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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Raman enhancement induced by exciton hybridization in molecules and 2D materials

Abstract Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for trace-level fingerprinting. Recently, layered two-dimensional (2D) materials have gained significant interest as SERS substrates for providing stable, uniform, and reproducible Raman enhancement with the potential for trace-level detection. Yet, the development of effective 2D SERS substrates is still hindered by the lack of fundamental understanding of the coupling mechanism between target molecules and substrates. Here, we report a systematic excitation-dependent Raman spectroscopy investigation on the coupling between 2D materials such as SnS 2 , MoS 2 , WSe 2 , and graphene and small organic molecules like rhodamine 6G (Rh 6G). Strong coupling between SnS 2 and Rh 6G is found due to their degenerate excitons through Raman excitation profiles (REP), leading to the enhancement of Rh 6G vibrational modes that are observable down to 10 −13 M. Our study shows that exciton coupling in the substrate-adsorbate complex plays a vital role in the Raman enhancement effect, opening a new route for designing SERS substrates for high sensitivity.

Materials Science↗
DOE OSTI2024

Structural and physical properties of two distinct 2D lead halides with intercalated Cu( II )

Transition metal cation intercalation between the layers of two-dimensional (2D) metal halides is an underexplored research area. In this work we focus on the synthesis and physical property characterizations of two layered hybrid lead halides: a new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 and the previously reported [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 . These compounds exhibit 2D layered crystal structures with incorporated Cu 2+ between the metal halide layers, which is achieved by combining Cu(II) and lead bromide with suitable amino acid precursors. The resultant [Cu(O 2 C–(CH 2 ) 3 –NH 3 ) 2 ]PbBr 4 adopts a 2D layered perovskite structure, whereas the new compound [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 crystallizes with a new structure type based on edge-sharing dodecahedral PbBr5O3 building blocks. [Cu(O 2 C–CH 2 –NH 2 ) 2 ]Pb 2 Br 4 is a semiconductor with a bandgap of 3.25 eV. It shows anisotropic charge transport properties with a semiconductor resistivity of 1.44 × 10 10 Ω cm (measured along the a-axis) and 2.17 × 10 10 Ω cm (along the bc-plane), respectively. The fabricated prototype detector based on this material showed response to soft low-energy X-rays at 8 keV with a detector sensitivity of 1462.7 μCGy –1 cm –2 , indicating its potential application for ionizing radiation detection. Finally, these encouraging results are discussed together with the results from density functional theory calculations, optical, magnetic, and thermal property characterization experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Federated learning for 2D synchrotron x-ray diffractometry: a cross-institutional approach for phase quantification of Ti–6Al–4V alloy

High-energy Two dimensional (2D) synchrotron x-ray diffractometry provides important insights into the atomistic structure and phase evolution of materials, yet traditional analysis methods remain complex, knowledge-intensive, and computationally demanding. Deep-learning models offer a powerful alternative for automating their analysis. Institutions that hold these datasets may be unwilling to share their data due to privacy and security policies, as well as the challenges associated with large-scale data transfer. As a result, models trained on local datasets often perform well only on their own data but exhibit bias and poor generalization across different instruments or facilities. To overcome these limitations, we explore federated learning (FL) for 2D synchrotron diffractograms, enabling collaborative model training without exchanging raw data. In this study, 2D synchrotron diffractograms of Ti–6Al–4V alloy collected from two independent facilities are used to train convolutional neural networks for predicting the β-phase volume fraction. Experimental results show that federated global models significantly outperform locally trained models in terms of generalization and achieve accuracy comparable to centralized trained models. These findings demonstrate the potential of FL to enable secure, cross-institutional collaboration and enhance the scalability of deep-learning-based materials characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems↗
DOE OSTI2025

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2D Polyhedral Template Matching for Atomic Resolution Microscopy

SAND2024-13879O The 2D Polyhedral Template Matching for Atomic Resolution Microscopy is a suite of functions for analyzing atomic resolution electron microscopy images using the 2D polyhedral template matching (2D-PTM) method. This software analyzes atomic resolution microscopy data from electron microscopic imaging or scanning probe microscopies. The primary application is for identifying different crystal phases, crystal orientations, and defect structures obtained in such atomic resolution images. Written in MATLAB and starting from an atomic resolution image, the code identifies the positions of atomic intensity peaks. It then matches predefined structural templates to the local atomic environments. Outputs include the local structural identification, the template scaling factor and rotation angle, root-mean-squared deviation (RMSD), and centrosymmetry parameter.

