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At least 613 records · Page 34

Charge Concentration Limits the Hydrogen Evolution Rate in Organic Nanoparticle Photocatalysts

Colloidal organic nanoparticles have proven to be a promising class of photocatalyst for performing the Hydrogen Evolution Reaction (HER) due to their dispersibility in aqueous environments, their strong absorption within the visible region, and the tunabilty of their component materials' redox potentials. Currently, there is little understanding of how charge generation and accumulation in organic semiconductors change when these materials are formed into nanoparticles that share a high interfacial area with water, nor is it known what mechanism limits the hydrogen evolution efficiency in recent reports on organic nanoparticle photocatalysts. Herein, we use Time-Resolved Microwave Conductivity to study aqueous-soluble organic nanoparticles and bulk thin films composed of various blend ratios of the non-fullerene acceptor EH-IDTBR and conjugated polymer PTB7-Th and examine the relationship between composition, interfacial surface area, charge carrier dynamics, and photocatalytic activity. We quantitatively measure the rate of Hydrogen Evolution Reaction by nanoparticles composed of various donor:acceptor blend ratio compositions and find that the most active blend ratio displays a Hydrogen Quantum Yield of 0.83% per photon. Moreover, we find that nanoparticle photocatalytic activity corresponds directly to charge generation, and that nanoparticles have 3x more long-lived accumulated charges relative to bulk samples of the same material composition. Here these results suggest that, under our current reaction conditions, with approximately 3x solar flux, catalytic activity by these nanoparticles is limited by the concentration of electrons and holes in operando and not a finite number of active surface cites or the catalytic rate at the interface. This provides a clear design goal for the next generation of efficient photocatalytic nanoparticles.

08 HYDROGEN↗

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

Mechanical joint performances of friction self-piercing riveted carbon fiber reinforced polymer and AZ31B Mg alloy

Carbon fiber reinforced polymer (CFRP) and AZ31B Mg alloy were joined by the friction self-piercing riveting (F-SPR) with different steel rivet shank sizes. With the increase of rivet shank size, lap shear fracture load and mechanical interlock distance increased. Ultrafine grains were formed at the joint in AZ31B as a result of dynamic recrystallization, which contributed to the higher hardness. Fatigue life of the CFRP-AZ31B joint was studied at various peak loads of 0.5, 1, 2, and 3 kN and compared with the resistance spot welded AZ31B-AZ31B from the open literature. The fatigue performance was better at higher peak load (>2 kN) and comparable to that of resistance spot welding of AZ31B to AZ31B at lower peak loads (<1 kN). From fractography, the crack initiation for lower peak load (<1 kN) case was observed at the fretting positions on the top and bottom surfaces of AZ31B sheet. When peak load was increased, fretting between the rivet and the top of AZ31B became more dominant to initiate a crack during fatigue testing.

36 MATERIALS SCIENCE↗

Rheological Properties of Small-Molecular Liquids at High Shear Strain Rates

Molecular-scale understanding of rheological properties of small-molecular liquids and polymers is critical to optimizing their performance in practical applications such as lubrication and hydraulic fracking. We combine nonequilibrium molecular dynamics simulations with two unsupervised machine learning methods: principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), to extract the correlation between the rheological properties and molecular structure of squalane sheared at high strain rates (10 6 –10 10 s -1 ) for which substantial shear thinning is observed under pressures P ϵ 0.1–955 MPa at 293 K. Intramolecular atom pair orientation tensors of 435 × 6 dimensions and the intermolecular atom pair orientation tensors of 61 × 6 dimensions are reduced and visualized using PCA and t-SNE to assess the changes in the orientation order during the shear thinning of squalane. Dimension reduction of intramolecular orientation tensors at low pressures P = 0.1,100 MPa reveals a strong correlation between changes in strain rate and the orientation of the side-backbone atom pairs, end-backbone atom pairs, short backbone-backbone atom pairs, and long backbone-backbone atom pairs associated with a squalane molecule. At high pressures P ≥ 400 MPa, the orientation tensors are better classified by these different pair types rather than strain rate, signaling an overall limited evolution of intramolecular orientation with changes in strain rate. Dimension reduction also finds no clear evidence of the link between shear thinning at high pressures and changes in the intermolecular orientation. The alignment of squalane molecules is found to be saturated over the entire range of rates during which squalane exhibits substantial shear thinning at high pressures.

