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At least 1,801 records · Page 100

Carbon-efficient conversion of natural gas and natural-gas condensates to chemical products and intermediate feedstocks via catalytic metal–organic framework (MOF) chemistry

The net-zero carbon emission scenario of stopping hydrocarbon use as fuel is unlikely to end the extraction of fossil hydrocarbons. Remaining will be a sizable need for hydrocarbons as feedstocks for commodity chemicals destined for transformation into polymers, manufacturing-relevant intermediates, and value-added chemicals. Historically, the primary feedstock source has been oil. Over the past dozen years, however, fracking-based extraction of shale-trapped natural gas from known enormous reserves, in North America, has resulted in feedstock sourcing instead from wet shale gas. This shift has transformed the catalytic chemistry of commodity chemical manufacturing. In this paper, following a brief discussion of the merits and limitations of crystallographically well-defined metal–organic frameworks (MOFs) as model catalysts and catalyst-supports, we examined their applications for understanding and potentially enabling carbon-economical, catalytic transformation of C 1 , C 2 , C 3 , and C 4 components of natural gas to desirable commodity chemicals, intermediates, or model compounds.

03 NATURAL GAS↗

Conversion of plastic waste into high-value lubricants: techno-economic analysis and life cycle assessment

Given the low recycling rate of plastic waste in the United States due to low economic incentives, it is of great interest to develop a technology to upgrade plastic waste with favorable economics. Plastic upcycling to valuable chemicals could ensure a circular economy for plastics and reduce the environmental burden caused by their end use cycle and disposal. A conceptual facility to convert 250 metric ton (MT) per day of plastic waste was modeled; the main product was a high-quality liquid (HQL) with a similar performance to polyalphaolefin (PAO) lubricants. The modeled process had a lubricant yield of up to 90% based on the experimental results at the laboratory scale. Techno-economic analysis (TEA) and life cycle assessment (LCA) were also performed to evaluate the process economics and its environmental impact. By using a mixture of colored and natural high-density polyethylene (HDPE), the production cost was in the range of 0.6–1.98 dollars per kg of lubricant, depending on the operating conditions. The life cycle emissions were in the range of 0.48–1.2 kg CO 2e kg Lub -1 showing, for the best case scenario, a 52% reduction relative to the emissions for petroleum lubricants, and a 74% reduction relative to the emissions for PAO lubricants. Finally, the impacts of the lubricant yield, the catalyst amount, and reaction time were evaluated, and their effect on the final production cost was discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical detection of alcohols with a Cu($\tiny{I}$)HETPHEN complex by reversible aldehyde to hemiacetal conversion

A heteroleptic copper(I) bis(phenanthroline) complex with aldehyde groups at the 4,7 positions of the phenanthroline ligand was synthesized. Here, the complex is responsive to alcohol, resulting in a distinct colour change caused by the facile reaction of the aldehyde group with alcohol, forming a hemiacetal product. The aldehyde species can be regenerated after heating the intermediate at 80 °C for 10 minutes, demonstrating the reusability of the complex for alcohol detection. This work presents a new strategy for applying transition metal complexes in small molecule sensing by installing functional groups in the secondary coordination sphere which reversibly react with analytes.

36 MATERIALS SCIENCE↗

Deep learning of electrochemical CO 2 conversion literature reveals research trends and directions

Large-scale and openly available material science databases are mainly composed of computer simulation results rather than experimental data. Some examples include the Materials Project, Open Quantum Materials Database, and Open Catalyst 2022. Unfortunately, building large-scale experimental databases remains challenging due to the difficulties in consolidating locally distributed datasets. In this work, focusing on the catalysis literature of CO 2 reduction reactions (CO 2 RRs), we present a machine learning (ML)-based protocol for selecting highly relevant papers and extracting important experimental data. First, we report a document embedding method (Doc2Vec) for collecting papers of greatest relevance to the specific target domain, which yielded 3154 CO 2 RR-related papers from six publishers. Next, we developed named entity recognition (NER) models to extract twelve entities related to material names (catalyst, electrolyte, etc.) and catalytic performance (Faradaic efficiency, current density, etc.). Further, among several tested models, the MatBERT-based approach achieved the highest accuracy, with an average F1-score of 90.4% and an F1-score of 95.2% in a boundary relaxation evaluation scheme. The accurate and accelerated NER-based data extraction from a large volume of catalysis literature enables temporal trend analyses of the CO 2 RR catalysts, products, and performances, revealing the potentially effective material space in CO 2 RRs. While this work demonstrates the effectiveness of our ML-based text mining methods for specifically CO 2 RR literature, the methods and approach are applicable to and may be used to accelerate the development of other catalytic chemical reactions.

