Search NASA⌕ Search

SEARCH · Search NASA

Results for “MCD”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Near-infrared C-term MCD spectroscopy of octahedral uranium (V) complexes

C-term magnetic circular dichroism (MCD) spectroscopy is a powerful method for probing d–d and f–f transitions in paramagnetic metal complexes. However, this technique remains underdeveloped both experimentally and theoretically for studies of U(V) complexes of Oh symmetry, which have been of longstanding interest for probing electronic structure, bonding, and covalency in 5f systems. In this study, C-term NIR MCD of the Laporte forbidden f–f transitions of [UCl 6 ] - and [UF 6 ] - are reported, demonstrating the significant fine structure resolution possible with this technique including for the low energy Γ 7 → Γ 8 transitions in [UF 6 ] - . The experimental NIR MCD studies were further extended to [U(OC 6 F 5 ) 6 ] - , [U(CH 2 SiMe 3 ) 6 ] - , and [U(NC(tBu)(Ph)) 6 ] - to evaluate the effects of ligand-type on the f–f MCD fine structure features. Theoretical calculations were conducted to determine the Laporte forbidden f–f transitions and their MCD intensity experimentally observed in the NIR spectra of the U(V) hexahalide complexes, via the inclusion of vibronic coupling, to better understand the underlying spectral fine structure features for these complexes. These spectra and simulations provide an important platform for the application of MCD spectroscopy to this widely studied class of U(V) complexes and identify areas for continued theoretical development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

C-Term magnetic circular dichroism (MCD) spectroscopy in paramagnetic transition metal and f-element organometallic chemistry

Magnetic circular dichroism (MCD) spectroscopy is a powerful experiment used to probe the electronic structure and bonding in paramagnetic metal-based complexes. While C-term MCD spectroscopy has been utilized in many areas of chemistry, it has been underutilized in studying paramagnetic organometallic transition metal and f-element complexes. From the analysis of isolated organometallic complexes to the study of in situ generated species, MCD can provide information regarding ligand interactions, oxidation and spin state, and geometry and coordination environment of paramagnetic species. The pratical aspects of this technique, such as air-free sample preparation and cryogenic experimental temperatures, allow for the study of highly unstable species, something that is often difficult with other spectroscopic techniques. This perspective highlights MCD studies of both transition metal and f-element organometallic complexes, including in situ generated reactive intermediates, to demonstrate the utility of this technique in probing electronic structure, bonding and mechanism in paramagnetic organometallic chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ligand effects on electronic structure and bonding in U(iii) coordination complexes: a combined MCD, EPR and computational study

The trivalent oxidation state of uranium has been shown to undergo unique reactivity, from its ability to activate a variety of small molecules to its role in the catalytic reduction of ethene to ethane amongst others. Central to this unique reactivity and ability to rationally design ligands for isotope separation is the underlying uranium electronic structure. While electronic structure studies of U(IV), U(V), and U(VI) have been extensive, by comparison, analogous studies of more reduced oxidation states such as U(III) remains underdeveloped. Herein we report a combined MCD and EPR spectroscopic approach along with density functional theory and multireference wavefunction calculations to elucidate the effects of ligand perturbation in three uranium(III) Tp* complexes. Overall, the experimental and computational insight suggests that the change in ligand environment across this series of U(III) complexes resulted in only minor perturbations in the uranium electronic structure. This combined approach was also used to redefine the electronic ground state of a U(III) complex with a redox non-innocent Bipy - ligand. Overall, these studies demonstrate the efficacy of the combined experimental and theoretical approach towards evaluating electronic structure and bonding in U(III) complexes and provide important insight into the challenges in altering ligand environments to modify bonding and reactivity in uranium coordination chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Minimizing development costs for efficient many-core visualization using MCD3

