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At least 577 records · Page 32

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗

An automated cluster surface scanning method for exploring reaction paths on metal-cluster surfaces

Metal-cluster surfaces present a wide variety of unique coordination environments. This complexity makes it difficult to manually probe the surface reactivity of such clusters. Here, we present a simple and automated method to systematically discover reaction pathways on cluster surfaces, based on the automated cluster surface scanning (ACSS) technique for mapping out potential energy surfaces. We showcase our method on 55-atom icosahedral Cu and Ag clusters, where we determine the activation energies of four elementary steps common in heterogeneous catalysis – hydrogen recombination (H* + H* → H 2 * + *), oxygen recombination (O* + O* → O 2 * + *), water formation (OH* + H* → H 2 O* + *), and CO oxidation (CO* + O* → CO 2 * + *) – with density functional theory calculations (DFT-PBE + D3). We show that the ACSS method requires significantly less human effort than the established manually performed climbing-image nudged elastic band (MP + CI-NEB) technique and locates transition states with comparable accuracy (root-mean-squared error of 0.10 eV) and similar computational cost. Rigorous sampling of the potential energy surface with the ACSS method allows one to locate all lowest-energy reaction pathways obtained via the MP+CI-NEB approach, as well as alternative pathways that one may have missed with the MP+CI-NEB approach due to the many possible pathways available on these clusters. The accuracy and efficiency afforded by the ACSS method could enable high-throughput exploration of the diverse reactivity of metal clusters.

36 MATERIALS SCIENCE↗

Susceptibility weighted MRI pinpoints spontaneous intracerebral hemorrhage in stroke-prone spontaneously hypertensive rats

Purpose: To find magnetic resonance imaging (MRI) precursors of spontaneous intracerebral hemorrhage in stroke-prone spontaneously hypertensive rats (SHRSP). Method: SHRSP rats were used with both a low/high salt (n = 18 or 11) Japanese diet and salty drinking water to generate spontaneous intracerebral hemorrhage (ICH). Various MRI sequences, and in particular, susceptibility weighted imaging (SWI), were used and combined with a gadolinium (Gd) contrast agent or oxygen gas to identify the rupture of the blood brain barrier (BBB) and the temporal ICH. Results: Most rats developed hypertensive ICH stroke in the high salt group during the 10–13 week period compared to only one third of rats in the low salt group during the 14–18 week period. The location of stroke for both the low/high-salt groups was highest in the striatum (58%/43%), followed by the cortex (21%/30%). The edematous enhancement on T2 weighted (T2W) imaging or Gd based T1 weighted (Gd-T1W) imaging due to the ruptured BBB preceded the striatal hemorrhages seen on SWI. The most recent bleeds were observed on temporal SWI or on oxygen-enhanced SWI. The mode of the volume of bleeds was 0.4 mm 3 . A positive correlation between susceptibility x volume and R2* x volume of the bleeds was observed. Conclusions: SHRSP rats with the high salt diet effectively generated a hypertensive hemorrhagic stroke which could be monitored by various MRI sequences. The venous dilation on SWI may precede any abnormality on T2W or Gd-T1W imaging. The edematous enhancement on T2W or Gd-T1W indicated a BBB breakdown that may precede striatal ICH by several days. This suggests the need for immediate treatment to improve outcome if this finding is observed. Here, the use of oxygen with SWI was able to help differentiate old bleeds from very recent bleeds.