36 MATERIALS SCIENCE↗

ChemPren: a new and economical technology for conversion of waste plastics to light olefins

With the ever-increasing demand for plastics, sustainable recycling methods are key necessities. Here, the current plastics industry can manage to recycle only 10% of the 400 million metric tons of plastic produced globally. Waste plastics, in the current infrastructure, land up mostly in landfills. Although a lot of research efforts have been spent on processing and recycling co-mingled mixed plastics, energy-efficient sustainable and scalable routes for plastic upcycling are still lacking. Catalytic valorization of waste plastic feedstock is one of the potential scalable routes for plastic upcycling. Silica-alumina based materials, and zeolites have shown a lot of promise. A major interest lies in restricting catalyst deactivation, and refining product selectivity and yield for such catalytic processes. This article highlights ChemPren technology as a clean energy solution to waste plastic recycling. Co-mingled, mixed plastic feedstock along with spray dried, attrition resistant, ZSM-5 containing catalysts is preprocessed with an extruder to form optimally sized particles and fed into a fluidized bed reactor for short contact times to produce selectively and in high yields ethylenes, propylenes and butylenes. This techno-economic perspective indicates that the ChemPren technology can produce propylene at $\$$0.16 per lb, whereas the current selling price of virgin propylene is $0.54 per lb. This technology can serve as a platform for mixed plastic upcycling, with more advancements necessary in the form of robust and resilient catalysts and reactor operation strategies for tuning product selectivity.

25 - ENERGY STORAGE↗

Application of real‐time nonlinear model predictive control for wave energy conversion

Abstract This article presents an approach to implement a Nonlinear Model Predictive Controller (NMPC) in real‐time with a non‐standard cost index. The proposed technique's applications are presented to maximize the energy produced by a Wave Energy Converter (WEC) when the cost index is a non‐quadratic piecewise discontinuous functional of some design variables. The presented framework is based on pseudo‐quadratisation and weight scheduling, which is implemented using the ACADO toolkit for MATLAB/Simulink. The proposed strategy features code generation and deployment on the real‐time target machines for industrial applications. The simulations and experiments confirm the success of the proposed approach in achieving the feasible operation of the NMPC and an optimal power capture by the wave energy converters.

16 TIDAL AND WAVE POWER↗

Filament-assisted mode conversion in magnetized plasmas

At density filaments in magnetized plasmas, electromagnetic waves are guided along the filament ("wave-filament bound states"). Several wave-filament bound states exist beyond those predicted. Here, the new bound states occur under experimentally relevant conditions, and are especially common under typical NSTX conditions, where they are a plausible mechanism for the experimentally observed power losses in the edge plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Proton-conducting oxides for energy conversion and storage

Proton-conducting oxides are a class of solid-state ion-conducting ceramic materials that demonstrate significant hydrogen ion (proton) conductivity at intermediate temperatures (e.g., 300–700 °C). They are garnering significant attention due to several unique characteristics that distinguish them from both higher temperature oxygen ion conducting oxides and lower temperature proton-conducting polymers. By enabling proton-mediated electrochemistry under both dry and wet environments at moderate temperatures, protonic ceramics provide unique opportunities to enhance or synergize a diverse range of complementary electrochemical and thermochemical processes. Because of this potential, significant efforts have been devoted to advancing numerous energy-related applications using these materials. This review aims to comprehensively summarize these applications and analyze the most up-to-date and future developments of proton-conducting oxides. We aim to bring together this diverse subject matter by integrating the fundamentals of proton-conducting oxides with application-oriented insights. We begin with a historical roadmap, followed by a basic overview of the materials, theories and fundamentals, and fabrication and processing technologies underlying the field. The central section of our review summarizes major applications and developments of proton-conducting ceramics, ranging from maturing applications approaching commercialization to embryonic technologies just now emerging from the lab. These include protonic ceramic fuel cells, protonic ceramic electrolysis cells, reversible protonic ceramic electrochemical cells, protonic ceramic membrane reactors, and protonic ceramic electrochemical reactors. For each application, we analyze both the prospects and challenges and offer recommendations for future research directions so that tomorrow's researchers can continue to advance the development and commercialization of these fascinating materials.

