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At least 289 records · Page 16

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗

Analysis of the molecular determinants for furin cleavage of the spike protein S1/S2 site in defined strains of the prototype coronavirus murine hepatitis virus (MHV)

We analyzed the spike protein S1/S2 cleavage of selected strains of a prototype coronavirus, mouse hepatitis virus (MHV) by the cellular protease furin, in order to understand the structural requirements underlying the sequence selectivity of the scissile segment. The probability of cleavage of selected MHV strains was first evaluated from furin cleavage scores predicted by the ProP computer software, and then cleavage was measured experimentally with a fluorogenic peptide cleavage assay consisting of S1/S2 peptide mimics and purified furin. We found that in vitro cleavability varied across MHV strains in line with predicted results—but with the notable exception of MHV-A59, which was not cleaved despite a high score predicted for its sequence. Using the known X-Ray structure of furin in complex with a substrate-like inhibitor as an initial structural reference, we carried out molecular dynamics (MD) simulations to learn the modes of binding of the peptides in the furin active site, and the suitability of the complex for initiation of the enzymatic cleavage. We identified the 3D structural requirements of the furin active site configuration that enable bound peptides to undergo cleavage, and the way in which the various strains tested experimentally are fulfilling these requirements. We find that despite some flexibility in the organization of the peptide bound to the active site of the enzyme, the presence of a histidine at P2 of MHV-A59 fails to properly orient the sidechain of His194 of the furin catalytic triad and therefore produces a distortion that renders the peptide/complex structural configuration in the active site incompatible with requirements for cleavage initiation. The Ser/Thr in P1 of MHV-2 and MHV-S has a similar effect of distorting the conformation of the furin active site residues produced by the elimination of the canonical salt-bridge formed by arginine in P1 position. This work informs a study of coronavirus infection and pathogenesis with respect to the function of the viral spike protein, and suggests an important process of viral adaptation and evolution within the spike S1/S2 structural loop.

60 APPLIED LIFE SCIENCES↗

TCO Analysis Approach and Regional Analysis of dWPT for Class 8 Tractors

Dynamic Wireless Power Transfer (dWPT) is a method by which battery electric vehicles (BEVs) can charge their battery while traveling on the road without the need for a physical conductive connection to the power source. dWPT has been proposed as a strategy to enable a reduction in vehicle battery capacity and associated mass and cost. In this slide deck presented at the EVs@Scale Consortium - Wireless Power Transfer Pillar Deep-Dive Meeting on November 11th, 2023, NREL provides results from an evaluation of dWPT using data from Class 8 tractors driving in the Atlanta Metro Area. NREL selected data for archetypal days representing local, regional, and long-haul trips, defined according to trip length, that included travel on primary roadways. EVI-InMotion (Electric Vehicle Infrastructure - InMotion), a systems planning and optimization tool developed at NREL, was used to evaluate dWPT performance assuming dWPT charging on 120 road segments for a total roadway lane distance of 2,365 miles. The EVI-InMotion results and representative day drive cycles were analyzed with NREL's T3CO (Transportation Technology Total Cost of Ownership) tool to estimate the total cost of ownership (TCO) for scenarios comprising two model years - 2030 and 2040 - and two technology progress cases. TCO was calculated for diesel, fuel cell electric, BEVs with batteries sized assuming no dWPT capabilities, and 200kWh BEVs with dWPT installed. This analysis finds that en-route stationary charging frequency and downtime when not on electrified roadways are the main contributors to TCO for the dWPT vehicles and that these vehicles can achieve cost parity with FCEVs at low electricity costs. Based on the scenario assumptions used here, low electricity costs would further help the cost parity with diesel vehicles in regional and long-haul cases due to stationary fueling downtime. This presentation also concludes that key factors affecting the parity potential of dWPT-capable vehicles include more extensive dWPT road coverage, higher en-route charging power, less expensive power batteries, and higher hydrogen or diesel fuel costs.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Spatially-resolved dynamic sampling of different phasic magnetic resonances of nanoparticle ensembles in a magnetotactic bacterium Magnetospirillum magnetotacticum

Abstract Nanoscaled magnetic particle ensembles are promising building blocks for realizing magnon based binary logic. Element-specific real-space monitoring of magnetic resonance modes with sampling rates in the GHz regime is imperative for the experimental verification of future complex magnonic devices. Here we present the observation of different phasic magnetic resonance modes using the element-specific technique of time-resolved scanning transmission x-ray microscopy within a chain of dipolarly coupled Fe 3 O 4 nanoparticles (40–50 nm particle size) inside a single cell of a magnetotactic bacterium Magnetospirillum magnetotacticum . The particles are probed with 25 nm resolution at the Fe L 3 x-ray absorption edge in response to a microwave excitation of 4.07 GHz. A plethora of resonance modes is observed within multiple particle segments oscillating in- and out-of-phase, well resembled by micromagnetic simulations.

