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PARC and PNNL will develop advanced carbon fiber-reinforced polymer (CFRP) materials and manufacturing process that will equip automotive manufacturers with a scalable innovation that reduces costs, improves performance, and accelerates the deployment of CFRP materials across vehicle classes.
Polymer–nanoparticle interactions play an important role in determining the morphology and properties of polymer nanocomposites and controlling the polymeric reactions involving heterogeneous catalysts. Here, in this study, we modulate the interactions between nonpolar polymers and nanoparticles by modifying the nanoparticle surface chemistry and quantify the interaction strength through direct contact angle measurements. We investigate the interactions of three nonpolar polymers, polystyrene, polyethylene, and polycyclooctene, with silica nanoparticles whose surface chemistry has been modified by atomic layer deposition of titania and calcium carbonate and by alkyl silanization. Significant differences in polymer–nanoparticle interactions are observed, which can be attributed to differences in the polarizability of the polymers and oxide surface composition. Compared to fully hydrogenated polycyclooctene, polycyclooctene is shown to have stronger interactions with most metal oxides; however, this trend is reversed following alkyl silanization of the silica nanoparticles, which makes the surface of the particles less polar. These differences in interactions can be leveraged to make polymer nanocomposites with unique properties and enable the selective conversion of polymers without the need for separations.
Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.
The clinical translation of many biomolecular therapeutics has been hindered by undesirable pharmacokinetic (PK) properties, inadequate membrane permeability, poor endosomal escape and cytosolic delivery, and/or susceptibility to degradation. Overcoming these challenges merits the development of nanoscale drug carriers (nanocarriers) to improve the delivery of therapeutic cargo. Herein, we implement a flash nanoprecipitation (FNP) approach to produce nanocarriers of diverse vesicular morphologies by using various molecular weight PEG-bl-DEAEMA-co-BMA (PEG-DB) polymers. We demonstrated that FNP can produce uniform (PDI < 0.1) particles after 5 impingements, and that by varying the copolymer hydrophilic mass fraction, FNP enables access to a diverse variety of nanoarchitectures including micelles, unilamellar vesicles (polymersomes), and multi-compartment vesicles (MCVs). We synthesized a library of 2 kDa PEG block copolymers, with DEAEMA-co-BMA second block molecular weights of 3, 6, 12, 15, 20, and 30 kDa. All formulations were both pH responsive, endosomolytic, and capable of loading and cytosolically delivering small negatively charged molecules – albeit to different degrees. Using a B16.F10 melanoma model, we showcased the therapeutic potential of a lead FNP formulated PEG-DB nanocarrier, encapsulating the cyclic dinucleotide (CDN) cGAMP to activate the stimulator of interferon genes (STING) pathway in a therapeutically relevant context. Collectively, these data demonstrate that an FNP process can be used to formulate pH-responsive nanocarriers of diverse morphologies using a PEG-DB polymer system. As FNP is an industrially scalable process, these data address the critical translational challenge of producing PEG-DB nanoparticles at scale. Furthermore, the diverse morphologies produced may specialize in the delivery of distinct biomolecular cargos for other therapeutic applications, implicating the therapeutic potential of this platform in an array of disease applications.
Commercially available particulate amendments demonstrate high reactivity for effective treatment of water soluble organic and inorganic contaminants in laboratory studies; however, transport of these particles is constrained in the subsurface. In many field applications, particulate amendments are mixed with organic polymers to enhance mobility for direct push applications or stabilize suspensions for high mass loadings. As such, the interactions between particulate amendments, organic polymers and contaminant species need to be systematically investigated to properly understand mechanistic processes that facilitate predictive performance metrics for specific applications in situ . In this study, batch experiments were conducted to quantify the effects of organic polymers (xanthan gum, guar gum, and sodium alginate), polymer concentration (800 and 4,000 mg/L), and aging (up to 28 days) on chromate treatment rate and capacity by two classes of amendments: reductants [granular zero-valent iron (gZVI), micron-ZVI (mZVI), sulfur modified iron (SMI)], and an adsorbent (bismuth sub-nitrate). When particulate amendments were suspended in polymer solutions, reductants retained between 84–100% of the amendment treatment capacity. Conversely, the adsorbent maintained 63–97% relative treatment capacity of the no-polymer control. Polymer solutions had a more pronounced impact on the rate of chromate removal; first order rates of chemical reduction decreased by as much as 70% and adsorption by up to 81% relative to the no-polymer controls. Polymer–amendment aging experiments also showed decreased Cr(VI) treatment capacity; reductants decreased by as much as 24% and adsorption decreased by as much as 44% after 28 days of incubation. While polymer suspensions are needed to aid the injection of particulate amendments into the subsurface, the results from this study indicate potential losses of treatment capacity and a decrease in the rate of remedial performance due to the physical and chemical interactions between polymer suspensions and reactive particulate amendments. Simple batch systems provide baseline characterization of tripartite interactions for the removal of Cr(VI). Additional work is needed to quantify the full impact of polymers on remedial outcomes under site relevant conditions at field scale.