36 MATERIALS SCIENCE↗

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗

Electronic, Ionic, and Mixed Conduction in Polymeric Systems

Polymers that simultaneously transport electrons and ions are paramount to drive the technological advances necessary for next-generation electrochemical devices, including energy storage devices and bioelectronics. However, efforts to describe the motion of ions or electrons separately within polymeric systems become inaccurate when both species are present. In this paper, we highlight the basic transport equations necessary to rationalize mixed transport and the multiscale materials properties that influence their transport coefficients. Potential figures of merit that enable a suitable performance benchmark in mixed conducting systems independent of end application are discussed. Practical design and implementation of mixed conducting polymers require an understanding of the evolving nature of structure and transport with ionic and electronic carrier density to capture the dynamic disorder inherent in polymeric materials.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Anti-polyelectrolyte and polyelectrolyte effects on conformations of polyzwitterionic chains in dilute aqueous solutions

Abstract Polyzwitterions (PZs) are considered as model synthetic analogs of intrinsically disordered proteins. Based on this analogy, PZs in dilute aqueous solutions are expected to attain either globular (i.e. molten, compact) or random coil conformations. Addition of salt is expected to open these conformations. To the best of our knowledge, these hypotheses about conformations of PZs have never been verified. In this study, we test these hypotheses by studying effects of added salt [potassium bromide (KBr)] on gyration and hydrodynamic radii of poly(sulfobetaine methacrylate) in dilute aqueous solutions using dynamic light scattering and small-angle X-ray scattering, respectively. Effects of zwitteration are revealed by direct comparisons of the PZs with the polymers of the same backbone but containing (1) no explicit charges on side groups such as poly(2-dimethylaminoethyl methacrylate)s and (2) explicit cationic side groups with tertiary amino bromide pendants. Zeta-potential measurements, transmission electron microscopy, and ab initio molecular dynamics simulations reveal that the PZs acquire net positive charge in near salt-free conditions due to protonation but retain coiled conformations. Added KBr leads to nonmonotonic changes exhibiting an increase followed by a decrease in radius of gyration (and hydrodynamic radius), which are called antipolyelectrolyte and polyelectrolyte effects, respectively. Charge regulation and screening of charge–charge interactions are discussed in relation to the antipolyelectrolyte and polyelectrolyte effects, respectively, which highlight the importance of salt in affecting net charge and conformations of PZs.

36 MATERIALS SCIENCE↗

Designing a Dynamic Material via Interlocking Kraft Lignin with Ultrahigh Molecular Weight Poly(ethylene oxide)

The environmental issues stemming from plastic waste and the excessive use of petroleum-based chemicals are both concerning and urgent. To effectively address this problem, we need to adopt a comprehensive approach involving developing more sustainable and renewable materials. These materials should be capable of demonstrating similar or even better performance than functional polymers synthesized from petroleum-based chemicals. Our research aims to develop more sustainable materials by leveraging the intrinsic characteristics of a natural polymer, lignin, a byproduct of the biorefinery industries. We utilized the three-dimensional branching structure of lignin as a material framework. We employed an approach to co-reactive melt processing of kraft lignin with aliphatic flexible chains of soft cross-linkers through the reaction of the cross-linker epoxy chain ends with lignin functional groups. Our study demonstrates that the interlocked structure formed from the co-blending of kraft lignin with ultrahigh molecular weight poly(ethylene oxide) and the cross-linking of lignin chains through a solvent-free process can manipulate the macromolecular interactions and relaxation. This manipulation results in materials that exhibit a wide range of thermomechanical properties and self-healing and shape memory effects, with drastically improved stiffness in a single material. We have explored the fundamental understanding of the macromolecular chain relaxation dynamics originating from the interlocking structure formation. In conclusion, this investigation utilized various techniques, including thermal, mechanical, rheology, and quasi-elastic neutron scattering.