time-resolved scanning transmission x-ray microsco↗

Broken into Pieces: ATLAS and Aliqa Uma as One Single Stream

We present the first spectroscopic measurements of the ATLAS and Aliqa Uma streams from the Southern Stellar Stream Spectroscopic Survey (S 5), in combination with the photometric data from the Dark Energy Survey and astrometric data from Gaia. From the coherence of spectroscopic members in radial velocity and proper motion, we find that these two systems are extremely likely to be one stream with discontinuity in morphology and density on the sky (the “kink” feature). We refer to this entire stream as the ATLAS-Aliqa Uma stream, or the AAU stream. We perform a comprehensive exploration of the effect of baryonic substructures and find that only an encounter with the Sagittarius dwarf ∼0.5 Gyr ago can create a feature similar to the observed “kink.” In addition, we also identify two gaps in the ATLAS component associated with the broadening in the stream width (the “broadening” feature). These gaps have likely been created by small mass perturbers, such as dark matter halos, as the AAU stream is the most distant cold stream known with severe variations in both the stream surface density and the stream track on the sky. With the stream track, stream distance, and kinematic information, we determine the orbit of the AAU stream and find that it has been affected by the Large Magellanic Cloud, resulting in a misalignment between the proper motion and stream track. Together with the Orphan-Chenab Stream, AAU is the second stream pair that has been found to be a single stream separated into two segments by external perturbation.

79 ASTRONOMY AND ASTROPHYSICS↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gravo-aeroelastic scaling of a 13-MW downwind rotor for 20% scale blades

A 105-m, 13-MW two-bladed downwind Segmented Ultralight Morphing Rotor (SUMR-13) blade was gravo-aeroelastically scaled by 20% to a 20.87-m-long demonstrator blade and confirmed through structural ground testing. The subscale model was achieved through geometric scaling and by aeroelastic scaling principles based on operational flapwise deflections combined with rotational and structural frequencies while retaining the turbine tip-speed ratio. In particular, the subscale demonstrator was designed to replicate, as closely as possible, the nondimensional geometry, the ratio of centrifugal to gravitational moments, the tip-speed ratio, and the nondimensional rotation rate. The intent for this demonstrator was to achieve the same nondimensional flapwise blade deflections and dynamics of the full-scale 13-MW rotor. The manufactured SUMR-D blade resulted in less than half of the mass of the conventional two-bladed Controls Advanced Research Turbine (CART2) rotor blade based on scaling and a lower power rating, though with some differences in mass and stiffness from the ideal scaled-down design to meet safety requirements at the test site. To achieve proper scaling, operational pitch control set points were altered to account for the differences by evaluating simulated operation of both the SUMR-13 and SUMR-D rotors. Structural testing of the SUMR-D blade investigated the response to well-defined flapwise loads and indicated that the subscale blade had the appropriate elastic properties needed for both scaling and for safe operational field testing.

17 WIND ENERGY↗

Monitoring Depolymerization in Mesopores Using Dynamic Properties of Polymeric Melt Accessed via Dielectric Spectroscopy

Traditional design principles for heterogeneous catalysis guide the use of catalytic particles with mesosized (∼2–50 nm) pores to increase the number of surface-active sites by way of an increased surface area. However, the entry of long-chain polymers into such pores may be significantly limited by the size and entanglement of polymers in the melt state, thereby decreasing the number of accessible sites. Assessment of catalyst performance from traditional reactor-based studies averages over intrapore reaction events as well as reactions on the surface of a particle, resulting in an inability to distinguish between differences in site accessibility and activity. Techniques that assess the intrapore performance can inform the design of future heterogeneous catalysts for polymer upcycling. In this work, we demonstrate the use of broadband dielectric spectroscopy to monitor depolymerization of a polymer melt within mesopores via changes in the segmental relaxation time scale of amorphous polymer chains. In particular, we highlight the use of an anodic aluminum oxide (AAO) membrane as a readily available model for catalyst pores with a well-characterized pore morphology. The decrease in the segmental relaxation (α-relaxation) time of the melt with increasing chain scission emerges as a measure of the extent of polymer deconstruction inside mesopores. To demonstrate the utility of this technique, we demonstrate the decomposition of two commercial poly(propylene carbonate) polymers with different decomposition rates within mesopores. As the polymers depolymerize, their segmental relaxation time decreases as the molecular weight decreases (as predicted by the Fox–Flory equation). The BDS-measured change in segmental relaxation time mirrors the expected trend based on change in molecular weight measured by size exclusion chromatography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Edge-Guided Polyethylene Crystallization on Monolayer Two-Dimensional Materials