Scientific visualization software increasingly needs to support many-core architectures. However, development time is a significant challenge due to the breadth and diversity of both visualization algorithms and architectures. With this work, we introduce a development environment for visualization algorithms on many-core devices that extends the traditional data-parallel primitive (DPP) approach with several existing constructs and an important new construct: meta-DPPs. We refer to our approach as MCD 3 — Meta-DPPs, Convenience routines, Data management, DPPs, and Devices. The twin goals of MCD 3 are to reduce developer time and to deliver efficient performance on many-core architectures, and our evaluation considers both of these goals. For development time, we study 57 algorithms implemented in the VTK-m software library and determine that MCD 3 leads to significant savings. For efficient performance, we survey ten studies looking at individual algorithms and determine that the MCD 3 hardware-agnostic approach leads to performance comparable to hardware-specific approaches: sometimes better, sometimes worse, and better in the aggregate. In total, we find that MCD 3 is an effective approach for scientific visualization libraries to support many-core architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Additively manufactured cryogenic microchannel distillation device for air separation

Abstract The efficiency of air separation is tested using three different small‐scale cryogenic distillation columns. The performance of a random packed column is compared to the performance of two microchannel distillation (MCD) columns that use thin wicking structures and gas flow channels to achieve process intensification. The MCD columns tested include a plate‐type layered column and an additively manufactured porous honeycomb (AMPH) column. For columns with 25.4 cm of active height and run under similar conditions, the packed, plate‐type layering, and AMPH columns achieved approximate height equivalent of a theoretical plate (HETP) values of 5.5, 3.7, and 3.2 cm for nitrogen, and 5.9, 4.9, and 3.3 cm for argon. The AMPH column can produce up to 0.4 SLM of more than 90% purity oxygen with 12 W of cooling lift. These results demonstrate the feasibility of using additive manufacturing to construct MCD devices and pave a way for constructing novel MCD designs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Relativistic Effects in Magnetic Circular Dichroism: Restricted Magnetic Balance and Temperature Dependence

Magnetic circular dichroism of transition metal complexes and open-shell systems are challenging to simulate and analyze, mainly due to the interplay of spin–orbit couplings and finite-magnetic-field induced Zeeman effects with the complex selection rules dictated by the circularly polarized light. In this study, we introduce an ab initio relativistic two-component formalism based on the restricted magnetic-balanced Hamiltonian for simulating MCD spectra. Both homogeneous finite magnetic field and relativistic effects are included variationally in the ground state reference. Finite-field London orbitals are used to enforce the constrained gauge-origin independence in the calculation using localized atomic orbitals. Through benchmark studies of AuCl 4 – , Pt(CN) 4 2– , and Mo(CN) 8 3– , we discuss how relativistic effects are manifested in MCD for both closed-shell and open-shell molecular complexes and how the interplay between spin–orbit coupling and magnetic field modulates the MCD selection rules. Finally, an investigation on temperature-dependent MCD is carried out and compared to experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Evaluating the Potential and Challenges of an Uncertainty Quantification Method for Long Short–Term Memory Models for Soil Moisture Predictions

Recently, recurrent deep networks have shown promise to harness newly available satellite–sensed data for long–term soil moisture projections. However, to be useful in forecasting, deep networks must also provide uncertainty estimates. Here we evaluated Monte Carlo dropout with an input–dependent data noise term (MCD+N), an efficient uncertainty estimation framework originally developed in computer vision, for hydrologic time series predictions. MCD+N simultaneously estimates a heteroscedastic input–dependent data noise term (a trained error model attributable to observational noise) and a network weight uncertainty term (attributable to insufficiently constrained model parameters). Although MCD+N has appealing features, many heuristic approximations were employed during its derivation, and rigorous evaluations and evidence of its asserted capability to detect dissimilarity were lacking. To address this, we provided an in–depth evaluation of the scheme's potential and limitations. We showed that for reproducing soil moisture dynamics recorded by the Soil Moisture Active Passive (SMAP) mission, MCD+N indeed gave a good estimate of predictive error, provided that we tuned a hyperparameter and used a representative training data set. The input–dependent term responded strongly to observational noise, while the model term clearly acted as a detector for physiographic dissimilarity from the training data, behaving as intended. However, when the training and test data were characteristically different, the input–dependent term could be misled, undermining its reliability. Additionally, due to the data–driven nature of the model, data noise also influences network weight uncertainty, and therefore the two uncertainty terms are correlated. Altogether, this approach has promise, but care is needed to interpret the results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating Probabilistic Deep Learning Methods for Uncertainty Quantification of Precipitation Bias Correction

