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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.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Simulation and optimization of the NSLS-II SRX beamline combining ray-tracing and wavefront propagation

The Sub-micron Resolution X-ray spectroscopy (SRX) beamline will benefit from the ultralow emittance of the National Synchrotron Light Source II to address a wide variety of scientific applications studying heterogeneous systems at the sub-micrometer scale. This work focuses on the KB branch ({Delta}E: 4.65-28 keV). Its main optical components include a horizontally focusing mirror forming an adjustable secondary source, a horizontally deflecting monochromator and two sets of Kirkpatrick-Baez mirrors as focusing optics of two distinct inline stations for operations requiring either high flux or high resolution. In the first approach, the beamline layout was optimized with ray-tracing calculations involving Shadowvui computer codes. As a result, the location and characteristics of optics were specified for achieving either the most intense or the smallest monochromatic beam possible on the target (10{sup 13} ph/s or 10{sup 12} ph/s respectively in a 500 nm or 65 nm focal spot). At the nanoprobe station, the diffraction limited focusing of X-rays is governed by the beam coherence. Hence, a classical geometric approach is not anymore adapted. To get reliable estimates of the Nanoprobe performances, a wavefront propagation study was performed using Synchrotron Radiation Workshop (SRW) code. At 7.2 keV, calculations show an intense (10{sup 12} ph/s) 67 nm wide diffraction limited spot achieved with actual metrological data of mirrors.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Reducing Operating Temperature in Photovoltaic Modules

Reducing the operating temperature of photovoltaic modules increases their efficiency and lifetime. This can be achieved by reducing the production of waste heat or by improving the rejection of waste heat. We tested, using a combination of simulation and experiment, several thermal modifications in each category. To predict operating temperature and energy yield changes in response to changes to the module, we implemented a physics-based transient simulation framework based almost entirely on measured properties. The most effective thermal modifications reduced the production of waste heat by reflecting unusable light from the cell or the module. Consistent with previous results and verified in this work through year-long simulations, the ideal reflector resulted in an annual irradiance-weighted temperature reduction of 3.8 K for crystalline silicon (c-Si). Our results illustrate that more realistic reflector concepts must balance detrimental optical effects with the intended thermal effects to realize the optimal energy production advantage. Methods improving thermal conductivity or back-side emissivity showed only modest improvements of less than 1 K. We also studied a GaAs module, which uses high-efficiency and high-subbandgap reflectivity to operate at an annual irradiance-weighted temperature 12 K cooler than that of a c-Si module under the same conditions.

14 SOLAR ENERGY↗
DOE OSTI2015

Loss resilience for two-qubit state transmission using distributed phase sensitive amplification

We transmit phase-encoded non-orthogonal quantum states through a 5-km long fibre-based distributed optical phase-sensitive amplifier (OPSA) using telecom-wavelength photonic qubit pairs. The gain is set to equal the transmission loss to probabilistically preserve input states during transmission. While neither state is optimally aligned to the OPSA, each input state is equally amplified with no measurable degradation in state quality. These results promise a new approach to reduce the effects of loss by encoding quantum information in a two-qubit Hilbert space which is designed to benefit from transmission through an OPSA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

THE EFFECTS OF DARK MATTER ANNIHILATION ON COSMIC REIONIZATION

We revisit the possibility of constraining the properties of dark matter (DM) by studying the epoch of cosmic reionization. Previous studies have shown that DM annihilation was unlikely to have provided a large fraction of the photons which ionized the universe, but instead played a subdominant role relative to stars and quasars. The DM might, however, have begun to efficiently annihilate with the formation of primordial microhalos at z ∼ 100–200, much earlier than the formation of the first stars. Therefore, if DM annihilation ionized the universe at even the percent level over the interval z ∼ 20–100, it could leave a significant imprint on the global optical depth, τ . Moreover, we show that cosmic microwave background polarization data and future 21 cm measurements will enable us to more directly probe the DM contribution to the optical depth. In order to compute the annihilation rate throughout the epoch of reionization, we adopt the latest results from structure formation studies and explore the impact of various free parameters on our results. We show that future measurements could make it possible to place constraints on the DM’s annihilation cross-sections, which are at a level comparable to those obtained from the observations of dwarf galaxies, cosmic-ray measurements, and studies of recombination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Diagrammatic approach to nonlinear optical response with application to Weyl semimetals

