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At least 109 records · Page 6

Toward accurate prediction of partial-penetration laser weld performance informed by three-dimensional characterization – Part II: μCT based finite element simulations

The mechanical behavior of partial-penetration laser welds exhibits significant variability in engineering quantities such as strength and apparent ductility. Understanding the root cause of this variability is important when using such welds in engineering designs. In Part II of this work, we develop finite element simulations with geometry derived from micro-computed tomography (μCT) scans of partial-penetration 304L stainless steel laser welds that were analyzed in Part I. We use these models to study the effects of the welds’ small-scale geometry, including porosity and weld depth variability, on the structural performance metrics of weld ductility and strength under quasi-static tensile loading. We show that this small-scale geometry is the primary cause of the observed variability for these mechanical response quantities. Additionally, we explore the sensitivity of model results to the conversion of the μCT data to discretized model geometry using different segmentation algorithms, and to the effect of small-scale geometry simplifications for pore shape and weld root texture. The modeling approach outlined and results of this work may be applicable to other material systems with small-scale geometric features and defects, such as additively manufactured materials.

36 MATERIALS SCIENCE↗

Partial inhibition of activin receptor-like kinase 4 alleviates bladder fibrosis caused by bladder outlet obstruction

The bladder undergoes profound structural alterations after bladder outlet obstruction (BOO), characterized by hypertrophy of the bladder wall and accumulation of extracellular matrix (ECM). Transforming growth factor-β (TGF-β) has been found to promote fibrosis of the bladder induced by partial bladder outlet obstruction (pBOO). Activin receptor-like kinase 4 (ALK4) is a downstream receptor of the TGF-β superfamily. However, the role of the ALK4–Smad2/3 pathway in the pathogenesis of bladder fibrosis caused by pBOO remains unknown. This study focused on learning the role of ALK4 in the process of bladder fibrosis caused by pBOO. The pBOO mice models showed that ALK4 expression was found to upregulate in the wild-type bladder 6 weeks after pBOO compared to control group. Then, mice with heterozygous knockout of the ALK4 gene (ALK4+/−) were generated. Histological analysis and Western blot (WB) results showed significant suppression of collagen expression in the bladders of ALK4+/− mice after pBOO compared with WT mice. WB also showed that ALK4+/− mice demonstrated significant suppression of phosphorylated Smad2/3 (p-Smad2/3) expression in the bladder 6 weeks after pBOO but not of phosphorylated extracellular signal-regulated kinase, c-Jun N-terminal kinase or protein 38 (p-ERK, p-JNK, p-P38) expression. This effect might have occurred through partial inactivation of the Smad2/3 signaling pathway. In vitro, ALK4 overexpression promoted collagen production in cultured BSMCs and activated the Smad2/3 signaling pathway. Taken together, our results demonstrated that ALK4 insufficiency alleviated bladder fibrosis in a mouse model of pBOO partly by suppressing Smad2/3 activity.

60 APPLIED LIFE SCIENCES↗

Determining Partial Atomic Charges for Liquid Water: Assessing Electronic Structure and Charge Models

Partial atomic charges provide an intuitive and efficient way to describe the charge distribution and the resulting intermolecular electrostatic interactions in liquid water. Many charge models exist and it is unclear which model provides the best assignment of partial atomic charges in response to the local molecular environment. In this work, we systematically scrutinize various electronic structure methods and charge models (Mulliken, natural population analysis, CHelpG, RESP, Hirshfeld, Iterative Hirshfeld, and Bader) by evaluating their performance in predicting the dipole moments of isolated water, water clusters, and liquid water as well as charge transfer in the water dimer and liquid water. Although none of the seven charge models is capable of fully capturing the dipole moment increase from isolated water (1.85 D) to liquid water (about 2.9 D), the Iterative Hirshfeld method performs best for liquid water, reproducing its experimental average molecular dipole moment, yielding a reasonable amount of intermolecular charge transfer, and showing modest sensitivity to the local water environment. The performance of the charge model is dependent on the choice of the density functional and the quantum treatment of the environment. The computed molecular dipole moment of water generally increases with the percentage of the exact Hartree–Fock exchange in the functional, whereas the amount of charge transfer between molecules decreases. For liquid water, including two full solvation shells of surrounding water molecules (within about 5.5 Å of the central water) in the quantum chemical calculation converges the charges of the central water molecule. Furthermore, our final pragmatic quantum chemical charge-assigning protocol for liquid water is the Iterative Hirshfeld method with M06-HF/aug-cc-pVDZ and a quantum region cutoff radius of 5.5 Å.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ion Correlations and Partial Ionicities in the Lamellar Phases of Block Copolymeric Ionic Liquids