In this report we combine an advanced synthesis of two-dimensional (2D) materials (MoSe 2 ) having well-defined atomic edge configurations with ab initio and atomistic molecular dynamics (MD) simulations to study how atomic edges interact with polyethylene (HDPE) chains in a dilute solution assembly process. Our results reveal that Mo-terminated zigzag (Mo-ZZ) edges act as preferred nucleation sites and strongly interact with HDPE chains. The HDPE chains align in parallel with the Mo-ZZ edges and form arrays of lamellae that are perpendicular to the edges. Interestingly, atomic edge configurations are observed to dramatically change such interactions. The crystallization discrepancy at different edges was demonstrated on the same piece of MoSe 2 with different types of edges. The ab initio and MD simulations between n-alkane (n = 5 and 25), a segment of HDPE, and MoSe 2 suggest that the atomic structures of MoSe 2 can affect their interactions with n-alkane chains. Following the Mo-ZZ edge preferred nucleation principle, controlled long-range alignment of HDPE lamellae can be realized by creating multilayer MoSe 2 with parallel atomic steps. This research opens a pathway toward an atomic level understanding of polymer–2D nanomaterial interactions. It also bridges the gap between atomic-level and long-range mesoscopic structures and introduces a novel strategy for long-range structural control.

36 MATERIALS SCIENCE↗

Sizing Considerations for EV Dynamic Wireless Charging Systems with Integrated Energy Storage

Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.

Lewis, Donovin D.↗

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗

Structural basis for severe pain caused by mutations in the voltage sensors of sodium channel NaV1.7

Voltage-gated sodium channels in peripheral nerves conduct nociceptive signals from nerve endings to the spinal cord. Mutations in voltage-gated sodium channel NaV1.7 are responsible for a number of severe inherited pain syndromes, including inherited erythromelalgia (IEM). Here, we describe the negative shifts in the voltage dependence of activation in the bacterial sodium channel NaVAb as a result of the incorporation of four different IEM mutations in the voltage sensor, which recapitulate the gain-of-function effects observed with these mutations in human NaV1.7. Crystal structures of NaVAb with these IEM mutations revealed that a mutation in the S1 segment of the voltage sensor facilitated the outward movement of S4 gating charges by widening the pathway for gating charge translocation. In contrast, mutations in the S4 segments modified hydrophobic interactions with surrounding amino acid side chains or membrane phospholipids that would enhance the outward movement of the gating charges. These results provide key structural insights into the mechanisms by which these IEM mutations in the voltage sensors can facilitate outward movements of the gating charges in the S4 segment and cause hyperexcitability and severe pain in IEM. Our work gives new insights into IEM pathogenesis at the near-atomic level and provides a molecular model for mutation-specific therapy of this debilitating disease.

60 APPLIED LIFE SCIENCES↗

Rupture Jumping and Seismic Complexity in Models of Earthquake Cycles for Fault Stepovers with Off-Fault Plasticity

ABSTRACT Fault stepovers are prime examples of geometric complexity in natural fault zones that may affect seismic hazard by determining whether an earthquake rupture continues propagating or abruptly stops. However, the long-term pattern of seismicity near-fault stepovers and underlying mechanisms of rupture jumping in the context of earthquake cycles are rarely studied. Leveraging a hybrid numerical scheme combining the finite element and the spectral boundary integral methods, FEBE, we carry out fully dynamic simulations of sequences of earthquakes and aseismic slip for both compressive and tensile stepovers with off-fault plasticity. We consider a rate-and-state friction law for the fault friction and pressure-sensitive Drucker–Prager plasticity for the off-fault bulk response. We observe that the accumulation of plastic deformation, an indication of off-fault damage, is significantly different in the two cases, with more plastic deformation projected in the overlapping region for the tensile stepover. The seismic pattern for a tensile stepover is more complex than for a compressive stepover, and incorporating plasticity also increases complexity, relative to the elastic case. A tensile stepover with off-fault plasticity shows rupture segmentation, temporal clustering, and frequent rupture jumping from one fault to another. These results shed light on possible mechanisms of rupture jumping in fault stepovers as well as the long-term evolution of the fault zone.

Geochemistry & Geophysics↗

Deep learning approaches for instantaneous laser absorptance prediction in additive manufacturing

Abstract The quantification of absorbed light is essential for understanding laser-material interactions and melt pool dynamics in order to minimize defects in additively manufactured metal components. The geometry of a vapor depression formed during laser melting is closely related to laser energy absorption. This relationship has been observed by the state-of-the-art in situ high-speed synchrotron X-ray visualization and integrating sphere radiometry. These two techniques create a temporally resolved dataset consisting of vapor depression images and corresponding laser absorptance. In this work, we propose two different approaches to predict instantaneous laser absorptance. The end-to-end approach uses deep convolutional neural networks to learn implicit features of X-ray images automatically and predict the laser energy absorptance. The two-stage approach uses a semantic segmentation model to engineer geometric features and predict absorptance using classical regression models. While having distinct advantages, both approaches achieved a consistently low mean absolute error of less than 3.3%.