Flotation has been effectively demonstrated as a low footprint, high efficiency separation process when utilising simple anionic surface modifying agents such as sodium dodecyl sulphate (SDS). These agents increase hydrophobicity to remove suspended cationic surface charged particulates such as Mg(OH){sub 2} from waste suspensions similar to those at British nuclear fuel management sites- where corrosion processes have degraded fuel cladding. The technology is advantageous as it could effectively be retrofitted into existing waste management facilities at nuclear waste management sites such Sellafield and Hanford as the simplicity (no moving parts) and size of this technology coupled with low cost of construction could be rapidly deployed to aid in risk and hazard reduction decommissioning operations with minimum impact to secondary waste generation. Previously, sodium dodecyl sulphate has been deployed as a collector agent to increase the hydrophobicity of Mg(OH){sub 2} suspended particles, achieving a maximum particulate extraction percentage of 93%. To achieve further particulate extraction, flotation performance has been determined to be a function of the hydrodynamic limitations extracting fine material (>20 μm). Fine particulates have been shown in the minerals industry to have an inability to overcome slipstreams created from rising bubbles in flotation cells, likely due to the low mass and thus momentum of the colloidal material, preventing interaction between the hydrophobized particles and air-water interfaces (bubbles). To combat this mass transfer resistance poly(acrylic acid)-block-poly(n-butyl acrylate) amphiphilic diblock copolymers were synthesised via reversible addition-fragmentation chain-transfer (RAFT) polymerisation. The anticipated mode of action of these polymers involves the hydrophilic poly(acrylic acid) block polymer acting as a flocculation agent to increase the mass of the aggregates, and the hydrophobic poly(n-butyl acrylate) modifies the hydrophobicity of the resulting flocs. The concentration of this polymer (termed a macro-collector) was varied and the change in particle size distribution of the particulate suspension was analysed using static light scattering. The flotation performance was then characterised by several methods including percentage particulate recovery, volume reduction factor and residual bulk particulate concentration. This was then benchmarked against the traditional surfactant collector agent SDS. (authors)
Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.
A variety of electrochemical energy conversion technologies, including fuel cells, rely on solution-processing techniques (via inks) to form their catalyst layers (CLs). The CLs are heterogeneous structures, often with uneven ion-conducting polymer (ionomer) coverage and underutilized catalysts. Various platinum-supported-on-carbon colloidal catalyst particles are used, but little is known about how or why changing the primary particle loading (PPL, or the weight fraction of platinum of the carbon-platinum catalyst particles) impacts performance. Here, by investigating the CL gas-transport resistance and zeta-potentials of the corresponding inks as a function of PPL, a direct correlation between the CL high current density performance and ink zeta-potential is observed. This correlation stems from likely changes in ionomer distributions and catalyst-particle agglomeration as a function of PPL, as revealed by pH, zeta-potential, and impedance measurements. These findings are critical to unraveling the ionomer distribution heterogeneity in ink-based CLs and enabling enhanced Pt utilization and improved device performance for fuel cells and related electrochemical devices.
Disclosed are methods and systems of providing carbon nanotubes decorated with polymer coated metal nanoparticles. Then, annealing the metal coated carbon nanotubes to reduce a quantity of hydrophilic components of the polymer coating.
Solid polymer and perovskite-type ceramic electrolytes have both shown promise in advancing solid-state lithium metal batteries. Despite their favorable interfacial stability against lithium metal, polymer electrolytes face issues due to their low ionic conductivity and poor mechanical strength. Highly conductive and mechanically robust ceramics, on the other hand, cannot physically remain in contact with redox-active particles that expand and contract during charge-discharge cycles unless excessive pressures are used. To overcome the disadvantages of each material, polymer-ceramic composites can be formed; however, depletion interactions will always lead to aggregation of the ceramic particles if a homopolymer above its melting temperature is used. In this study, we incorporate Li 0.33 La 0.56 TiO 3 (LLTO) nanoparticles into a block copolymer, polystyrene- b -poly (ethylene oxide) (SEO), to develop a polymer-composite electrolyte (SEO-LLTO). TEMs of the same nanoparticles in polyethylene oxide (PEO) show highly aggregated particles whereas a significant fraction of the nanoparticles are dispersed within the PEO-rich lamellae of the SEO-LLTO electrolyte. We use synchrotron hard x-ray microtomography to study the cell failure and interfacial stability of SEO-LLTO in cycled lithium-lithium symmetric cells. Three-dimensional tomograms reveal the formation of large globular lithium structures in the vicinity of the LLTO aggregates. Encasing the SEO-LLTO between layers of SEO to form a “sandwich” electrolyte, we prevent direct contact of LLTO with lithium metal, which allows for the passage of seven-fold higher current densities without signatures of lithium deposition around LLTO. We posit that eliminating particle clustering and direct contact of LLTO and lithium metal through dry processing techniques is crucial to enabling composite electrolytes.