Recently, significant interest has arisen on the impact of dynamical ion correlations on the conductivity and transport properties of polymeric electrolyte materials. It has been hypothesized that confining ion motion to narrow channels may reduce such ion correlations and enhance the resulting ionic conductivity. Motivated by such considerations, in this study we used a multiscale simulation framework to study the dynamical ion correlations in the microphase-separated lamella phase of block copolymeric ionic liquids and compare with the corresponding results for homopolymeric systems. We probed the influence of ion correlations through the partial ionicity, Δ, which quantifies the ratio of true conductivity to the ideal, Nernst–Einstein conductivity for the anion-related contributions. Consistent with our original hypothesis, our results demonstrate that the partial ionicity relating to the mobile anions is much larger in the lamella phases of block copolymers compared to that in homopolymers. Analysis of the distinct conductivity contributions demonstrates that such results arise as a result of an intricate compensation among the nonideal dynamical correlations relating to anions in lamella phases. Overall, our results suggest that self-assembled phases of block copolymers may provide an avenue to tune the dynamical ion correlations in polymer electrolyte systems.

36 MATERIALS SCIENCE↗

Can We Rely on Satellite Visible/Infrared Microphysical Retrievals of Boundary Layer Clouds in Partially Cloudy Scenes? Implications for Climate Research

This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (τ) and droplet effective radius (r e ) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP r e substantially improves when the retrievals are averaged after removing pixels with τ < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of r e , and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.

Painemal, David [NASA Langley Research Center, Ham↗

Restoring Historic Forest Disturbance Frequency Would Partially Mitigate Droughts in the Central Sierra Nevada Mountains

Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate the water resource impacts of forest management scenarios targeting partial or full restoration of the pre-colonial disturbance return interval in the central Sierra Nevada mountains. In a fully restored disturbance regime that includes fire, thinning, and insect mortality, reservoir inflow increases by 4%–9% total and 8%–14% in dry years. At sub-watershed scales (10–100 km2), thinning dense forests can increase streamflow by >20% in dry years. In a thinner forest, increased understory transpiration compensates for decreased overstory transpiration. Consequentially, 73% of streamflow gains are attributable to decreased overstory rain and snow interception loss. Thinner forests can increase headwater peak flows, but reservoir-scale peak flows are almost exclusively influenced by climate. Uncertainty in future precipitation causes high uncertainty in future water yield, but the additional water yield attributable to forest disturbance is about five times less sensitive to annual precipitation uncertainty. This partial decoupling of the streamflow disturbance response from annual precipitation makes disturbance especially valuable for water supply during dry years. Our study can increase confidence in the water resource benefits of restoring historic forest disturbance frequencies in the central Sierra Nevada mountains, and our modeling framework is widely applicable to other forested mountain landscapes.

Boardman, Eli N. [University of Nevada, Reno, NV (↗

Learning emergent partial differential equations in a learned emergent space

We propose an approach to learn effective evolution equations for large systems of interacting agents. This is demonstrated on two examples, a well-studied system of coupled normal form oscillators and a biologically motivated example of coupled Hodgkin-Huxley-like neurons. For such types of systems there is no obvious space coordinate in which to learn effective evolution laws in the form of partial differential equations. In our approach, we accomplish this by learning embedding coordinates from the time series data of the system using manifold learning as a first step. In these emergent coordinates, we then show how one can learn effective partial differential equations, using neural networks, that do not only reproduce the dynamics of the oscillator ensemble, but also capture the collective bifurcations when system parameters vary. The proposed approach thus integrates the automatic, data-driven extraction of emergent space coordinates parametrizing the agent dynamics, with machine-learning assisted identification of an emergent PDE description of the dynamics in this parametrization.

97 MATHEMATICS AND COMPUTING↗

Spin-resolved topology and partial axion angles in three-dimensional insulators

Abstract Symmetry-protected topological crystalline insulators (TCIs) have primarily been characterized by their gapless boundary states. However, in time-reversal- ( $${{{{{{{\mathcal{T}}}}}}}}$$ T -) invariant (helical) 3D TCIs—termed higher-order TCIs (HOTIs)—the boundary signatures can manifest as a sample-dependent network of 1D hinge states. We here introduce nested spin-resolved Wilson loops and layer constructions as tools to characterize the intrinsic bulk topological properties of spinful 3D insulators. We discover that helical HOTIs realize one of three spin-resolved phases with distinct responses that are quantitatively robust to large deformations of the bulk spin-orbital texture: 3D quantum spin Hall insulators (QSHIs), “spin-Weyl” semimetals, and $${{{{{{{\mathcal{T}}}}}}}}$$ T -doubled axion insulator (T-DAXI) states with nontrivial partial axion angles indicative of a 3D spin-magnetoelectric bulk response and half-quantized 2D TI surface states originating from a partial parity anomaly. Using ab-initio calculations, we demonstrate that β -MoTe 2 realizes a spin-Weyl state and that α -BiBr hosts both 3D QSHI and T-DAXI regimes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Total X-ray scattering and big-box modeling of pressure-induced local disorder and partial amorphization in CsPbBr 3