60 APPLIED LIFE SCIENCES↗

Experimental Investigation of Nanosecond and Subnanosecond Pulsed DBD in Atmospheric Air: Fast Imaging and Spectroscopy

Dielectric barrier discharge (DBD), as an easy and simple way of generation of non-thermal plasma, has found a number of applications in variuos fields. However, development of a homogeneous, or uniform, DBD that would operate at atmospheric pressure conditions in atmospheric air, would open a number of new applications in various fields from thin film coatings to plasma medicine. Unfortunately, at atmospheric pressure, a uniform DBD can be easily transformed into a filamentary dielectric DBD; therefore some serious issues arise, such as gas heating due to strong discharges in the random microdischarge channel and non-uniform energy distribution, which adversely affect applications. These issues traditionally are solved by the use of an appropriate working gas composition, an alternating current driving frequency, lowering of gas pressure, etc. The transitions between discharge modes in the same experimental conditions have been thoroughly investigated in nitrogen, rare gases and their mixtures with air and other gases. In many cases (for example, in plasma medicine), these methods, especially those related to gas composition and pressure, may not be applied in a convenient manner. Recent advances in pulsed power technology permitted application of much faster voltage rise times (including the subnanosecond range) and short (few nanoseconds) pulses, and revealed that uniform DBD can, in fact, be generated in atmospheric air. Such discharges are in the great interest for many applications, however to date there still little understanding of the mechanisms of their operation and characteristics. Currently, there is no adequate model of the uniform dielectric barrier discharge development in atmospheric air. Although extensive studies have been performed on understanding of the nature of the pulsed DBD uniformity, until now there is still little understanding of the mechanism of the DBD transition from the filamentary mode to uniform mode. One of the reasons for this is that development of streamers, and later – filaments, occurs on the sub-nanosecond and nanosecond time scales, and therefore requires imaging and other diagnostic techniques with corresponding speed of registration. Recently developed technologies allow such studies. Here we demonstrate that DBD uniformity strongly depends on applied electric field in the discharge gap. More specifically, the discharge uniformity may be achieved in the case when two conditions are satisfied: (1) stong overvoltage in the discharge gap (provided by fast rise times), when anode-directed streamers are formed, and (2) short pulse duration that prevents discharge overheating due to rising conductivity (current) which leads to formation of filaments. We show that by controlling the applied (global) electric field in ns-pulsed DBD, it is possible to control the uniformity of the discharge. In addition, this offers better control of the discharge chemistry due to local changes of electric fields and therefore electron energy distribution function.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Microsphere LiMn 0.6 Fe 0.4 PO 4 /C cathode with unique rod-like secondary architecture for high energy lithium ion batteries

LiMn x Fe 1-x PO 4 /C is considered a promising next-generation cathode material with significant commercial potential, inheriting the safety of LiFePO 4 while offering higher energy densities. However, the extremely low conductivity and the Jahn-Teller effect induced by Mn 3+ limit its practical capacity and rate performance. Effective modifications can be achieved through particle nanonization and uniform carbon coating. Here, in this work, we synthesized microspherical LiMn 0.6 Fe 0.4 PO 4 /C cathode materials using a hydrothermal method combined with spray drying carbon coating. The cathode material exhibits a microsphere structure composed of aggregated nanorods with a uniform 3 nm carbon coating, showing good dispersibility, small specific surface area and high tap density. In-situ diffraction analysis showed that expanding the single-phase solid solution region during (de)lithiation can reduce the energy barrier for electron transport, improve the kinetics of the (dis)charge process, and enhance both cycling and rate performance. The initial capacity at 0.1C can reach 155 mAh/g, and the capacity remains at 133.5 mAh/g with a retention rate of 97.1 % after 300 cycles. The synergistic effect of particle nanonization and uniform carbon coating endows the LiMn x Fe 1-x PO 4 /C material with excellent electrochemical performance.