A new silicon-strip-type detector was developed for precise charged-particle tracking in the central rapidity region of heavy ion collisions. A new detector and collaboration at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory is sPHENIX, which is a major upgrade of the PHENIX detector. The intermediate tracker (INTT) is part of the advanced tracking system of the sPHENIX detector complex together with a CMOS monolithic-active-pixel-sensor based silicon-pixel vertex detector, a time-projection chamber, and a micromegas-based detector. The INTT detector is barrel shaped and comprises 56 silicon ladders. Two different types of strip sensors of 78 micron pitch and 320 micron thick are mounted on each half of a silicon ladder. Each strip sensor is segmented into 8 × 2 and 5 × 2 blocks with lengths of 16 and 20 mm. Strips are read out with a silicon strip-readout (FPHX) chip. In order to transmit massive data from the FPHX to the down stream readout electronics card (ROC), a series of long and high speed readout cables were developed. This document focuses on the silicon ladder, the readout cables, and the ROC of the INTT. The radiation hardness is studied for some parts of the INTT devices in the last part of this document, since the INTT employed some materials from the technology frontier of the industry whose radiation hardness is not necessarily well known.
Halide perovskite heterostructures offer promising interfacial interactions for energy conversion, yet challenges in synthesizing structurally well-defined systems limit detailed investigations into structure–property relationships. In this article, we report the synthesis of compositionally controlled 3D/3D and 3D/2D halide perovskite heterostructures using evaporation crystallization-polymer pen lithography (EC-PPL) and a single-particle analysis of their properties. By systematically varying A-site cation combinations and crystal dimensions, we show that heterointerfaces induce local lattice distortions that modulate vibrational dynamics and electron-phonon coupling. These interfacial effects result in significantly extended carrier lifetimes compared to compositionally similar pure phases. Raman spectroscopy, temperature-dependent photoluminescence, and power-dependent emission analysis reveal that localized structural modulations at the interface govern exciton-phonon interactions. These effects are magnified in smaller crystals due to increased interfacial contributions. Our findings highlight the critical role of interface-driven lattice control in tuning the optoelectronic properties of halide perovskites and provide design principles for engineering heterostructures in next-generation optoelectronic devices.
Abstract Binder Jet Additive Manufacturing (BJAM) is a versatile AM technique that can form parts from a variety of powdered materials including metals, ceramics, and polymers. BJAM utilizes inkjet printing to selectively bind these powder particles together to form complex geometries. Adoption of BJAM has been limited due to its inability to form strong green parts using conventional binders. We report the discovery of a versatile polyethyleneimine (PEI) binder for silica sand that doubled the flexural strength of parts to 6.28 MPa compared with that of the conventional binder, making it stronger than unreinforced concrete (~4.5 MPa) in flexural loading. Furthermore, we demonstrate that PEI in the printed parts can be reacted with ethyl cyanoacrylate through a secondary infiltration, resulting in an increase in flexural strength to 52.7 MPa. The strong printed parts coupled with the ability for sacrificial washout presents potential to revolutionize AM in various applications including construction and tooling.
Membranes, methods of making the membranes, and methods of using the membranes are described herein. The membranes can comprise a gas permeable support layer, an inorganic layer disposed on the support, the inorganic layer comprising a plurality of discreet nanoparticles having an average particle size of less than 1 micron, and a selective polymer layer disposed on the inorganic layer, the selective polymer layer comprising a selective polymer having a CO2:N2 selectivity of at least 10 at 57° C. In some embodiments, the membrane can be selectively permeable to an acidic gas. The membranes can be used, for example, to separate gaseous mixtures, such as flue gas.
