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At least 145 records · Page 8

Advanced Observation Operators for GPS Radio Occultation: Validation of the 2D Ray Tracing Approach with CHAMP and SAC-C bending angle and refractivity data - Part 1

Global Positioning System (GPS) Radio Occultations (RO) bending angles and refractivity data characterize mostly the vertical structure of the Earth's atmosphere. We answer the question whether proper simulation of GPS RO data for data assimilation can be obtained with one-dimensional vertical operators, or if accounting also for horizontal atmospheric structures via ray-tracing makes a positive difference when compared with real data. We present a detailed implementation of a geometrical optics multi-plane two-dimensional (2D) ray-tracing as an observation operator to simulate GPS RO bending angles and refractivities within the Finite Volume Data Assimilation System (FVDAS). Comparisons of the outputs of that 2D observation operator with those of simpler ID observation operators are used to generate estimates of errors induced by neglecting tangent point drift (TPD) and horizontal gradients (HG). These error estimates are then confronted with errors estimates derived using 6335 real CHAMP and SAC-C occultations. The agreement for TPD-induced (HG-induced) errors is remarkably positive at altitudes 10-30 km (below 10 km). Comparisons in bending angles O - B STD of the outputs of the multi-plane 2D ray-tracer with those of a vertical Abel transform show reductions of about 8% of the usual O - B bending angle STD due to TPD in the stratosphere (3% due to HG, in the troposphere only). In terms of refractivity, the O - B STD reductions are about 1520% for TPD and 3-5% for HG in the same regions. These reductions are obtained using either 6-hour forecasts or analyses as backgrounds, and using Geometrical Optics (GO) or Canonical Transform (CT) data.

Poli, P.↗

Modeling the Elastic Modulus of 2D Woven CVI SiC Composites

The use of fiber, interphase, CVI SiC minicomposites as structural elements for 2D-woven SiC fiber reinforced chemically vapor infiltrated (CVI) SiC matrix composites is demonstrated to be a viable approach to model the elastic modulus of these composite systems when tensile loaded in an orthogonal direction. The 0deg (loading direction) and 90deg (perpendicular to loading direction) oriented minicomposites as well as the open porosity and excess SiC associated with CVI SiC composites were all modeled as parallel elements using simple Rule of Mixtures techniques. Excellent agreement for a variety of 2D woven Hi-Nicalon(TradeMark) fiber-reinforced and Sylramic-iBN reinforced CVI SiC matrix composites that differed in numbers of plies, constituent content, thickness, density, and number of woven tows in either direction (i.e, balanced weaves versus unbalanced weaves) was achieved. It was found that elastic modulus was not only dependent on constituent content, but also the degree to which 90deg minicomposites carried load. This depended on the degree of interaction between 90deg and 0deg minicomposites which was quantified to some extent by composite density. The relationships developed here for elastic modulus only necessitated the knowledge of the fractional contents of fiber, interphase and CVI SiC as well as the tow size and shape. It was concluded that such relationships are fairly robust for orthogonally loaded 2D woven CVI SiC composite system and can be implemented by ceramic matrix composite component modelers and designers for modeling the local stiffness in simple or complex parts fabricated with variable constituent contents.

Morscher, Gregory N.↗

Measurements of Thermal Conductivity of Superfluid Helium Near its Transition Temperature T(sub lambda) in a 2D Confinement

We report our recent experiments on thermal conductivity measurements of superfluid He-4 near its phase transition in a two-dimensional (2D) confinement under saturated vapor pressure. A 2D confinement is created by 2-mm- and 1-mm-thick glass capillary plates, consisting of densely populated parallel microchannels with cross-sections of 5 x 50 and 1 x 10 microns, correspondingly. A heat current (2 < Q < 400 nW/sq cm) was applied along the channels long direction. High-resolution measurements were provided by DC SQUID-based high-resolution paramagnetic salt thermometers (HRTs) with a nanokelvin resolution. We might find that thermal conductivity of confined helium is finite at the bulk superfluid transition temperature. Our 2D results will be compared with those in a bulk and 1D confinement.

