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Surface-functionalized porous coordination cages can be used to create homogeneous mixed-cage alloys with high levels of tunability and processability.
Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.
The separation of alkane/alkene gas mixtures represents an important yet challenging process in the petrochemical industry to produce valuable chemical feedstocks with sufficiently high purity. These molecules have similar physical properties, making their separation difficult and capital-intensive. The current separation and purification technology relies largely on heat-driven distillations with a huge unit composed of hundreds of trays. Adsorptive separation using porous solids is capable of accomplishing the purification under ambient conditions, offering potential energy and environmental benefits. In particular, metal–organic frameworks (MOFs) hold enormous promise for this separation process in light of their highly tunable pore shape, pore size, and pore surface functionality. In this review article, we provide a comprehensive account of metal–organic frameworks that have been investigated for the separation of alkanes and alkenes with a focus on C 2 –C 3 hydrocarbons. Here, the material design rationale, separation mechanisms, and structure–property relations are highlighted. Finally, the existing challenges and possible design strategies for desirable materials are also discussed.
This work demonstrates the application of pilot-scale surface functionalization of cellulose nanofibrils (CNFs) by aqueous grafting-through polymerization and subsequent spray drying in 3D printed poly(lactic acid) (PLA) composites. Grafted-CNF composites attain an ultimate tensile strength of 88 ± 3 MPa and a tensile modulus of elasticity of 7.8 ± 1.3 GPa in the printing direction at 20 wt% reinforcement loading. These increases, 42% and 139% over neat PLA, respectively, represent the strongest reported 3D printed CNF/PLA composite to date in the literature. The mechanisms behind these improvements are investigated by comparisons to neat PLA and unmodified spray-dried CNF/PLA controls using melt rheology, dynamic mechanical analysis, and assessment of the reinforcement dispersion. These experiments reveal that improved network formation and shear-induced alignment of the grafted CNFs facilitate the remarkable tensile properties of the printed composites.
Characterizing ionization wave propagation in low temperature plasma jets is critical to predicting production of reactive species and plasma–surface interactions for biomedical applications and surface functionalization. In this work, results from optical emission and laser induced fluorescence measurements of the ionization wave in a He plasma jet operating in a controlled gas environment are discussed and used for comparison with numerical modeling. Additionally, the ionization wave was observed using ICCD (Intensified Charge Coupled Device) imaging and characterized by time and spatially resolved electron density measurements using laser-collision-induced fluorescence. The plasma jet was initially characterized using pure He (nominally at 200 Torr), while varying pressure and voltage. When operating in pure He, the ionization wave broadly expands exiting the plasma tube. Increasing the operating pressure reduces the speed and isotropic expansion of the ionization wave. Furthermore, the jet operated with a humid He shroud was also studied. The humid He shroud results in the electron density increasing and having an annular profile due to the lower ionization potential of H2O compared to He and localized photoionization in the mixing region. Numerical modeling highlighted the importance of resonance radiation emitted by excited states of He, photoelectron emission from the quartz tube, and the kinetic behavior of the electrons produced by photoionization ahead of the ionization front.
Metasurfaces offer a compact platform for optical vapor sensing, but their practical deployment has been limited by weak evanescent light–matter interactions and reliance on spectrally resolved instrumentation. Here, we report porous silicon (pSi) metasurfaces for spectrometer-free quantitative detection of volatile organic compounds (VOCs) with strongly enhanced light–matter interaction. The engineered porosity increases sensitivity by >100× relative to non-porous dielectric metasurfaces, enabling limits of detection of 1.65 ppm for methanol and 9.1 ppm for ethanol across a broad dynamic range (<10 ppm to >103 ppm). Imaging-based readout provides a lightweight, spectrometer-free pathway for real-time quantitative sensing. Beyond quantitative detection, the mesoporous architecture introduces adsorption–desorption kinetics as an additional information channel. Analysis of the resulting spatiotemporal signatures enables kinetic fingerprinting without reliance on infrared spectral features or surface functionalization, and a lightweight machine-learning classifier differentiates acetone, methanol, ethanol, and isopropanol with 91.6% accuracy. These results establish porous metasurfaces as spatiotemporal sensing elements that couple quantitative vapor detection with kinetic fingerprinting through real-time dynamical responses, enabling low-cost, high-performance optical sensors.