36 MATERIALS SCIENCE↗

Cation–polymer interactions and local heterogeneity determine the relative order of alkali cation diffusion coefficients in PEGDA hydrogels

Current research efforts are focused on endowing polymer membranes with ion–ion selectivity by incorporating ion–polymer interactions into materials to bias the selective partitioning and or diffusivity of one species over another. However, little is known about the impact of such interactions on the mechanisms of ion transport. In this study, we probe the influence of cation–polymer interactions on cation, anion, and salt diffusivity in a model membrane material, poly(ethylene glycol) diacrylate (PEGDA) by modeling concentrated polyethylene oxide solutions via molecular dynamics simulations. These results are compared to published experimental data for LiCl, NaCl, and KCl diffusion in PEGDA. Experimentally, the order of salt and cation diffusion coefficients for LiCl, NaCl, and KCl deviate from the order in aqueous solutions. Here, simulations identify these deviations to arise from cation–polymer coordination in the membrane. Both the fraction of bound cations and the average binding lifetime increases with decreasing cation hydration free energy (moving down the alkali series), leading to different diffusivity trends in the membrane compared to solution. However, to recover the experimentally observed order of diffusivities cations and salt in our simulations, we needed to incorporate membrane heterogeneity explicitly via a polymer charge scaling procedure. Together, our results indicate that cation–polymer interactions, as well as spatial heterogeneity within the membrane, play a critical role in dictating the observed order of alkali cation and salt diffusion coefficients in membranes.

36 MATERIALS SCIENCE↗

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗

Underlying Roles of Polyol Additives in Promoting CO2 Capture in PEI/Silica Adsorbents

Solid-supported amines having low molecular weight branched poly(ethylenimine) (PEI) physically impregnated into porous solid supports are promising adsorbents for CO2 capture. Co-impregnating short-chain poly(ethylene glycol) (PEG) together with PEI alters the performance of the adsorbent, delivering improved amine efficiency (AE, mol CO2 sorbed / mol N) and faster CO2 uptake rates. To uncover the physical basis for this improved gas capture performance, we probed the distribution and mobility of the polymers in the pores via small angle neutron scattering (SANS), solid-state NMR, and molecular dynamic (MD) simulation studies. SANS and MD simulations reveal that PEG displaces wall-bound PEI, making amines more accessible for CO2 sorption. Solid-state NMR and MD simulation suggest intercalation of PEG into PEI domains, separating PEI domains and reducing amine-amine interactions, providing potential PEG-rich and amine-poor interfacial domains that bind CO2 weakly via physisorption while providing facile pathways for CO2 diffusion. Contrary to a prior literature hypothesis, no evidence is obtained for PEG facilitating PEI mobility in solid supports. Instead, the data suggest that PEG chains coordinate to PEI, form larger bodies with reduced mobility compared to PEI alone. We also demonstrate promising CO2 uptake and desorption kinetics at varied temperatures, given by favorable amine distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Layer-by-Layer-Processed Organic Solar Cells with 18.02% Efficiency Enabled by Regulating the Aggregation of Bottom Polymers

The fabrication of organic solar cells (OSCs) by a layer-by-layer (LBL) method has attracted growing attention in recent years. As already known, the pre-aggregates of conjugated polymers in solution have a profound impact on their microstructure morphology in films. Herein, by simply controlling the solution temperature and annealing processes, the pre-aggregation behavior of D18 polymer in solution can be fine-tuned and the microstructure of D18 bottom layer is well manipulated. The optimized D18 bottom layer can effectively regulate L8-BO upper-layer-forming suitable networks for efficient charge transportation. In addition, a vertical phase separation with a special D/D:A/A structure (P-i-N-type component distribution) is also formed. As a result, compared to the 16.43% power conversion efficiency (PCE) of the bulk heterojunction devices, such control enables bilayer OSC devices based on the polymer D18 and L8-BO to deliver an enhanced PCE of 18.02% with simultaneously improved short-circuit current density, open-circuit voltage, and fill factor. Importantly, it is also demonstrated in these results that the LBL deposition process utilizing the pre-aggregation of polymer and its fiber-network-forming ability is a very promising approach to improve charge dynamics, suppress carrier recombination, and fabricate highly efficient OSCs.