Medlin, Douglas↗
DOE OSTI2025

2D reactive transport model of shale chemical weathering and biogeochemical fluxes along a mountainous hillslope, East River Watershed, Colorado: Input files and simulation results

This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2025

Understanding the optoelectronic properties of doped 2D organic-inorganic halide perovskite quantum wells: towards efficient quantum well IR photodetectors

Metal halide perovskite (MHP) multiple quantum wells which consist of multilayers of alternate organic and inorganic layers exhibit large exciton binding energies due to the dielectric confinement between the inorganic and organic layers. These naturally formed multiple quantum wells have strong spin-orbit coupling (SOC) due to the presence of heavy elements in their crystal structures. Although the fundamental properties of 2D MHPs are far from being entirely understood, it is widely accepted that their band edge absorption coefficient results from strong exciton interactions. However, studies demonstrating how different exciton interactions and doping effects influence electronic traps and disorder on the band edge absorption coefficient of 2D MHPs have not been demonstrated. Understanding these interactions in MHPs will allow us to access low energy optical transitions for the fabrication of solution processable short-to-mid-wavelength IR photodetectors (1 – 8 μm). Moreover, upon doping, it is possible to move the Fermi energy into the conduction band (CB) to favorably promote the transport of charges in a working device. Herein, we study the development of 2D MHPs having strong SOC, high carrier mobility, and tunable quantum well structures. Our studies shed light on the design and modulation of fundamental physical phenomena by carefully elucidating the role of dopants (n-type and p-type), exciton heterogeneity, orientation, structure, and bias stress effects on the performance of MHPs as potential IR photodetectors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Epitaxial 2D Magnet and Topological Insulator Heterostructures

I will discuss our latest advances on the epitaxial growth of 2D van der Waals (vdW) magnets and their integration with topological insulators (TI). This work is motivated by the realization of topological phases such as the quantum anomalous Hall effect and highly efficient spin-orbit torque produced by TIs. Our initial studies of MnSe2 growth on Bi2Se3 showed a tendency for the interdiffusion of Mn into the Bi2Se3. This ultimately led to the synthesis of MnBi2Se4 (MBS), a new magnetic TI. Interestingly, the vdW phase is not the thermodynamically stable phase and bulk crystals do not exist, so the epitaxial stabilization of MBS creates the opportunity to explore the magnetic and topological properties of this material. We find that MBS is a layered antiferromagnet, similar to MnBi2Te4, but a difference is that the magnetic moments lie in the plane of the film. Angle resolved photoemission experiments show the presence of a topological surface state with Dirac dispersion. For bilayers of 2D magnets and TIs, we have developed FGT films on Bi2Te3. We first optimized FGT by studying its growth on Ge(111) substrates, where we find that kinetic considerations play a major role. Using cross-sectional scanning transmission electron microscopy and scanning tunneling microscopy, we optimize the FGT films to have atomically smooth surfaces and abrupt interfaces with the Ge(111). Subsequently, we have developed the growth of FGT on Bi2Te3 for the integration of 2D magnets with Tis. Interestingly, we observe room temperature ferromagnetism in FGT/Bi2Te3 heterostructures by varying the growth conditions.

Kawakami, Roland↗
NASA NTRS1985

Theoretical transition probabilities between the lowest 2S, 2P and 2D states of Na, K, Rb and Cs

Theoretical transition probabilities between the lowest 2S, 2P and 2D states of the alkali atoms Na through Cs have been computed using near Hartree-Fock quality Slater basis sets. The important core-valence correlation effects are incorporated explicitly by a configuration-interaction procedure. For Cs, the calculations were repeated using a Gaussian basis set so that relativistic effects could be incorporated through an effective core potential procedure. The best calculated electric quadrupole Einstein coefficients are Na(196.3/s), K(103.6/s), Rb(72.4/s) and Cs(19.7/s). Core-valence effects become increasingly important down the column, and reduce the quadrupole transition strengths to about the same degree as for the 2P-2S and 2D-2P dipole-allowed transitions. Relativistic effects increase the quadrupole moment of Cs, but less so than in Ba, presumably because the alkali 2D states are more diffuse.