Climate models often exhibit biases in their precipitation predictions, particularly underestimating high-intensity events and overestimating low precipitation. Deep learning approaches offer promising solutions, but their epistemic uncertainty associated with a deep learning–based bias correction method has not previously been quantified for reliable downstream climate impact studies. While methods for capturing the epistemic uncertainty in deep learning frameworks exist, there is currently no consensus on the best method. In this work, we compare three uncertainty quantification (UQ) methods—Deep Ensembles (DEns), Monte Carlo Dropout (MCD), and Flipout—by assessing the reliability of their uncertainty estimates using standard measures such as sharpness and calibration. These UQ methods are applied to an existing deep learning precipitation bias correction model known as UFNet: a coupled U-Net and fully connected neural network. The methods utilized to assess the models’ uncertainties are 1) calibration, which ensures that the expected probabilities of the model align with reality and 2) sharpness, which is a measure of the precision of the model’s probabilistic predictions. Of the three UQ methods evaluated, the DEns and MCD methods demonstrated the best-calibrated performance (expected calibration error of 0.36 and 0.35, respectively), compared to Flipout (0.58). In contrast, Flipout had the sharpest predictions and the highest metric performance in bias correcting precipitation—especially for higher-order moments such as kurtosis with a spatial correlation of 72% compared to 32% and 55% spatial correlation for DEns and MCD, respectively. Of the three UQ methods, MCD was found to be the most suitable method for UQ purposes based on its calibration, sharpness, and computational requirements.

Bayesian methods↗
DOE OSTI2022

Unsymmetric Pentacene- and Pentacenequinone-Fused Porphyrins: Understanding the Effect of Cross- and Linear-Conjugation

Unsymmetric pentacenequinone-fused (cross-conjugated) and pentacene-fused (linear-conjugated) porphyrins were designed and synthesized. The cross-conjugated (AM 1 –AM 3 ) and linear-conjugated (AM 5 –AM 7 ) porphyrins displayed strikingly different sets of optical and electronic properties, both of which are unusual and nontypical of porphyrins. MCD, DFT, and TDDFT calculations suggest that multiple charge transfer states exist in both π-conjugated systems, which contributes to the complex absorption and MCD spectra of these molecular systems. The general Gouterman’s four-orbital model used to explain porphyrin spectroscopy led to contradicting theoretical and experimental data, and is thus not applicable for these molecular systems. The “2 + 4” and “3 + 3” active spaces have been deduced and have proven effective to interpret the absorption and MCD spectra of the pentacenequinone-fused (cross-conjugated) and pentacene-fused (linear-conjugated) porphyrins, respectively. Spectroelectrochemistry of AM 5 –AM 7 revealed broad and intense IR absorptions in the range of 1500–2500 nm, illustrating the exceptional ability of these pentacene-fused systems to accommodate positive charges. A pronounced metal effect was observed for pentacene-fused porphyrins. While pentacene-fused Ni(II) porphyrin (AM 6 ) demonstrated an abnormal ability to stabilize pentacene with a half-life of >28.3 days, the half-life of the free base and Zn(II) counterparts were normal, similar to those of pentacene analogues. This work provides important and useful information on guiding new material designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Data and scripts associated with the manuscript "Organic Molecules are Deterministically Assembled in River Sediments"