Lipoarabinomannan (LAM), an amphiphilic lipoglycan of the Mycobacterium tuberculosis cell wall, is a diagnostic target for tuberculosis. Previous work from our laboratory and others suggests that LAM is associated with host serum lipoproteins, which may in turn have implications for diagnostic assays. Our team has developed two serum assays for amphiphile detection: lipoprotein capture and membrane insertion. The lipoprotein capture assay relies on capture of the host lipoproteins, exploiting the biological association of host lipoprotein with microbial amphiphilic biomarkers to “concentrate” LAM. In contrast, the membrane insertion assay is independent of the association between pathogen amphiphiles and host lipoprotein association, and directly captures LAM based on its thermodynamic propensity for association with a supported lipid membrane, which forms the functional surface of an optical biosensor. In this manuscript, we explored the use of these assays for the detection of LAM in sera from adults whose tuberculosis status had been well-characterized using conventional microbiological tests, and endemic controls. Using the lipoprotein capture assay, LAM signal/noise ratios were >1.0 in 29/35 (83%) individuals with culture-confirmed active tuberculosis, 8/13 (62%) individuals with tuberculosis symptoms, but no positive culture for M . tuberculosis , and 0/6 (0%) symptom-free endemic controls. To evaluate serum LAM levels without bias associated with potential differences in circulating host lipoprotein concentrations between individuals, we subsequently processed available samples to liberate LAM from associated host lipoprotein assemblies followed by direct detection of the pathogen biomarker using the membrane insertion approach. Using the membrane insertion assay, signal/noise for detection of serum LAM was greater than that observed using the lipoprotein capture method for culture-confirmed TB patients (6/6), yet remained negative for controls (2/2). Taken together, these results suggest that detection of serum LAM is a promising TB diagnostic approach, but that further work is required to optimize assay performance and to decipher the implications of LAM/host lipoprotein associations for diagnostic assay performance and TB pathogenesis.
As part of the Cyclotron Road program, the participant worked to develop geometric inorganic metamaterial coatings with functional surface energies that approached theoretical minimum. Most coating technologies chemically modify surfaces by applying a fluoropolymer to cause water to bead and roll off the surface, but the metamaterial coatings studied under this project were designed to modify local surface tension of a droplet, such that it pulls down on it at the bottom like a spring and as the droplet grows, the magnitude of the surface tension force increases to overwhelm droplet adhesion forces, causing the droplet to be repelled. These attributes make this technology ideally suited for heat transfer applications. This project’s coating experiments on evaporator coils inside an air conditioning unit demonstrated significant increases in energy efficiency.
The program goal was the development and demonstration of a novel material coating system using an innovative atmospheric cold microwave plasma jet to enable surface functionalization for corrosion protection, wear resistance and improved bonding strength. The technical approach was directed towards proof-of-concept demonstration of advanced point-of-manufacturing material bonding to improve adhesive joint performance subject to harsh environmental exposure. The assembled team, consisting of the researchers at the University of Illinois, end-users at General Motors and small business manufacturer Starfire Industries, successfully demonstrated a single, cost-effective, high-volume production process that meets the requirements of multi-material combinations relevant to the energy-intensive transportation industry (e.g. Al-steel, Mg-steel, Al-Mg and Al-CFRP joints for body-in-white structures) while eliminating offline pretreatment for Al and Mg alloy substrates that are energy intensive, have chemical waste disposal issues, and add cost. Technical demonstration of dissimilar material joining while maintaining bonding strength and cohesion after long-duration environmental exposure was accomplished for all materials of interest. This novel approach has broad applicability for manufacturing in automotive, aerospace, marine, railcar, and specialty consumer goods, etc.
The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.
The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.
The primary goals of the project are a) improve the understanding of transport processes, chemical reactions and plasma-driven self-organization such as stratification and filamentation, formation of anode spots, liquid droplets ejection from cathodes, and plasma electrolysis, b) utilize and share among the project participants computational tools developed by the participants to understand plasma-based surface functionalization and plasma-enabled pattern nucleation in a wide range of scales from nano- to millimeters, and c) use experimental methods and facilities available at the University of Alabama in Huntsville (UAH) and Sandia National Laboratories (SNL) to understand and control plasma processes, reaction pathways and the electric nature of self-organization of the plasma-exposed interface structures.