Nonlinear optical responses are a crucial probe of physical systems including periodic solids. In the absence of electron-electron interactions, they are calculable with standard perturbation theory starting from the band structure of Bloch electrons, but the resulting formulas are often large and unwieldy, involving many energy denominators from intermediate states. This work gives a Feynman diagram approach to calculating nonlinear responses. This diagrammatic method is a systematic way to perform perturbation theory, which often offers shorter derivations and also provides a natural interpretation of nonlinear responses in terms of physical processes. Applying this method to second-order responses concisely reproduces formulas for the second-order-harmonic shift current. We then apply this method to third-order responses and derive formulas for third-order-harmonic generation and self-focusing of light, which can be directly applied to tight-binding models. Third-order responses in the semiclasscial regime include a Berry curvature quadrupole term, whose importance is discussed including symmetry considerations and when the Berry curvature quadrupole becomes the leading contribution. In conclusion, the method is applied to compute third-order optical responses for a model Weyl semimetal, where we find a new topological contribution that diverges in a clean material, as well as resonances with a peculiar linear character.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Spinning metasurface stack for spectro-polarimetric thermal imaging

Spectro-polarimetric imaging in the long-wave infrared (LWIR) region plays a crucial role in applications from night vision and machine perception to trace gas sensing and thermography. However, the current generation of spectro-polarimetric LWIR imagers suffers from limitations in size, spectral resolution, and field of view (FOV). While meta-optics-based strategies for spectro-polarimetric imaging have been explored in the visible spectrum, their potential for thermal imaging remains largely unexplored. In this work, we introduce an approach for spectro-polarimetric decomposition by combining large-area stacked meta-optical devices with advanced computational imaging algorithms. The co-design of a stack of spinning dispersive metasurfaces along with compressive sensing and dictionary learning algorithms allows simultaneous spectral and polarimetric resolution without the need for bulky filter wheels or interferometers. Our spinning-metasurface-based spectro-polarimetric stack is compact (<10×10×10cm) and robust, and it offers a wide field of view (20.5°). We show that the spectral resolving power of our system substantially enhances performance in machine learning tasks such as material classification, a challenge for conventional panchromatic thermal cameras. Our approach represents a significant advance in the field of thermal imaging for a wide range of applications including heat-assisted detection and ranging (HADAR).

Optics↗
DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Dynamic mitigation of EDFA power excursions with machine learning

Dynamic optical networking has promising potential to support the rapidly changing traffic demands in metro and long-haul networks. However, the improvement in dynamicity is hindered by wavelength-dependent power excursions in gain-controlled erbium doped fiber amplifiers (EDFA) when channels change rapidly. We introduce a general approach that leverages machine learning (ML) to characterize and mitigate the power excursions of EDFA systems with different equipment and scales. An ML engine is developed and experimentally validated to show accurate predictions of the power dynamics in cascaded EDFAs. Recommended channel provisioning based on the ML predictions achieves within 1% error of the lowest possible power excursion over 94% of the time. In conclusion, we also showcase significant mitigation of EDFA power excursions in super-channel provisioning when compared to the first-fit wavelength assignment algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

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

Non-resonant Raman optical activity from phase-space electronic structure theory

In order to model experimental non-resonant Raman optical activity, chemists must compute a host of second-order response tensors (e.g., the electric-dipole–magnetic-dipole polarizability) and their nuclear derivatives along a set of vibrational modes. While these response functions are almost always computed within a Born–Oppenheimer (BO) framework, here we provide a natural interpretation of the electric-dipole–magnetic-dipole polarizability within phase space electronic structure theory, a beyond-BO model whereby the electronic structure depends on nuclear momentum (P) in addition to nuclear position (R). By coupling to nuclear momentum, phase space electronic structure theory is able to capture the asymmetric response of the electronic properties to an external field, in so far as for a vibrating (non-stationary) molecule, $\frac{∂μ}{∂B}$≠$\frac{∂m}{∂F}$, where μ and m are the electrical linear and magnetic dipoles, and F and B are electric and magnetic fields. As an example, for a prototypical methyloxirane molecule, we show that phase space electronic structure theory is able to deliver a reasonably good match with experimental results in a manner that is formally invariant to gauge origin G 0 —provided that one uses a complete basis or, alternatively, gauge invariant atomic orbitals.

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

Ab initio leading order effective potential for elastic proton scattering based on the symmetry-adapted no-core shell model

