transmission during plastic deformation. We reveal that basal dislocations can be transmuted into its neighboring grain and continue gliding on the basal plane. The prismatic dislocation can transmit the GB remaining on the same Burgers vector. However, a mobile pyramidal c+a dislocation can be absorbed at GBs, initiating the formation of new grain. These findings provide a comprehensive understanding on GB-dislocation interaction in hexagonal close-packed (HCP) metals.
Spinel oxide enables high-temperature self-lubrication in superalloys
Zhang, Zhengyu; Hershkovitz, Eitan; An, Qi; Liu, Liping; Wang, Xiaoqing; Deng, Zhifei; Baucom, Garrett; Wang, Wenbo; Zhao, Jing; Xin, Ziming; Moore, Lowell; Yi, Yao; Islam, Md Rezwan Ul; Chen, Xin; Cui, Bai; Li, Ling; Xin, Hongliang; Li, Lin; Kim, Honggyu; Cai, Wenjun (Nature Research, 2024-11-20)
The ability to lubricate and resist wear at temperatures above 600 °C in an oxidative environment remains a significant challenge for metals due to their high-temperature softening, oxidation, and rapid degradation of traditional solid lubricants. Herein, we demonstrate that high-temperature lubricity can be achieved with coefficients of friction (COF) as low as 0.10-0.32 at 600- 900 °C by tailoring surface oxidation in additively-manufactured Inconel superalloy. By integrating high-temperature tribological testing, advanced materials characterization, and computations, we show that the formation of spinel-based oxide layers on superalloy promotes sustained self-lubrication due to their lower shear strength and more negative formation and cohesive energy compared to other surface oxides. A reversible phase transformation between the cubic and tetragonal/monoclinic spinel was driven by stress and temperature during high temperature wear. To span Ni- and Cr-based ternary oxide compositional spaces for which little high-temperature COF data exist, we develop a computational design method to predict the lubricity of oxides, incorporating thermodynamics and density functional theory computations. Our finding demonstrates that spinel oxide can exhibit low COF values at temperatures much higher than conventional solid lubricants with 2D layered or Magnéli structures, suggesting a promising design strategy for selflubricating high-temperature alloys.
Monitoring Wind and Particle Concentrations Near Freshwater and Marine Harmful Algal Blooms (HABs)
Bilyeu, Landon; Gonzalez-Rocha, Javier; Hanlon, Regina; AlAmiri, Noora; Foroutan, Hosein; Alading, Kun; Ross, Shane D.; Schmale, David G. III (Royal Society of Chemistry, 2023-10-05)
Harmful algal blooms (HABs) are a threat to aquatic ecosystems worldwide. New information is needed about the environmental conditions associated with the aerosolization and transport of HAB cells and their associated toxins. This information is critical to help inform our understanding of potential exposures. We used a ground-based sensor package to monitor weather, measure airborne particles, and collect air samples on the shore of a freshwater HAB (bloom of predominantly Rhaphidiopsis, Lake Anna, Virginia) and a marine HAB (bloom of Karenia brevis, Gulf Coast, Florida). Each sensor package contained a sonic anemometer, impinger, and optical particle counter. A drone was used to measure vertical profiles of windspeed and wind direction at the shore and above the freshwater HAB. At the Florida sites, airborne particle number concentrations (cm−3) increased throughout the day and the wind direction (offshore versus onshore) was strongly associated with these particle number concentrations (cm−3). Offshore wind sources had particle number concentrations (cm−3) 3 to 4 times higher than those of onshore wind sources. A predictive model, trained on a random set of weather and particle number concentrations (cm−3) collected over the same time period, was able to predict airborne particle number concentrations (cm−3) with an R squared value of 0.581 for the freshwater HAB in Virginia and an R squared value of 0.804 for the marine HAB in Florida. The drone-based vertical profiles of the wind velocity showed differences in wind speed and direction at different altitudes, highlighting the need for wind measurements at multiple heights to capture environmental conditions driving the atmospheric transport of aerosolized HAB toxins. A surface flux equation was used to determine the rate of aerosol production at the beach sites based on the measured particle number concentrations (cm−3) and weather conditions. Additional work is needed to better understand the short-term fate and transport of aerosolized cyanobacterial cells and toxins and how this is influenced by local weather conditions.
Chain-length-controllable upcycling of polyolefins to sulfate detergents
Munyaneza, Nuwayo Eric; Ji, Ruiyang; DiMarco, Adrian; Miscall, Joel; Stanley, Lisa; Rorrer, Nicholas; Qiao, Rui; Liu, Guoliang (Springer Nature, 2024-11-18)
Escalating global plastic pollution and the depletion of fossil-based resources underscore the urgent need for innovative end-of-life plastic management strategies in the context of a circular economy. Thermolysis is capable of upcycling end-of-life plastics to intermediate molecules suitable for downstream conversion to eventually high-value chemicals, but tuning the molar mass distribution of the products is challenging. Here we report a temperature-gradient thermolysis strategy for the conversion of polyethylene and polypropylene into hydrocarbons with tunable molar mass distributions. The whole thermolysis process is catalyst- and hydrogen-free. The thermolysis of polyethylene and polyethylene/polypropylene mixtures with tailored temperature gradients generated oil with an average chain length of ~C14. The oil featured a high concentration of synthetically useful α-olefins. Computational fluid dynamics simulations revealed that regulating the reactor wall temperature was the key to tuning the hydrocarbon distributions. Subsequent oxidation of the obtained α-olefins by sulfuric acid and neutralization by potassium hydroxide afforded sulfate detergents with excellent foaming behaviour and emulsifying capacity and low critical micelle concentration. Overall, this work provides a viable approach to producing value-added chemicals from end-of-life plastics, improving the circularity of the anthropogenic carbon cycle.

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