25 ENERGY STORAGE↗

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗

A dynamic solvent chamber propagation estimation framework using RNN for warm solvent injection in heterogeneous reservoirs

Warm solvent injection (WSI), injecting low-temperature solvent into formations to reduce the viscosity of heavy oil, is a clean technology for heavy oil production through reducing greenhouse gas emissions and water usage. The success of WSI operation depends on the uniform development and propagation of solvent chambers in reservoirs. However, reservoir heterogeneity stemming from shale barriers plays a detrimental role in the conformance of solvent chamber development and oil production rate. In this work, we developed a novel recurrent neural network (RNN)-based framework with the capability of efficiently tracking and estimating the solvent chamber positions in heterogeneous reservoirs based on only production time-series data. The developed estimation model utilizes the “sequence-to-sequence" mapping methodology to correlate observed production time-series sequence and solvent chamber edge sequence via a long short-term memory (LSTM) algorithm. The trained RNN models exhibit high accuracy, evidenced by the predicted dynamic solvent chamber locations match the corresponding true locations from numerical simulation, with a high coefficient of determination (R 2 ) and a low mean squared error. Specifically, the achieved R 2 values exceed 0.98 on both the training and testing data. The developed RNN-based workflow was tested via several cases from both regularly- and irregularly-shaped shale barriers, and the results were promising. The predicted solvent chambers showed strong agreement with those obtained from numerical simulations. The major benefits of this workflow include reducing computational time and saving overall monitoring and tracking costs for conventional techniques. In conclusion, the present work would provide a good demonstration of the capability of practical integration of machine learning methods in solving engineering problems.

58 GEOSCIENCES↗

Supported Oxygen Evolution Catalysts by Design: Toward Lower Precious Metal Loading and Improved Conductivity in Proton Exchange Membrane Water Electrolyzers

Reducing the precious metal content of water oxidation catalysts for proton-exchange-membrane water electrolyzers remains a critical barrier to their large-scale deployment. Herein, we present an engineered architecture for supported iridium catalysts, which enables decreased precious metal content and improved activity and conductivity. The improvement in performance at lower precious metal loading is realized by the deposition of a conformal layer of platinum nanoparticles on titanium dioxide (TiO 2 ) using a facile photoreduction method to prepare conductive layer coated supports (CCSs). Platinum nanoparticles are homogeneously dispersed on TiO 2 , and the conductivity of the subsequent catalysts with 39 wt % precious group metal loadings is significantly higher than the commercial 75 wt % loaded IrO 2 -TiO 2 catalysts. The conformal conductive layer also maintains an enhanced conductivity and electrochemical activity upon thermal annealing when compared to catalysts without the conductive layer and nonconformal heterogeneous conductive layer. The iridium mass activity from half-cell studies shows a 141% improvement for CCS supported catalysts at 42% lower loadings compared to the commercial catalysts. The conductive layer also improves the single cell electrolyzer performance at a similar catalyst loading in comparison to a commercial state-of-the-art catalyst. Here, we correlate the physical properties of the engineered catalysts with their electrochemical performance in electrolyzers to understand structure-activity relationships, and we anticipate further performance improvements upon synthesis and materials optimizations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determinants of rural-urban differences in health care provider visits among women of reproductive age in the United States

Background Rural health disparities and access gaps may contribute to higher maternal and infant morbidity and mortality. Understanding and addressing access barriers for specialty women’s health services is important in mitigating risks for adverse childbirth events. The objective of this study was to investigate rural-urban differences in health care access for women of reproductive age by examining differences in past-year provider visit rates by provider type, and quantifying the contributing factors to these findings. Methods and findings Using a nationally-representative sample of reproductive age women (n = 37,026) from the Medical Expenditure Panel Survey (2010–2015) linked to the Area Health Resource File, rural-urban differences in past-year office visit rates with health care providers were examined. Blinder-Oaxaca decomposition analysis quantified the portion of disparities explained by individual- and county-level sociodemographic and provider supply characteristics. Overall, there were no rural-urban differences in past-year visits with women’s health providers collectively (65.0% vs 62.4%), however differences were observed by provider type. Rural women had lower past-year obstetrician-gynecologist (OB-GYN) visit rates than urban women (23.3% vs. 26.6%), and higher visit rates with family medicine physicians (24.3% vs. 20.9%) and nurse practitioners/physician assistants (NPs/PAs) (24.6% vs. 16.1%). Lower OB-GYN availability in rural versus urban counties (6.1 vs. 13.7 providers/100,000 population) explained most of the rural disadvantage in OB-GYN visit rates (83.8%), and much of the higher family physician (80.9%) and NP/PA (50.1%) visit rates. Other individual- and county-level characteristics had smaller effects on rural-urban differences. Conclusion Although there were no overall rural-urban differences in past-year visit rates, the lower OB-GYN availability in rural areas appears to affect the types of health care providers seen by women. Whether rural women are receiving adequate specialized women’s health care services, while seeing a different cadre of providers, warrants further investigation and has particular relevance for women experiencing high-risk pregnancies and deliveries.