Jerebets, Sergei↗

In-Plane Cracking Behavior and Ultimate Strength for 2D Woven and Braided Melt-Infiltrated SiC/SiC Composites Tensile Loaded in Off-Axis Fiber Directions

The tensile mechanical properties of ceramic matrix composites (CMC) in directions off the primary axes of the reinforcing fibers are important for architectural design of CMC components that are subjected to multi-axial stress states. In this study, 2D-woven melt-infiltrated (MI) SiC/SiC composite panels with balanced fiber content in the 0 degree and 90 degree directions were tensile loaded in-plane in the 0 degree direction and at 45 degree to this direction. In addition, a 2D triaxially-braided MI composite panel with balanced fiber content in the plus or minus 67 degree bias directions and reduced fiber content in the axial direction was tensile loaded perpendicular to the axial direction tows (i.e., 23 degrees from the bias fibers). Stress-strain behavior, acoustic emission, and optical microscopy were used to quantify stress-dependent matrix cracking and ultimate strength in the panels. It was observed that both off-axis loaded panels displayed higher composite onset stresses for through-thickness matrix cracking than the 2D-woven 0/90 panels loaded in the primary 0 degree direction. These improvements for off-axis cracking strength can in part be attributed to higher effective fiber fractions in the loading direction, which in turn reduces internal stresses on critical matrix flaws for a given composite stress. Also for the 0/90 panel loaded in the 45 degree direction, an improved distribution of matrix flaws existed due to the absence of fiber tows perpendicular to the loading direction. In addition, for the +67/0/-67 braided panel, the axial tows perpendicular to the loading direction were not only low in volume fraction, but were also were well separated from one another. Both off-axis oriented panels also showed relatively good ultimate tensile strength when compared to other off-axis oriented composites in the literature, both on an absolute strength basis as well as when normalized by the average fiber strength within the composites. Initial implications are discussed for constituent and architecture design to improve the directional cracking of SiC/SiC CMC components with MI matrices.

Morscher, Gregory N.↗

Area Coverage Planning with 3-axis Steerable, 2D Framing Sensors

Existing algorithms for Agile Earth Observing Satellites((Lemaitre et al. 2002)) were largely created for 1D line sensors that acquire images in linear swaths. However, imaging satellites increasingly use 2D framing sensors (cameras) that capture discrete rectangular images. We describe tiling step-stare approaches that are more suited to rectangular image footprints than are 1D swath-based algorithms. Optimal area planning for these 2D framing instruments is an NPcomplete problem and intractable for large areas, so we present four approximation algorithms. Strategies are compared against a prior 2D framing instrument algorithm (Knight 2014) in three computational experiments. The impact of observer agility on schedule makespan is examined. Makespans vary more as observer agility decreases toward a critical point, then vary less after the critical point, suggesting a possible problem phase transition.

Chien, Steve↗

N‐Heterocyclic Carbene Functionalization of 2D Transition Metal Dichalcogenides via a Frustrated Lewis Pair Strategy

Molecular functionalization of 2D transition metal dichalcogenides (TMDs), which unites tailorability of organic molecules and robustness of inorganic solids, is important for tuning their surface properties. While it is common to leverage the electronic effect of organic ligands to functionalize TMDs, the corresponding steric hinderance has remained elusive and underexplored. Herein N‐heterocyclic carbene (NHC) functionalization of WS 2 is demonstrated via a frustrated Lewis pair (FLP) route, which exploits both the electronic and steric effect for TMD functionalization. The Lewis base, 1,3‐bis(2,4,6‐trimethylphenyl)imidazol‐2‐ylidene (IMes), is anchored to the sulfur vacancy sites (Lewis acid) of the WS 2 nanostructures with the hybrid‐interface‐mediated steric hinderance, mimicking the FLP chemistry and enabling dihydrogen cleavage at room temperature and atmospheric pressure. Solid‐state nuclear magnetic resonance (ssNMR) results reveal the local chemical environment of the activated hydrogen species, which can be transferred for room‐temperature hydrogenation reactions. Finally, the insights are useful for designing weak, non‐covalent bonds to modify the 2D surface of TMDs for a broad scope of applications.