Increasing demand for high-purity fine chemicals and a drive for process intensification of large-scale separations have driven significant work on the development of highly engineered porous materials with promise for sorption-based separations. While sorptive separations in porous materials offer energy-efficient alternatives to longstanding thermal-based methods, the particulate nature of many of these sorbents has sometimes limited their large-scale deployment in high-throughput applications such as gas separations, for which the necessary high feed flow rates and gas velocities accrue prohibitive operational costs. These processability limitations have been historically addressed through powder shaping methods aimed at the fabrication of structured sorbent contactors based on pellets, beads or monoliths, commonly obtained as extrudates. These structures overcome limitations such as elevated pressure drops commonly recorded across powder adsorption beds but often accrue thermal limitations arising from elevated particle density and aggregation, which ultimately cap their maximum separation performance. Furthermore, the harsh mechanical strain to which powder particles are subjected during contactor fabrication, in the form of extrusion/compression forces, can result in partial pore occlusion and framework degradation, further limiting their performance. Here, we present the development of porous fiber sorbents as an alternative sorbent contactor design capable of addressing sorbent processability limitations while enabling an array of performance-maximizing heat integration capabilities. This new sorbent form factor leverages pre-existing know-how from hollow fiber spinning to produce fiber-shaped sorbent contactors through the phase inversion of known polymers in a process known as dry-jet/wet quenching. The process of phase inversion allows microporous sorbent particles to be latched onto a macroporous polymer matrix under mild processing conditions, thus making it compatible with soft porous materials prone to amorphization under traditional pelletization conditions. Sorbent fibers can be created with different geometries through control of the spinning apparatus and process, offering the possibility to produce monolithic and hollow fibers alike, the latter of which can be integrated with thermalization fluid flows. In this Account, we summarize our progress in the field of fiber sorbents from both design and application standpoints. We further guide the reader through the evolution of this field from the early inceptive work on zeolite hollow fibers to recent developments on MOF fibers. We highlight the versatile nature of fiber sorbents, both from the composition, fabrication and structure points of view, and further demonstrate how fiber sorbents offer alternative paths in tackling new and challenging chemical separation challenges like direct air capture (DAC), with a final perspective on the future of the field.
Modeling of packed-bed microwave reactors relies on an accurate representation of particle size, shape, and distribution within the bed, as well as the particles' dielectric properties. The measured permittivity of microwave susceptors (powders or structured materials) depends on the geometric features of the particles and the porosity of the bed, as well as the specific form factor of a structured material. These are effective properties and cannot be used to analyze other reactor configurations unless the geometric effects are removed. Therefore, we introduce a methodology for extracting the intrinsic particle permittivity from experimentally measured effective permittivity by combining cavity-based measurements with multiscale simulations and machine learning. Further, we develop the first multiscale model of packed-bed microwave reactors that incorporate particle effects (geometric features, random packing, and particle contact). This approach bridges macroscopic observables with mesoscopic physics, enabling analysis of local hotspots, arcing, and contact effects that control reactor performance. Using polymer-based spherical activated carbon (PBSAC) and silicon carbide (SiC) as examples, we demonstrate that the inferred particle permittivity is consistent with independent experimental heating profiles we collect from microwave reactors without adjustable parameters. Finally, this methodology establishes a foundation for predictive, multiscale design of microwave packed-bed reactors that explicitly accounts for particle-scale effects, enabling the estimation of intrinsic permittivity for the first time.
Mixed matrix materials (MMMs) containing nanofillers dispersed in continuous polymer matrices have emerged as an exciting and versatile platform to develop membranes with superior CO 2 /N 2 separation performance for post-combustion carbon capture. Both polymers and nanofillers can be vertically designed and engineered to combine the advantages of excellent processability (derived from polymers) and strong size-sieving ability or/and significant permanent porosity (originated from nanofillers). However, the MMMs face major challenges, such as interfacial incompatibility, particle agglomeration, and poor thin-film formability. This report provides a comprehensive yet critical review of various polymers and nanofillers (such as metal-organic frameworks, covalent organic frameworks, and two-dimensional materials) with promising CO 2 /N 2 separation properties. We exhaustively describe strategies to improve interfacial compatibility, such as in situ syntheses of polymers and nanofillers and functionalization of both components to improve adhesion. Moreover, we highlight various approaches to engineer the MMMs into thin-film composite (TFC) membranes. The review reveals the structure/property relationship in these MMMs and outlines the challenges and opportunities to realize their potential for practical applications.
A thermally insulating composition comprising hollow spherical silica particles and a coating of a material having a thermal conductivity of less than 0.3 W/m·K on surfaces of said silica particles. In particular embodiments, the low conductivity coating material may be a polymer, such as polystyrene or polyvinylpyrrolidone, or the low conductivity coating material may be a quaternary ammonium salt of the Formula (1), i.e., R1R2R3R4N+A−, with at least one of R1, R2, R3, and R4 being an alkyl group containing at least ten carbon atoms (and A− is a counter anion), or the low conductivity coating material may be phenyl-C61-butyric acid methyl ester covalently bound to the hollow spherical silica particles. Also described herein is a method of thermally insulating a surface by applying a coating of the thermally insulating composition, described above, onto the surface.