60 APPLIED LIFE SCIENCES↗

Algae cultivation systems and methods adapted for weather variations

Algae cultivation systems and methods account for weather variations that can affect algae cultivation. In one system, an open raceway algae cultivation system includes a channel having a high section and a low liquid collection section. The channel is sloped to allow substantially all of an algae cultivation fluid in the high section to flow downwardly into the low liquid collection section. A barrier is removably positioned in the high section and a drain is positioned in the high section such that, when substantially all of the algae cultivation fluid has collected in the low liquid collection section, any rainwater that falls in the high section flows into the drain, without the rainwater mixing with the algae cultivation fluid in the low liquid collection section.

59 BASIC BIOLOGICAL SCIENCES↗

Multiscale, mechanistic calculation of the effective silver diffusion coefficient in polycrystalline silicon carbide: application to silver release in AGR-1 TRISO particles

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, the effective diffusion coefficient of the fission product Ag through the grain boundary (GB) network is calculated using a combination of atomistic and phase-field methods. Atomistic calculations of Ag diffusivity in SiC bulk and GBs are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Since GBs serve as pathways for Ag diffusion, Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗

Dynamic Restructuring Induced Oxygen Activation on AgCu Near Surface Alloys

Recent studies have shown that the addition of Cu to Ag catalysts improves their epoxidation performance by increasing the overall selectivity of the bimetallic catalyst. We have prepared AgCu near-surface alloys and used scanning tunneling microscopy to gain an atomistic picture of O 2 dissociation on the bimetallic system. These data reveal a higher dissociative sticking probability for O 2 on AgCu than Ag(111), and density functional theory (DFT) confirms that the O 2 dissociation barrier is 0.17 eV lower on the alloy. Surprisingly, we find that after a slow initial uptake of O 2 , the sticking probability increases exponentially. Further DFT calculations indicate that surface oxygen reverses the segregation energy for AgCu, stabilizing Cu atoms in the Ag layer. These single Cu atoms in the Ag surface are found to significantly lower the O 2 dissociation barrier. Altogether, these results explain nonlinear effects in the activation of O 2 on this catalytically relevant surface alloy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Forte: A suite of advanced multireference quantum chemistry methods

Software development plays a critical role in advancing quantum chemistry, enabling the exploration of new fundamental theoretical ideas and modeling systems of ever-increasing complexity. In the past decade, the availability of quantum chemistry packages that use modular designs and provide application programming interfaces (APIs) has enabled the creation of specialized software plugins, enhancing the capabilities of the original codes. Here, the availability of well-documented APIs is particularly beneficial in the context of academic scientific software development because it reduces the entry barrier for new developers and shields them from the complexities of large software projects.

74 ATOMIC AND MOLECULAR PHYSICS↗

Full‐dimensional coupled‐channel statistical approach to atom‐triatom systems and applications to H/D + O 3 reaction

Abstract The statistical quantum model (SQM), which assumes that the reactivity is controlled by entrance/exit channel quantum capture probabilities, is well suited for chemical reactions with a long‐lived intermediate complex. In this work, a time‐independent coupled‐channel implementation of the SQM approach is developed for atom‐triatom systems in full dimensionality. As SQM treats the capture dynamics quantum mechanically, it is capable of handling quantum effects such as tunneling. A detailed study of the H/D + O 3 capture dynamics was performed by applying the newly developed SQM method on an accurate global potential energy surface. Agreement with previous ring polymer molecular dynamics (RPMD) results on the same potential energy surface is excellent except for very low temperatures. The SQM results are also in reasonably good agreement with available experimental rate coefficients. The strong H/D kinetic isotope effect underscores the dominant role of quantum tunneling under an entrance channel barrier at low temperatures.