Calculating microscopic optical potentials for elastic scattering at intermediate energies from light nuclei in an ab initio fashion within the Watson expansion has been established within the last few years. Based on the Watson expansion of the multiple scattering series, we employ a nonlocal translationally invariant nuclear density derived within the symmetry-adapted no-core shell model (SA-NCSM) framework from a chiral next-to-next-to-leading order (NNLO) nucleon-nucleon interaction and the very same interaction for a consistent full-folding calculation of the effective (optical) potential for nucleon-nucleus scattering for medium-heavy nuclei. The leading order effective (optical) folding potential is computed by integrating over a translationally invariant SA-NCSM one-body scalar density, spin-projected momentum distribution, and the Wolfenstein amplitudes 𝐴, 𝐶, and 𝑀. The resulting nonlocal potentials serve as input for a momentum space Lippmann-Schwinger equation. In the SA-NCSM, the model space is systematically up-selected using Sp⁡(3,ℝ) symmetry considerations. For the light nucleus of 6 He, we establish a systematic selection scheme in the SA-NCSM for scattering observables. Then, we apply this scheme to calculations of scattering observables, such as differential cross sections, analyzing powers, and spin rotation functions for elastic proton scattering from 20 Ne and 40 Ca in the energy regime between 65 and 200 MeV, and compare to available data. Furthermore, our calculations show that the leading order effective nucleon-nucleus potential in the Watson expansion of multiple scattering theory obtained from an up-selected SA-NCSM model space describes 40 Ca elastic scattering observables reasonably well to about 60 degrees in the center-of-mass frame, which coincides roughly with the validity of the NNLO chiral interaction used to calculate both the nucleon-nucleon amplitudes and the one-body scalar and spin nuclear densities.

Ab initio calculations↗
DOE OSTI2024

Effect of laminae count and manufacturing methods on mechanical properties of thin‐ply woven composites

Abstract Thin‐ply woven composites exhibit exceptional mechanical performance by delaying the onset of damage, making them suitable for high‐performance structural applications. This study outlines the impact of manufacturing techniques (vacuum bagging and hot pressing), ply count, and fiber waviness on the mechanical properties of aromatic thermosetting copolyester/carbon‐fiber (ATSP/CF) composites. The analysis encompasses several different ply counts, evaluating their effects on the in‐plane elastic modulus (0°–90°) and tensile strength. Results demonstrate that reducing the waviness (or crimp) ratio significantly enhances the in‐plane elastic modulus, with improvements up to 188%, highlighting the importance of fiber alignment. Vacuum bagging produced ply thicknesses from 128 to 58 μm for 1–36 plies, with in‐plane elastic moduli from 30.3 to 87.2 GPa, and 4‐ and 8‐ply samples showed approximately 40% higher stiffness than those made by hot pressing. ATSP resin with high thermal stability (up to 400°C) and recyclability was used. Furthermore, this study highlights the microstructural enhancements achieved through vacuum bagging, as revealed by scanning electron and optical microscopy, and micro‐computed tomography imaging. This paper provides insights into damage mitigation and achieving enhanced mechanical properties by controlling fiber waviness using vacuum bagging and higher ply count in thin‐ply ATSP/CF composites. Highlights Crimp ratio reduction enhances elastic in‐plane elastic modulus up to 188%. Vacuum bagging increases modulus over the hot pressing manufacturing method by 40%. Lowering thickness‐per‐ply increases failure strain from 0.8% to 1.2%. Explored the performance of a novel ATSP matrix with high recyclability and thermal stability.

Kushwaha, Shashank [The Grainger College of Engine↗
DOE OSTI2019

Role of Invasive and Non-invasive Imaging Tools in the Diagnosis and Optimal Treatment of Patients with Spontaneous Coronary Artery Dissection

Purpose of Review: Spontaneous coronary artery dissection (SCAD) is a serious non-atherosclerotic disease, most frequently presenting as an acute coronary syndrome and affecting female patients. Considering that diagnosis of SCAD is often elusive, and its interventional treatment is associated to a higher rate of complications than obstructive atherosclerotic disease, we aim to review all the imaging tools currently available for the optimal diagnosis and treatment of this condition. Recent Findings: The developments in both invasive and non-invasive imaging alternatives to coronary angiography, such as intravascular ultrasound, optical coherence tomography, and computed coronary angiography, have largely contributed to appraise the epidemiology of SCAD, understand its causative pathophysiological mechanisms, and improve our ability to confirm doubtful cases of SCAD. Intracoronary imaging is also a valuable in deciding the best therapeutic approach and in guiding interventions in those patients requiring percutaneous treatment. Furthermore, non-invasive imaging is a key tool in ruling out significant extracoronary vascular abnormalities which frequently occur in patients with underlying conditions like fibromuscular dysplasia who develop SCAD. Summary: Main imaging tools employed in SCAD cases could have advantages and drawbacks. Focusing on different types of SCAD, operators should be able to choose the best imaging technique for diagnosis, management, and follow-up.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Characterization of weld metal microstructure in a Ni-30Cr alloy with additions of niobium and molybdenum