Chemistry↗

Data from "A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans"

Processed LiDAR data and environmental covariates from 2015 and 2019 LiDAR scans in the Vicinity of Snodgrass Mountain (Western Colorado, USA), in a geographic subset used in primary analysis for the research paper.This package contains LiDAR-derived canopy height maps for 2015 and 2019, crown polygons derived from the height maps using a segmentation algorithm, and environmental covariates supporting the model of forest growth. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Colorado Hazard Mapping Program and the Colorado Water Conservation Board. Both datasets adhere to the USGS QL2 quality standard. The point cloud data were processed using the R package lidR to generate a canopy height model representing maximum vegetation height above the ground surface, using a pit-free algorithm.This dataset was compiled to assess how spatial patterns of tree growth in montane and subalpine forests are influenced by water and energy availability. Understanding these growth patterns can provide insight into forest dynamics in the Southern Rocky Mountains under changing climatic conditions.This dataset contains .tif, .csv, and .txt files. This dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Sweep-tracing algorithm: in silico slip crystallography and tension-compression asymmetry in BCC metals

Abstract Direct Molecular Dynamics (MD) simulations are being increasingly employed to model dislocation-mediated crystal plasticity with atomic resolution. Thanks to the dislocation extraction algorithm (DXA), dislocation lines can be now accurately detected and positioned in space and their Burgers vector unambiguously identified in silico, while the simulation is being performed. However, DXA extracts static snapshots of dislocation configurations that by themselves present no information on dislocation motion. Referred to as a sweep-tracing algorithm (STA), here we introduce a practical computational method to observe dislocation motion and to accurately quantify its important characteristics such as preferential slip planes (slip crystallography). STA reconnects pairs of successive snapshots extracted by DXA and computes elementary slip facets thus precisely tracing the motion of dislocation segments from one snapshot to the next. As a testbed for our new method, we apply STA to the analysis of dislocation motion in large-scale MD simulations of single crystal plasticity in BCC metals. We observe that, when the crystal is subjected to uniaxial deformation along its [001] axis, dislocation slip predominantly occurs on the {112} maximum resolved shear stress plane under tension, while in compression slip is non-crystallographic (pencil) resulting in asymmetric mechanical response. The marked contrast in the observed slip crystallography is attributed to the twinning/anti-twinning asymmetry of shears in the {112} planes relatively favoring dislocation motion in the twinning sense while hindering dislocations from moving in the anti-twinning directions.

36 MATERIALS SCIENCE↗

Antielectrophoretic Response-Driven Bending–Tilting Deformation of Cationic Polyelectrolyte Brushes Drives Nonlinear Electroosmotic Transport in Brush-Grafted Nanochannels

In this paper, we use all-atom molecular dynamics (MD) simulations to describe a non-linearly enhanced electroosmotic (EOS) flow, where, in a nanochannel grafted with cationic PMETAC ([Poly(2-(Methacryloyloxy)Ethyl) Trimethylammonium Chloride]) brushes, a two-fold increase in the electric field strength leads to a several-fold (more than two-fold) increase in the EOS flow strength and volume flow rate. The electric field enforces the PMETAC brushes to undergo a bending-tilting driven deformation with a significant portion of the brush layer becoming parallel to the grafting surface. In response, a substantial fraction of the counterions leave the brush layer (hence become more mobile), but instead of going into the bulk, accumulate at the brush-bulk interface, i.e., stay in proximity of the brush segments aligned parallel to the grafting surface. This creates an interesting situation, where the counterions are not completely within the brush layer, yet they fully screen the brush charges. Such “freer” conditions enable the counterions to achieve very high velocity, thereby ensuring that the water solvating the counterions themselves move very fast triggering the significantly augmented EOS transport. Probing deeper we can identify that the bending-tilting driven brush deformation, enforcing the brushes to align parallel to the substrate, results from the anti-electrophoretic behavior of the brushes, where despite being positively charged, the brushes move against the electric field direction. Such an anti-electrophoretic behavior of the PE brushes, which has not been reported before, can be associated with the very fast velocities of the negatively charged counterions and the electrostatic and hydrodynamic coupling of the counterions with the positive functional groups of the brushes. Here, we anticipate that the findings of this paper will shed light on strategies for nanochannel flow, the anti-electrophoretic response of charged polymer chains, and the significance of capturing the detailed chemical architecture of polyelectrolytes in nanoscale science and engineering.

36 MATERIALS SCIENCE↗