14 SOLAR ENERGY↗

Enabling Industrial Re-Use of Large-Format Additive Manufacturing Molding and Tooling

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications.

additive manufacturing↗

Topological Effects Near Order–Disorder Transitions in Symmetric Diblock Copolymer Melts

The effects of polymer chain topology on the order–disorder transition of symmetric AB diblock copolymer melts are studied using coarse-grained molecular dynamics simulations. Specifically, we compared chain conformations near the lamellar-disordered transition in melts of symmetric (i.e., 50–50) AB diblock copolymers of linear chains, rings, and trefoil knots at the same chain lengths. The order (lamellar)–disorder transition temperature and the domain sizes both shifted to lower values with the introduction of topological constraints, leading to the following sequence: linear chains > rings > trefoil knots. Furthermore, investigation of the polymer chain conformations in terms of their radii of gyration, their writhe values (a measure for the degree of intertwining of a chain around itself), and their Jones polynomials (a method to measure entanglement of curves) showed that linear chains and rings remained stretched, while knots were stretched and tightened in disordered melts close to the lamellar-disorder transition. This work highlights chain topology as an important factor in affecting microphase separation in block copolymers.

36 MATERIALS SCIENCE↗

A structural and electrochemical study of perfluoropolyether-poly(ethylene oxide) solid polymer electrolytes

Solid polymer electrolytes offer attractive safety, processability, and interfacial adhesion for enabling high–energy solid-state lithium batteries, but they are often limited by narrow oxidative stability windows and low lithium-ion transference numbers. In an attempt to broaden the electrochemical stability window and increase lithium-ion transference number of poly(ethylene oxide) (PEO)-based solid polymer electrolytes, we produce an optically clear, crosslinked membrane of PEO and perfluoropolyether (PFPE) using a mixed solvent method and subsequently infuse the membrane with a lithium salt. Structural and thermal analyses reveal nanoscale phase separation between fluorocarbon and hydrocarbon domains with characteristic spacings of 7–8 nm and an elevated glass transition for the hydrocarbon phase. Consistent with this, PFPE-containing membranes exhibit substantially lower ionic conductivity than PEO analogs (dry and plasticized). The transference number and electrochemical stability are similar to pure PEO. These results demonstrate that fluorination implemented as segregated nanoscale domains does not deliver the anticipated transport or stability benefits; instead, phase separation increases tortuosity and suppresses hydrocarbon-phase dynamics. The work underscores the importance of fluorine placement and morphology control, guiding the design of partially fluorinated solid polymer electrolytes toward architectures that avoid detrimental nanoscale phase separation.

Carden, Peyton [ORNL] (ORCID:0000000162296538)↗

Observations on the deformation of metal microspheres in shock-driven polymer flows

We report that solid particles can be fragmented by a fast-moving fluid if their velocity difference is great enough, such as during the atmospheric entry of meteoroids or the shock compression of engineered particulate composites. The extent of particle deformation and breakup in such systems is poorly understood because the necessary extreme conditions make observation difficult and data scarce. To meet this need, experiments combining ultrafast synchrotron-based radiography with plate impact loading were performed at the dynamic compression sector at the advanced photon source. Metal microspheres of several densities and strengths (Au, Ta, and W) were placed inside a polymer matrix. A planar shock wave was then produced in the polymer by the impact of a gun-launched flyer plate. X-ray images of the resulting flow were collected at ~150ns intervals. These images document the progression of particle deformation across a range of flow conditions and particle materials. They show that the extent of deformation is sensitive to the ratio of drag stress to particle strength. The deforming particle's shape is determined by the initial shock–particle interaction, fluid stagnation pressure, and vorticity, each acting on its own timescale. A set of scaling relationships is presented to capture these observations and enable comparison with prior hydrodynamic data. The result is a framework for predicting the conditions under which strong particles are severely deformed by a shock-driven flow.

36 MATERIALS SCIENCE↗