Additions of niobium (Nb) and molybdenum (Mo) were made to an Alloy 690 base alloy in order to investigate the formation of a eutectic constituent at the end of solidification and to evaluate the effect of the eutectic liquid on backfilling (or healing) of solidification cracks. Solidification cracking was induced using the cast pin tear test (CPTT) and regions of backfilling were located and characterized via optical and electron microscopy. Computational predictions of fraction eutectic and composition of the eutectic constituent were compared to experimental findings and were found to correlate well in both cases. The extent of crack backfilling increased significantly with increasing Nb content, but the addition of Mo did not seem to influence the amount of eutectic constituent or the degree of backfilling. SEM/EDS analysis confirmed that the eutectic composition is constant and that increasing Nb above 4 wt% has little effect on expanding the solidification temperature range, but has a beneficial effect on mitigating solidification cracking by a crack healing effect. - Highlights: • Increasing fraction eutectic as a function of Nb, as predicted by ThermoCalc™, is consistent with image analysis results. • Nb, unlike Mo, had a significant effect on the fraction eutectic formed. • Both influence the composition of the eutectic. • Thermocalc™ predictions regarding Nb content in eutectic are consistent with EDS results, but are high for the Mo content. • Increased levels of niobium resulted in a higher degree of crack backfilling and leads to a lower cracking susceptibility. • Mo may influence the eutectic liquid along solidification grain boundaries, improving backfill and thus cracking resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Two-phase accurate multiplexed structured image capture (2pAc-MUSIC)

Multiplexed Structural Image Capture (MUSIC) technique uses modulation of light from a scene prior to imaging to encode the temporal evolution of target into spatial frequency shifts, with each shift corresponding to a unique time and resulting in individual distinct snapshots. Computational-processing of the multiplexed single-shot image can recover the nanosecond-resolution scene evolution. One of the limitations is the loss of spatial resolution of the recovered image due to limitations of the low-pass spatial frequency filtering depth. Here we demonstrated that two images with complementary spatial phases can be used to enhance the spatial resolutions. For this application, 2 Phase Accurate (2pAc)-MUSIC is implemented that a scene is encoded with two complementary phases. The increased spatial information captured reduces the lower frequency noise in the Fourier domain found in single-phase MUSIC. A recovery algorithm combines the 180-degree spatial frequency shifted images into a single scene and applies a spatial filter in the Fourier domain that has a larger depth than previously possible to achieve a scene with increased spatial resolution. The 2pAc-MUSIC can effectively enhance the spatial resolution by removing the overlapping zero-order spatial frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Toggling Stereochemical Activity through Interstitial Positioning of Cations between 2D V 2 O 5 Double Layers

The 5/6s 2 lone-pair electrons of p-block cations in their lower oxidation states are a versatile electronic and geometric structure motif that can underpin lattice anharmonicity and often engender electronic and structural instabilities that underpin the function of active elements in nonlinear optics, thermochromics, thermoelectrics, neuromorphic computing, and photocatalysis. In contrast to periodic solids where lone-pair-bearing cations are part of the structural framework, installing lone-pair-bearing cations in the interstitial sites of intercalation hosts provides a means of a systematically modulating electronic structure through the choice of the group and the period of the inserted cation while preserving the overall framework connectivity. The extent of stereochemical activity and the energy positioning of lone-pair-derived mid-gap states depend on the cation identity, stoichiometry, and strength of anion hybridization. V 2 O 5 polymorphs are versatile insertion hosts that can accommodate a broad range of s-, p-, and d-block cations. However, the insertion of lone-pair-bearing cations remains largely underexplored. In this article, we examine the implications of varying the 6s 2 cations situated in interlayer sites between condensed [V 4 O 10 ] n double layers. Systematic modulations of lattice distortions, electronic structure, and magnetic ordering are observed with increasing strength of stereochemical activity from group 12 to group 14 cations. We compare and contrast p-block-layered M x V 2 O 5 (M = Hg, Tl, and Pb) compounds and map the significance of local off-centering arising from the stereochemical activity of lone-pair cations to the emergence of filled antibonding lone-pair 6s 2 –O 2p-hybridized mid-gap states mediated by second-order Jahn–Teller distortions. Crystallographic studies of cation coordination environments and the resulting modulation of V–V interactions have been used in conjunction with variable-energy hard X-ray photoelectron spectroscopy measurements, first-principles electronic structure calculations, and crystal orbital Hamilton population analyses to decipher the origins of stereochemical activity. Magnetic susceptibility measurements reveal antiferromagnetic signatures for all the three compounds. However, the differences in V–V interactions significantly affect the energy balance of the superexchange interactions, resulting in an ordering temperature of 160 and 260 K for Hg 0.5 V 2 O 5 and δ-Tl 0.5 V 2 O 5 , respectively, as compared to 7 K for δ-Pb 0.5 V 2 O 5 . In δ-Pb 0.5 V 2 O 5 , the strong stereochemical activity of electron lone pairs and the resulting electrostatic repulsions enforce superlattice ordering, which strongly modifies the electronic localization patterns along the [V 4 O 10 ] slabs, resulting in disrupted magnetic ordering and an anomalously low ordering temperature. The results demonstrate a versatile strategy for toggling the stereochemical activity of electron lone pairs to modify the electronic structure near the Fermi level and to mediate superexchange interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