2D materials↗

Boosting Hydrogenation of CO 2 Using Cationic Cu Atomically Dispersed on 2D γ‐Al 2 O 3 Nanosheets

The continuous development of novel catalytic approaches is crucial for advancing efficient CO 2 hydrogenation processes. Drawing inspiration from single-atom catalysis and 2D materials, we designed a new 2D single-atom catalyst with excellent thermal stability by thermally treating Cu-adsorbed γ-AlOOH nanosheets, which yielded a Cu/γ-Al 2 O 3 catalyst with high activity in the hydrogenation of CO 2 -yielding methanol (CH 3 OH), dimethyl ether (DME), and CO as products. The active Cu sites are monodispersed and highly stable due to their cationic oxidation state and their substitution for pentacoordinated aluminum (Al P ) sites on particle surfaces. This study demonstrates an efficient approach for achieving a high CO 2 hydrogenation rate (30.45 mol mol −1 h −1 ) using a catalyst system that lacks metallic Cu centers, traditionally considered essential for H₂ dissociation, and employs what was previously thought to be an inert metal oxide (γ-Al 2 O 3 ) for CO and CH 3 OH production. Ongoing mechanistic studies aim to elucidate the synergy between cationic Cu single atoms and γ-Al 2 O 3 , a Lewis acid support, in facilitating hydrogen (H 2 ) activation and methanol formation.

2D catalyst↗

Self‐Lubricating Tribo‐Catalytic Activity of 2D High Entropy Alloy Nanoflakes

High Entropy Alloys (HEAs) have garnered attention due to their remarkable tribological attributes. Predominantly, failure mechanisms in HEAs emanate from stress‐induced dislocations, culminating in crack propagation and film delamination. In this study, we report on the synthesis of 2D HEA of (MoWNbTaV) 0.2 S 2 which facilitates shear‐induced energy dissipation at sliding interfaces. The ball‐on‐disk tribological investigations demonstrate unprecedentedly low average coefficients of friction (0.076) and wear rates (10 −9 mm 3 (N∙m) −1 ) under high contact pressures (0.936 GPa) within ambient conditions. Employing multi‐scale characterizations alongside molecular dynamic simulations, we elucidate that the presence of the HEA triggers tribocatalytic activity under high contact pressures emerging as a pivotal factor in extending lubricant lifespan during tribological tests. The resilient lubriciousness coupled with the facile spray coating methodology of (MoWNbTaV) 0.2 S 2 in ambient environments paves the way for the development of a new class of solid lubricants based on 2D HEA.

2D solid lubricant↗

Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling

One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.

2D modelling↗

Modulation of Electrostatic Potential in 2D Crystal Engineered by an Array of Alternating Polar Molecules

The moiré potential in rotationally misfit two-dimensional (2D) heterostructures has been used to build artificial exciton and electron lattices, which have become platforms for realizing exotic electronic phases. Here, we demonstrate a different approach to create a superlattice potential in 2D crystals by using the near field of an array of polar molecules. Here, a bilayer of titanyl phthalocyanine (TiOPc), consisting of alternating out-of-plane dipoles, is deposited on monolayer MoS 2 . Time-resolved two-photon photoemission spectroscopy reveals a pair of interlayer exciton states with an energy difference of ~0.1 eV, which is consistent with the electrostatic potential modulation induced by the TiOPc bilayer as determined by density functional theory calculations. Because the symmetry and the period of this potential superlattice can be changed readily by using molecules of different shapes and sizes, molecule/2D heterostructures can be promising platforms for designing artificial exciton and electron lattices.

2D heterostructures↗

Humidity Disrupts Structural and Chiroptical Properties of Chiral 2D Perovskites

Chiral two-dimensional (2D) hybrid organic–inorganic metal halide perovskite semiconductors have emerged as an exceptional material platform with many design opportunities for spintronic applications. However, a comprehensive understanding of changes to the crystal structure and chiroptical properties upon exposure to atmospheric humidity has not been established. We demonstrate phase degradation to the 1D (MBA)PbI 3 (MBA = methylbenzylammonium) and the hypothetical (MBA) 3 PbI 5 ·H 2 O hydrate phases, accompanied by a reduction and disappearance of the chiroptical response. Firstprinciple simulations show that water molecules preferentially locate at the interface between the organic cations and the inorganic framework, thereby disrupting the hydrogen bonding, impacting both the structural chirality and stability of the material. These findings provide critical insights into phase degradation mechanisms and their impact on chiroptical activity in chiral 2D perovskites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Air-Stable Room-Temperature Quasi-2D Tin Iodide Perovskite Microlasers