This data package is associated with the publication "Organic Molecules are Deterministically Assembled in River Sediments" submitted to Scientific Reports (Stegen et al., 2024). The study applies community ecology methods to dissolved organic matter (DOM) chemistry from variably inundated riverbed sediments to uncover principles governing DOM composition at a reach-scale. This data package documents the workflow used to process and generate the main findings in the manuscript. The R scripts reference the raw, unprocessed Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data from another data package, available on ESS-DIVE at https://data.ess-dive.lbl.gov/view/doi:10.15485/1834208. The scripts then process the raw FTICR-MS data and generate the findings and figures presented in the associated manuscript. In brief, this study demonstrates that DOM assemblages in variably inundated sediments are primarily governed by deterministic variable selection, including sediment moisture effecting the degree of deterministic assembly. See the manuscript for more details pertaining to interpretation and implications of the findings. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/ECA_2020_Sed.This data package is comprised of 6 scripts and 7 folders. The file-level metadata file (file ending in "flmd.csv") lists all files contained in this data package and descriptions for each. The data dictionary (file ending in "dd.csv) describes all tabular data columns and their respective definitions and units. The FTICR_Processing_Scripts produce the outputs found in the "Processed_Data" folder. The remaining scripts (located in the parent directory) produce the outputs found in the following four folders: (1) "MCD_Dendrograms", "MCD_Randomizations", "MCD_bNTI_Outcomes", and "OM_Null_Modeling". The fifth script additionally takes the three comma-separated values (CSV) files found in the parent directory as input ("VGC_texture.csv", "merged_weights.csv", and "ECA2_FTICR_BetaDisp.csv"). The outputs of each of the five scripts serve as the input to the following script, with the final outputs stored in the folder "OM_Null_Modeling".

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Evaluation of assumptions made by Hygroscopic Tandem Differential Mobility Analyzer inversion routines

The Hygroscopic Tandem Differential Mobility Analyzer (H-TDMA) measures the hygroscopicity of atmospheric particles, and many atmospheric processes that change this hygroscopicity also change the atmospheric size distribution. Two assumptions made during H-TDMA inversion create spurious hygroscopic trends as a function of the changing inlet size distribution. These two assumptions—that the particles exiting the first Differential Mobility Analyzer (DMA1) are singly charged and that the inlet size distribution has a slope of zero (flat)— generate Multi-Charge Dispersion (MCD) bias and Slope bias, respectively. First, we use a model, named TAO, to show that the inlet size distribution could theoretically change the measured ammonium sulfate hygroscopicity by 10%–20% as a function of diameter or experimental time with no change in relative humidity. Secondly, we show experimentally that aerosol emitted from the flaming combustion of grass creates MCD bias. Here, in this experiment, we measure the CPC response of the first three charges and invert these responses using a new routine named Junior. Junior's inversion of each charge shows that one growth factor distribution describes all measured diameters (no growth dependence on diameter). As in the modeling study above, previous publications of this aerosol system, using traditional inversion assumptions, report a decrease in hygroscopicity as DMA1 diameter increases. Unlike traditional inversions, Junior's inversion does not assume the particles are singly charged nor does it make the flat inlet size distribution assumption. Instead, both the inlet size distribution and each charge's CPC response are measured quantities. Thus, the discrepancy between our inversion results and previous publications is likely due to the traditional inversion routine assumptions. This underscores the importance for accounting for Slope and MCD bias during inversions. Experimental results should be carefully analyzed when reporting hygroscopic trends with respect to diameter or experimental time when using the traditional inversion assumptions.

42 ENGINEERING↗
DOE OSTI2023

Ultra-fast and sensitive magneto-optical hydrogen sensors using a magnetic nano-cap array

Magnetism in curved nano-geometries has opened a new path to design novel characteristics and phenomena that could greatly impact the future fundamental and applied studies of materials. Here, in this report, a hexagonally-packed array of magnetic nano-caps (or nano-patches, NP) exhibiting unique magnetic anisotropy and optimal nanostructure for fast hydrogen kinetics is explored as a sensing element for the spark-free magnetic-circular-dichroism (MCD) H 2 sensor. The MCD H 2 sensor outperforms the state-of-the-art optical sensors reported to date and satisfies the most challenging performance targets imposed by US Department of Energy. In particular, a Pd 67 Co 33 NP sensor exhibits response time of t 90 < 0.9 s, recovery time of t 10 < 9.0 s over the 1-100 mbar H 2 partial pressure range, and limit of detection (LOD) of ~1 ppm. The LOD improves to <700 ppb, when the signal-to-noise ratio is enhanced by stacking three NP arrays. Using a 30-nm TAF (Teflon AF 2400) polymer coating, the sorption kinetics of the Pd 67 Co 33 /TAF sensor are significantly accelerated, with t 90 < 0.4 s and t 10 < 2.8 s over the same pressure range. When the Pd 67 Co 33 /TAF sensor is further coated with a 100-nm poly(methyl methacrylate) (PMMA) layer, a rapid sorption time of t 90 < 0.5 s, LOD < 1 ppm and excellent sensor accuracy (<2.5% full scale) are maintained, while the sensor obtains strong selectivity against interference gases and moisture and a negligible aging effect. The MCD nano-cap sensor platform may have a great impact on the future deployment of H 2 fuel, H 2 environmental monitoring sensors, and fast proton-based magneto-ionic devices.