The mechanisms governing pressure-induced amorphization and its reversibility in halide perovskites are not yet fully understood, particularly the contribution of local disorder. We performed high-pressure synchrotron total X-ray scattering and reverse Monte Carlo (RMC) big-box modeling using CsPbBr 3 as a model system to investigate short-range structural evolution in both the ordered and partially amorphous phases. While diffraction data indicate that long-range order persists up to 2 GPa, pair distribution function (PDF) analysis reveals significant local distortions, including PbBr 6 octahedral tilting and Cs displacement, which influence the bandgap through a complex interplay between bond compression and angular tilting. Beyond 2 GPa, CsPbBr 3 undergoes partial amorphization, with significant disordering of Cs and Br, while the Pb sublattice remains preserved, allowing for structural recovery upon decompression. Our work, accounting for both short- and long-range structural evolution through RMC modeling, successfully captures how disorder shapes the structural response of halide perovskites under pressure.

critical phenomena↗

Gut microbiome partially mediates and coordinates the effects of genetics on anxiety-like behavior in Collaborative Cross mice

Abstract Growing evidence suggests that the gut microbiome (GM) plays a critical role in health and disease. However, the contribution of GM to psychiatric disorders, especially anxiety, remains unclear. We used the Collaborative Cross (CC) mouse population-based model to identify anxiety associated host genetic and GM factors. Anxiety-like behavior of 445 mice across 30 CC strains was measured using the light/dark box assay and documented by video. A custom tracking system was developed to quantify seven anxiety-related phenotypes based on video. Mice were assigned to a low or high anxiety group by consensus clustering using seven anxiety-related phenotypes. Genome-wide association analysis (GWAS) identified 141 genes (264 SNPs) significantly enriched for anxiety and depression related functions. In the same CC cohort, we measured GM composition and identified five families that differ between high and low anxiety mice. Anxiety level was predicted with 79% accuracy and an AUC of 0.81. Mediation analyses revealed that the genetic contribution to anxiety was partially mediated by the GM. Our findings indicate that GM partially mediates and coordinates the effects of genetics on anxiety.

59 BASIC BIOLOGICAL SCIENCES↗

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗

Closed-form theoretical model of the secondary drop size in partial coalescence—Capturing pertinent timescales and viscous forces

One of the most important outcomes of partial drop coalescence is the ratio of the secondary drop radius to the primary drop radius, known as the drop ratio, ri. This ratio is thought to be approximately constant and independent of physical parameters of the fluids involved. However, here we reveal that ambient fluid viscosity can alter the size of the secondary drop and the drop ratio consequently. Using scaling analysis, we derive a model that predicts the behavior of the drop ratio as a function of the Ohnesorge number, a dimensionless ratio of viscous to inertial forces. In addition, we present our experimental results of coalescing drops on a planar interface under the influence of surface tension gradients. A high-speed digital camera is used to observe the evolution of drops as they coalesce with a bulk liquid. We show that this process is influenced by the surface tension gradient between the drop and the bulk liquid. The ratio of the secondary drop to the primary drop in partial coalescence is smaller than the reported values for coalescence without a surface tension gradient. The analytical model derived through this study is based on a new modified Ohnesorge number that includes surface tension gradients. Our analytical model is compared against other models and the results illustrate good agreement with our experimental findings and experimental data in the literature.

42 ENGINEERING↗

Electron density measurement using a partially covered hairpin resonator in an inductively coupled plasma

Hairpin probes are used to determine electron densities via measuring the shift of the resonant frequency of the probe structure when immersed in a plasma. This manuscript presents new developments in hairpin probe hardware and theory that have enabled measurements in a high electron density plasma, up to approximately 10 12 cm -3 , corresponding to a plasma frequency of about 9 GHz. Hardware developments include the use of both quarter-wavelength and three-quarter-wavelength partially covered hairpin probes in a transmission mode together with an easily reproducible implementation of the associated microwave electronics using commercial off-the-shelf components. The three-quarter-wavelength structure is operated at its second harmonic with the purpose of measuring higher electron densities. New theory developments for interpreting the probe measurements include the use of a transmission line model to find an accurate relationship between the resonant frequency of the probe and the electron density, including effects of partially covering the probes with epoxy. Measurements are taken in an inductively coupled plasma sustained in argon at pressures below 50 mTorr. Results are compared with Langmuir probe and interferometry measurements.