Yang, Dongzheng↗

Electrical Control of Magnetic Resonance in Phase Change Materials

Metal–insulator transitions (MITs) in resistive switching materials can be triggered by an electric stimulus that produces significant changes in the electrical response. When these phases have distinct magnetic characteristics, dramatic changes in the spin excitations are also expected. The transition metal oxide La 0.7 Sr 0.3 MnO 3 (LSMO) is a ferromagnetic metal at low temperatures and a paramagnetic insulator above room temperature. When LSMO is in its metallic phase, a critical electrical bias has been shown to lead to an MIT that results in the formation of a paramagnetic resistive barrier transverse to the applied electric field. Using spin-transfer ferromagnetic resonance spectroscopy, we show that even for electrical biases less than the critical value that triggers the MIT, there is magnetic phase separation, with the spin-excitation resonances varying systematically with applied bias. Therefore, voltage-triggered MITs in LSMO can alter magnetic resonance characteristics, offering an effective method for tuning synaptic weights in neuromorphic circuits.

36 MATERIALS SCIENCE↗

Effect of an oxide layer on high velocity impact of tantalum particles characterized using molecular dynamics

Micro-cold spray, also commonly referred to as the aerosol deposition method or vacuum kinetic spraying, is a process for depositing nanostructured films of metals and ceramics by impacting solid nanoparticles at high velocity onto a substrate at room temperature and at low pressures. Tantalum films deposited by micro-cold spray are desirable because tantalum is non-reactive to certain molten metals and can therefore serve as a non-reactive barrier coating. However, unlike most other metals deposited by micro-cold spray, tantalum quickly forms an oxide layer when exposed to air. In the deposition of films using traditional cold spray with much larger particles, native oxides must fracture for particle–substrate bonding to occur. Furthermore, the fraction of the particle that is oxidized in micro-cold spray and the strain rates experienced by the particles upon impact are both much larger than in cold spray, suggesting that the role of the oxide on film deposition may be distinct. The effect of this oxide layer on particle deformation and adherence to a substrate under high strain rates is studied using molecular dynamics simulations. The effect of oxide layer thickness, particle diameter, and impact velocity are examined.

42 ENGINEERING↗

High accuracy barrier heights, enthalpies, and rate coefficients for chemical reactions

Abstract Quantitative chemical reaction data, including activation energies and reaction rates, are crucial for developing detailed kinetic mechanisms and accurately predicting reaction outcomes. However, such data are often difficult to find, and high-quality datasets are especially rare. Here, we use CCSD(T)-F12a/cc-pVDZ-F12// ω B97X-D3/def2-TZVP to obtain high-quality single point calculations for nearly 22,000 unique stable species and transition states. We report the results from these quantum chemistry calculations and extract the barrier heights and reaction enthalpies to create a kinetics dataset of nearly 12,000 gas-phase reactions. These reactions involve H, C, N, and O, contain up to seven heavy atoms, and have cleaned atom-mapped SMILES. Our higher-accuracy coupled-cluster barrier heights differ significantly (RMSE of ∼5 kcal mol −1 ) relative to those calculated at ω B97X-D3/def2-TZVP. We also report accurate transition state theory rate coefficients $${k}_{\infty }(T)$$ k ∞ ( T ) between 300 K and 2000 K and the corresponding Arrhenius parameters for a subset of rigid reactions. We believe this data will accelerate development of automated and reliable methods for quantitative reaction prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