Fast and sensitive hydrogen sensors↗
DOE OSTI2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling

Deep learning (DL) has emerged as a promising tool for downscaling coarse-resolution climate data to high-resolution outputs, enabling improved regional climate predictions. A critical aspect of DL-based downscaling is the incorporation of uncertainty quantification (UQ), which enhances the interpretability and reliability of predictions—key factors for climate risk assessment and decision-making. This study develops a DL model to downscale 2 m temperature across the contiguous United States using reanalysis datasets. We systematically evaluate three epistemic UQ methods—deep ensembles (DEns), Monte Carlo dropout (MCD), and Flipout—based on their probabilistic accuracy, downscaling performance, sensitivity to geographical features, and computational efficiency. Results indicate that MCD generally outperforms Flipout and DEns in terms of calibration and downscaling accuracy. However, DEns demonstrate lower calibration errors in coastal regions, indicating its higher confidence within these areas. Flipout, in contrast, is more sensitive to elevation gradients and exhibits higher calibration errors in mountainous regions. Hence, the choice of UQ method for this task depends on the specific requirements of the application. For applications that prioritize overall calibration, downscaling accuracy, and computational efficiency, MCD is a strong candidate. These findings highlight the importance of selecting UQ methods based on application-specific requirements, such as geographical context and computational constraints. By addressing the trade-offs between UQ methods, this study provides actionable insights for improving the reliability, scalability, and utility of DL-based downscaling in climate science.

Environmental sciences↗
DOE OSTI2025

Spin-Forbidden Excitations in the Magneto-optical Spectra of CrI 3 Tuned by Covalency

Spin-forbidden (Δ⁢𝑆 ≠0) multiplet excitations and their coupling to magnetic properties are of increasing importance for magneto-optical studies of correlated materials. Nonetheless, the mechanisms for optically brightening these transitions and their generality remain poorly understood. Here, we report magnetic circular dichroism (MCD) spectroscopy on the van der Waals ferromagnet (FM) CrI 3 . Previously unreported spin-forbidden (Δ⁢𝑆 =1) 4 𝐴 2⁢g → 2 𝐸 g / 2 𝑇 1⁢g Cr 3+ 𝑑⁢𝑑 excitations are observed near the ligand-to-metal charge-transfer excitation threshold. The assignment of these excitations and their Cr 3+ multiplet character is established through complementary Cr 𝐿 3 -edge resonant inelastic x-ray scattering measurements along with charge-transfer multiplet calculations and chemical trends in the chromium trihalide series (Cr⁢𝑋 3 , 𝑋 = Cl, Br, I). We utilize the high sensitivity of MCD spectroscopy to study the thickness-dependent optical response. The spin-forbidden excitations remain robust down to the monolayer limit, and we observe a significant magnetic-field dependence of the MCD spectrum across the antiferromagnetic-to-FM transition in few-layer samples. We preliminarily attribute this behavior to changes in the metal-ligand covalency with magnetic state. Our results clarify the magneto-optical response of CrI 3 and identify covalency as a central mechanism for the brightening and field tunability of spin-forbidden multiplet excitations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Quantification of neural networks uncertainties with applications to SAFARI-1 axial neutron flux profiles