Quasi-2D tin iodide perovskites (TIPs) are promising lead-free alternatives for optoelectronic applications, but achieving stable lasing remains challenging due to their limited environmental stability. Here, we report air-stable, room-temperature lasing from quasi-2D TIP microcrystals as small as 4 μm. Incorporation of the organic spacer 5IPA3 significantly enhanced the stability of these materials compared with previously reported TIPs. Lasing was observed from both dielectric (n = 4) and plasmonic (n = 3 and n = 4) TIP microlasers. Under picosecond pumping, lasing was sustained for over 108 pump pulses in ambient conditions. These results represent a significant step toward practical photonic applications of tin-based perovskites.

crystals↗

Spontaneous Formation of Single-Crystalline Spherulites in a Chiral 2D Hybrid Perovskite

In two-dimensional (2D) chiral metal-halide perovskites (MHPs), chiral organic spacers induce structural chirality and chiroptical properties in the metal-halide sublattice. This structural chirality enables reversible crystalline-glass phase transitions in (S-NEA) 2 PbBr 4 , a prototypical chiral 2D MHP where NEA + represents 1-(1-naphthyl)ethylammonium. Here, in this study, we investigate two distinct spherulite states of (S-NEA) 2 PbBr 4 , exhibiting either radial-like or stripe-like banded patterns depending on the annealing conditions of the amorphous film. Despite similarities in optical absorption and photoluminescence, the stripe-like, banded spherulite exhibits higher crystallinity and improved optical transparency compared to those of radial-like spherulite. X-ray nanoprobe measurements reveal tilting-angle modulations in the octahedral plane of stripe-like spherulites, correlating with the film’s surface geometry. Transfer matrix calculations indicate that the optical contrast in stripe-like patterns, seen in bright-field optical microscopy, arises from optical interference effects, differing from the contrast mechanism observed in polymer spherulites. Ultrafast carrier dynamics experiments suggest that the stripe-like spherulites resemble single crystals more closely than radial-like spherulites, while electrical conductivity measurements show enhanced charge carrier transport in stripe-like spherulites. These findings offer insights into MHP spherulite states with a single composition but different morphologies, previously observed only in polymers, highlighting their potential for optoelectronic applications.

36 MATERIALS SCIENCE↗

Compact in situ probe for magnetotransport measurements of 2D materials under variable tensile strain

The recent development of freestanding oxide membranes has opened new opportunities for strain engineering of transition metal oxides beyond values accessible in bulk samples. While a number of studies have been performed with fixed strain, the ability to dynamically control the strain state during measurement would be greatly enabling. To this end, we present an in situ uniaxial strain probe optimized for transport measurements of tensile-strained 2D or quasi-2D materials down to 2 K. Utilizing a flexible polyimide substrate as the stress transfer medium, our platform simplifies the sample preparation process and allows precise alignment of strain fields relative to the crystalline axes. An in situ optical microscope monitors the macroscopic strain state operando and makes it possible to complete an entire magnetotransport study at cryogenic temperatures under continuous strain variations. We demonstrate the capabilities of the probe on a freestanding LaNiO 3 membrane, where we induce tensile strain up to 8% and observe a corresponding strong transport anisotropy. In view of the rapid developments in low-dimensional materials synthesis and the plethora of novel quantum phenomena they exhibit, this strain probe provides general instrumentation for examining and controlling these properties via strain.

2D materials↗

Spin wave theory for the triaxial magnetic anisotropy 2D van der Waals antiferromagnet CrSBr

The magnetic properties of two-dimensional (2D) materials have been attracting increasing attention in recent years due to their unique behavior and possible applications in new devices. One material of great interest is the 2D van der Waals (vdW) crystal CrSBr, which exhibits antiferromagnetic (AF) order at low temperatures due to an interlayer AF exchange interaction. Here, we present a full quantum spin-wave theory for vdW crystals considering one interlayer and three intralayer exchange interactions, and triaxial magnetic anisotropy. The fits of the theoretical results to antiferromagnetic resonance measurements and inelastic neutron scattering data in CrSBr yield reliable values for the seven interaction parameters that can be used to calculate other properties of this interesting material.

2D materials↗

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. We employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2D materials↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