Langhoff, S. R.↗
NASA NTRS1989

Rapid deactivation of N(2D) by O - Impact on thermospheric and mesospheric odd nitrogen

One- and two-dimensional models of thermospheric odd nitrogen are used to explore the consequences of the recently measured fast quenching of N(2D) by O. A large rate coefficient for this reaction profoundly affects the odd-nitrogen chemistry by removing N(2D) as a source of NO and increasing the concentration of N(4S), which destroys NO. The model calculations show that, as the quenching rate increases, the NO and N(2D) densities decrease, while N(4S) densities increase. Comparisons with Atmosphere Explorer and Solar Mesosphere Explorer satellite observations are made. Use of the fast quenching rate in the models causes the NO peak altitude, typically observed near 110 km, to rise to 140 km.

Fesen, C. G.↗
NASA NTRS1998

Tropical Oceanic Precipitation Processes over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere, The vertical distribution of convective latent-heat release modulates the large-scale circulations of the tropics, Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate models simulate cloud processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMS) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and cloud systems, The major objective of this paper is to investigate the latent heating, moisture and momenti,im budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (CCE) model which includes a 3-class ice-phase microphysical scheme, The model domain contains 256 x 256 grid points (using 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km depth) in the vertical, The 2D domain has 1024 grid points. The simulations are performed over a 7 day time period. We will examine (1) the precipitation processes (i.e., condensation/evaporation) and their interaction with warm pool; (2) the heating and moisture budgets in the convective and stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.

Tao, W.- K.↗
NASA NTRS2002

Visualizing 2D Probability Distributions from Satellite Image-Derived Data

Creating maps of biophysical and geophysical variables using Earth Observing System (EOS) satellite image data is an important component of Earth science. These 2D maps have a single value at every location and standard techniques are used to visualize them. Current tools fall short, however, when it is necessary to describe a distribution of values at each location. Distributions may represent a frequency of occurrence over time, frequency of occurrence from multiple runs of an ensemble forecast or possible values from an uncertainty model. 'Distribution data sets' are described, then a case study is presented to visualize such 2D distributions. Distribution data sets are different from multivariate data sets in the sense that the values are for a single variable instead of multiple variables. Our case study data consists of multiple realizations of percent forest cover, generated using a geostatistical technique that combines ground measurements and satellite imagery to model uncertainty about forest cover. We present several approaches for analyzing and visualizing such data sets. The first is a pixel-wise analysis of the probability density functions for the 2D image while the second is an analysis of features identified within the image. Such pixel-wise and feature-wise views will give Earth scientists a more complete understanding of distribution data sets.

Kao, David↗
NASA NTRS2003

Precipitation Processes developed during ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999), Consistent 2D, semi-3D and 3D Cloud Resolving Model Simulations

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique (i.e. is 2D or semi-3D CRM appropriate for the super-parameterization?); (2) calculate and examine the surface energy (especially radiation) and water budgets; (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

Tao, Wei-Kuo↗
NASA NTRS2001

Momentum Transport: 2D and 3D Cloud Resolving Model Simulations

The major objective of this study is to investigate the momentum budgets associated with several convective systems that developed during the TOGA COARE IOP (west Pacific warm pool region) and GATE (east Atlantic region). The tool for this study is the improved Goddard Cumulas Ensemble (GCE) model which includes a 3-class ice-phase microphysical scheme, explicit cloud radiative interactive processes and air-sea interactive surface processes. The model domain contains 256 x 256 grid points (with 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km) in the vertical. The 2D domain has 1024 grid points. The simulations were performed over a 7-day time period (December 19-26, 1992, for TOGA COARE and September 1-7, 1994 for GATE). Cyclic literal boundary conditions are required for this type of long-term integration. Two well organized squall systems (TOGA, COARE February 22, 1993, and GATE September 12, 1994) were also simulated using the 3D GCE model. Only 9 h simulations were required to cover the life time of the squall systems. the lateral boundary conditions were open for these two squall systems simulations. the following will be examined: (1) the momentum budgets in the convective and stratiform regions, (2) the relationship between momentum transport and cloud organization (i.e., well organized squall lines versus less organized convective), (3) the differences and similarities in momentum transport between 2D and 3D simulated convective systems, and (4) the differences and similarities in momentum budgets between cloud systems simulated with open and cyclic lateral boundary conditions. Preliminary results indicate that there are only small differences between 2D and 3D simulated momentum budgets. Major differences occur, however, between momentum budgets associated with squall systems simulated using different lateral boundary conditions.

Tao, Wei-Kuo↗
NASA NTRS2003

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.↗
NASA NTRS2006

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.↗