47 OTHER INSTRUMENTATION↗

Generalized impurity pinch in partially magnetized multi-ion plasma

In a two-ion-species plasma with disparate ion masses, heavy ions tend to concentrate in the low-temperature region of collisionally magnetized plasma and in the high-temperature region of collisionally unmagnetized plasma, respectively. Moreover, collisional magnetization can be determined as the ratio of the light ion gyrofrequency to the collision frequency of light and heavy ion species, and the behavior of this effect in the intermediate regime of partially magnetized plasma is predominantly dependent on this Hall parameter. Multi-ion cross-field transport has been described before in the collisionally magnetized plasma regime, and generalized pinch relations, which describe densities of ion species in equilibrium in that plasma, are found in the literature. Here, the role of collisional magnetization and Larmor magnetization in multi-ion collisional transport is clarified, and generalized pinch relations are extended to the partially magnetized regime in which the ion Hall parameter may be small, as long as electrons remain collisionally magnetized. Equilibrium ion density profiles have the same dependence on external forces and on each other regardless of collisional magnetization of ions. The expansion of the range of validity of multi-ion collisional transport models makes them applicable to a wider range of laboratory plasma conditions. In particular, ion density profiles evolve sufficiently fast for radial impurity transport to be observable around stagnation on MagLIF, leading to expulsion of heavy ion impurities from the hotspot as long as plasma becomes sufficiently collisionally magnetized during the implosion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Partially polaron-transformed quantum master equation for exciton and charge transport dynamics

Polaron-transformed quantum master equation (PQME) offers a unified framework to describe the dynamics of quantum systems in both limits of weak and strong couplings to environmental degrees of freedom. Thus, the PQME serves as an efficient method to describe charge and exciton transfer/transport dynamics for a broad range of parameters in condensed or complex environments. However, in some cases, the polaron transformation (PT) being employed in the formulation invokes an over-relaxation of slow modes and results in premature suppression of important coherence terms. A formal framework to address this issue is developed in the present work by employing a partial PT that has smaller weights for low frequency bath modes. In this work, it is shown that a closed form expression of a second order time-local PQME including all the inhomogeneous terms can be derived for a general form of partial PT, although more complicated than that for the full PT. All the expressions needed for numerical calculation are derived in detail. Applications to a model of a two-level system coupled to a bath of harmonic oscillators, with test calculations focused on those due to homogeneous relaxation terms, demonstrate the feasibility and the utility of the present approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Finite ion temperature effects on electrostatic instabilities in partially magnetized plasmas

In this paper, the effects of warm ions on electrostatic, kinetic instabilities observed in partially magnetized plasmas, such as the electron cyclotron drift instability (ECDI) and modified two-stream instability (MTSI), are investigated. The kinetic dispersion relation that accounts for warm, non-magnetized ions and warm, magnetized electrons is solved using a complex root-finding technique [A. C. Denig and K. Hara, Phys. Plasmas 30, 032108 (2023)]. It is observed that finite ion temperature introduces ion Landau damping effects, decreasing the growth rate of most unstable modes. The high-frequency, short-wavelength ECDI modes are more strongly affected by ion Landau damping than the low-frequency, long-wavelength MTSI modes. The solutions of the kinetic dispersion relation for MTSI are compared with the fluid dispersion relation of MTSI, which was originally proposed by McBride et al. [Phys. Fluids 15 2367–2383 (1972)]. The differences in the dispersion characteristics between the kinetic and fluid MTSI limits are assessed, illustrating the effects of electron and ion Landau damping on kinetic instabilities in partially magnetized plasmas.

Denig, A. C. (ORCID:0000000253339572)↗

Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys

We report that mechanical properties are fundamental to structural materials, where dislocations play a decisive role in describing their mechanical behavior. Although the high-yield stresses of multiprincipal element alloys (MPEAs) have received extensive attention in the last decade, the relation between their mechanistic origins remains elusive. Our multiscale study of density functional theory, atomistic simulations, and high-resolution microscopy shows that the excellent mechanical properties of MPEAs have diverse origins. The strengthening effects through Shockley partials and stacking faults can be decoupled in MPEAs, breaking the conventional wisdom that low stacking fault energies are coupled with wide partial dislocations. This study clarifies the mechanistic origins for the strengthening effects, laying the foundation for physics-informed predictive models for materials design.

36 MATERIALS SCIENCE↗