Polymeric vesicles, characterized by enhanced colloidal stability, excellent mechanical properties, controllable surface functionality, and adjustable membrane thickness, are extremely useful in nano- and bio-technology for potential applications as nanosized carriers for drugs and enzymes. However, a few preparative steps are necessary to achieve a unilamellar vesicle with a narrow size distribution. Herein, we report the spontaneous formation of unilamellar polymeric vesicles with nanometer sizes (<50 nm), fabricated by simply mixing diblock copolymers (P(EO-AGE)(2K-2K) and P(EO-AGE)(0.75K-2K)) with differing hydrophilic mass fractions in aqueous solutions. Depending on the mixing ratio of block copolymers and the temperature, the block copolymer mixtures self-assemble into various nanostructures, such as spherical and cylindrical micelles, or vesicles. The self-assembled structures of the block copolymer mixtures were characterized by small-angle neutron scattering, resulting in a phase diagram drawn as a function of temperature and the mixing condition. Notably, the critical temperature for the micelle-to-vesicle phase transition can be easily controlled by altering the mixing conditions; it decreases with an increase in the concentration of one of the block copolymers.
The design and synthesis of porous carbons for CO 2 adsorption have attracted tremendous interest owing to the ever-soaring concerns regarding climate change and global warming. Herein, for the first time, nitrogen-rich porous carbon was prepared with chemical activation (KOH) of commercial melamine formaldehyde resin (MF) in a single step. It has been shown that the porosity parameters of the as-prepared carbons were successfully tuned by controlling the activating temperature and adjusting the amount of KOH. Thus, as-prepared N-rich porous carbon shows a large surface area of 1658 m 2 /g and a high N content of 16.07 wt%. Benefiting from the unique physical and textural features, the optimal sample depicted a CO 2 uptake of up to 4.95 and 3.30 mmol/g at 0 and 25 °C under 1 bar of pressure. More importantly, as-prepared adsorbents show great CO 2 selectivity over N 2 and outstanding recyclability, which was prominently important for CO 2 capture from the flue gases in practical application. An in-depth analysis illustrated that the synergetic effect of textural properties and surface nitrogen decoration mainly determined the CO 2 capture performance. However, the textural properties of carbons play a more important role than surface functionalities in deciding CO 2 uptake. In view of cost-effective synthesis, outstanding textural activity, and the high adsorption capacity together with good selectivity, this advanced approach becomes valid and convenient in fabricating a unique highly efficient N-rich carbon adsorbent for CO 2 uptake and separation from flue gases.
Provided are polymer-aerogel composite coatings, devices and articles including polymer-aerogel composite coatings, and methods for preparing the polymer-aerogel composite. The exemplary article can include a surface, wherein the surface includes at least one region and a polymer-aerogel composite coating disposed over the at least one region, wherein the polymer-aerogel composite coating has a water contact angle of at least about 140° and a contact angle hysteresis of less than about 1°. The polymer-aerogel composite coating can include a polymer and an ultra high water content catalyzed polysilicate aerogel, the polysilicate aerogel including a three dimensional network of silica particles having surface functional groups derivatized with a silylating agent and a plurality of pores.
Recombinant microorganisms including one or more modifications that enhance lipid production and uses of same for producing lipid. The modifications alter cell surface functions, envelope functions, and other functions. The modifications are capable of converting non-oleaginous microorganisms into oleaginous microorganisms. The lipids produced by some of the recombinant microorganisms are excreted.
A unique fiber core sampler composition, related systems, and techniques for designing, making, and using the same are described. The sampler is used to interface with existing field instrumentation, such as Ion Mobility Spectrometer (IMS) equipment. Desired sampler characteristics include its: stiffness/flexibility; thermal mass and conductivity; specific heat; trace substance collection/release dependability, sensitivity and repeatability; thickness; reusability; durability; stability for thermal cleaning; and the like. In one form the sampler has a glass fiber core with a thickness less than 0.3 millimeter that is coated with a polymer including one or more of: polymeric organofluorine, polyimide, polyamide, PolyBenzlmidazole (PBI), PolyDiMethylSiloxane (PDMS), sulfonated tetrafluoroethylene (PFSA) and Poly(2,6-diphenyl-p-phenylene Oxide) (PPPO). Multiple polymer coatings with the same or different polymer types may be included, core/substrate surface functionalization utilized, and/or the core/substrate may be at partially filled with thermally conductive particles.
The present disclosure relates to a plurality of powder particles configured to be joined in an additive manufacturing process to form a part. Each one of the powder particles has a determined three dimensional, non-spherical shape. The plurality of powder particles are further of dimensions enabling fitting individual ones of the powder particles in abutting relationship with one another. At least a subplurality of the powder particles each have a functionalized surface feature to enhance at least one of clustering or separation of the subplurality of powder particles.