Deep Neural Networks (DNNs) have been widely used as a data-driven modelling tool in nuclear engineering. However, as a Machine Learning model, Artificial Neural Network (ANN) predictions are subjected to uncertainties originating from the noise in training data, incomplete coverage of the domain, and imperfect neural network architectures. In this work, we target at quantifying the prediction/approximation uncertainties of ANNs using Monte Carlo Dropout (MCD), as well as Bayesian Neural Networks (BNNs) which are solved by variational inference. With a demonstration problem in which neural networks are used to predict the assembly axial neutron flux profiles, the results have shown that the three different neural network models (regular DNNs, DNNs solved with MCD and BNNs) can produce results that agree very well among each other and with the measurement data, on cycles that are not used in the training process. Besides the excellent generalization capability, the uncertainty bands produced by MCD and BNN agree very well, and in general, they can fully envelop the noisy measurement data points. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Nature of the Reactive Biferric Peroxy Intermediate P′ in the Arylamine Oxygenases and Related Binuclear Fe Enzymes

Binuclear nonheme iron enzymes activate O 2 to perform a wide range of chemical transformations. The process of O 2 activation typically involves a biferric peroxy-level intermediate P. It has been previously found that this intermediate undergoes further activation, either protonation or rearrangement to form P′ or further oxidation to form high-valent intermediates Q or X. Here, this study defines the structure of the P′ intermediate in the N-oxygenases CmlI (and AurF based on previous data) using nuclear resonance vibrational spectroscopy (NRVS) in conjugation with density functional theory (DFT) calculations. These results, combined with variable temperature variable field (VTVH) magnetic circular dichroism (MCD) spectroscopy on the 1-electron cryoreduced P′, define the structure of the P′ intermediate as a μ-1,2-hydroxoperoxo biferric site with a second hydroxide bridge. Reaction coordinate calculations demonstrate that single electron transfer (SET) is facilitated by protonation of the peroxo, activating its reductive cleavage, and that the additional hydroxide bridge does not impact this reaction. VTVH MCD studies further reveal that the hydroxide bridge is absent in the biferrous site, suggesting that during the O 2 reaction with the biferrous site, a water molecule forms the hydroxide bridge in providing the proton that activates the peroxide in P′ for reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Experimental electronic structures of the Fe IV =O bond in S=1 heme vs. nonheme sites: Effect of the porphyrin ligand

High-valent Fe IV =O species are common intermediates in biological and artificial catalysts. Heme and nonheme S=1 Fe IV =O sites have been synthesized and studied for decades but little quantitative experimental comparison of their electronic structures has been available, due to the lack of direct methods focused on the iron. This study allows a rigorous determination of the electronic structure of a nonheme Fe IV =O center and its comparison to an Fe IV =O heme site using 1s2p resonant inelastic X-ray scattering (RIXS) and Fe L-edge X-ray absorption spectroscopy (XAS). Further, variable temperature magnetic circular dichroism (VT-MCD) of the ligand field transitions, combined with nuclear resonance vibrational spectroscopy of the two S=1 Fe IV =O systems show that the equatorial ligand field decreases from a nonheme to a heme Fe IV =O site. Alternatively, RIXS and Fe L-edge XAS combined with MCD show that the Fe dπ orbitals are unperturbed in the Fe IV =O heme relative to the nonheme site because the strong axial Fe-O bond uncouples the Fe dπ orbitals from the porphyrin π-system. As a consequence, the thermodynamics and kinetics of the H-atom abstraction reactions are actually very similar for heme compound II and nonheme Fe IV =O active sites.

bioinorganic chemistry↗
DOE OSTI2023

Unique signatures of the Rashba effect in the magneto-optical properties of two-dimensional semiconductors

Herein, the authors theoretically demonstrate two simple magneto-optical measurements which can be used to confirm the existence of Rashba terms in two dimensional semiconductors, even in samples of unoptimal quality, where the transition line widths are comparable to or larger than the Landau level splitting. The first is magnetic circular dichroism (MCD), where a giant MCD signal should be observed at the band edge in the presence of Rashba terms. The second is the comparison of the diamagnetic shift measured in absorption with that in photoluminescence which occurs from the dispersion minimum of the Rashba exciton.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