Duan, Chuancheng (ORCID:0000000218261415)↗

Computational fluid dynamics analysis of char conversion in Sandia’s pressurized entrained flow reactor

Design and analysis of practical reactors utilizing solid feedstocks rely on reaction rate parameters that are typically generated in lab-scale reactors. Evaluation of the reaction rate information often relies on assumptions of uniform temperature, velocity, and species distributions in the reactor, in lieu of detailed measurements that provide local information. This assumption might be a source of substantial error, since reactor designs can impose significant inhomogeneities, leading to data misinterpretation. Spatially resolved reactor simulations help understand the key processes within the reactor and support the identification of severe variations of temperature, velocity, and species distributions. In this work, Sandia’s pressurized entrained flow reactor is modeled to identify inhomogeneities in the reaction zone. Tracer particles are tracked through the reactor to estimate the residence times and burnout ratio of introduced coal char particles in gasifying environments. The results reveal a complex mixing environment for the cool gas and particles entering the reactor along the centerline and the main high-speed hot gas reactor flow. Furthermore, the computational fluid dynamics (CFD) results show that flow asymmetries are introduced through the use of a horizontal gas pre-heating section that connects to the vertical reactor tube. Computed particle temperatures and residence times in the reactor differ substantially from the idealized plug flow conditions typically evoked in interpreting experimental measurements. Furthermore, experimental measurements and CFD analysis of heat flow through porous refractory insulation suggest that for the investigated conditions (1350 °C, <20 atm), the thermal conductivity of the insulation does not increase substantially with increasing pressure.

47 OTHER INSTRUMENTATION↗

Microhydration of the metastable N -Protomer of 4-Aminobenzoic acid by condensation at 80 K: H/D exchange without conversion to the more stable O- protomer

4-Aminobenzoic acid (4ABA) is a model scaffold for studying solvent-mediated proton transfer. Although protonation at the carboxylic group (O-protomer) is energetically favored in the gas phase, the N-protomer, where the proton remains on the amino group, can be kinetically trapped by electrospray ionization of 4ABA in an aprotic solvent such as acetonitrile. Here we report the formation of the hydrated deuterium isotopologues of the N-protomers, RND 3 + ·(H 2 O) n=1-3 , (R=C 6 H 4 COOD), which are generated by condensing water molecules onto the bare N-protomers in a liquid nitrogen cooled, radiofrequency octopole ion trap at 80 K. The product clusters are then transferred to a 20 K cryogenic ion trap where they are tagged with weakly bound D 2 molecules. The structures of these clusters are determined by analysis of their vibrational patterns obtained by resonant IR photodissociation. The resulting patterns confirm that the metastable N-protomer configuration remains intact even when warmed by sequential condensation of water molecules. Attachment of H 2 O molecules onto the RND 3 + head group also affords the opportunity to explore the possibility of H/D exchange between the acid scaffold and the proximal water network. The spectroscopic results establish that although the RND 3 + ·(H 2 O) n=1,2 clusters are formed without H/D exchange, the n = 3 cluster exhibits about 10% H/D exchange as evidenced by the appearance of the telltale HOD bands. Furthermore, the site of exchange on the acid is determined to be the acidic OH by the emergence of the OH stretching fundamental in the -COOH motif.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Wet chemistry-synthesized Fe/mixed ferrite soft magnetic composites for high-frequency power conversion

State-of-the-art soft magnetic (SM) alloy systems such as electrical steels and permalloys exhibit large eddy current losses at high-frequency (kHz range and above), limiting their application in fast switching devices. Eddy current losses can be reduced for metallic alloys through a decrease in characteristic length scale or embedding them in an insulation layer. This work proposes the development of fine-scale core materials consisting of metallic SM nano/microparticles with magnetic, inorganic insulation layers, and their synthesis using a wet chemistry-based, scalable method for high frequency and high-power applications. More specifically, a magnetic ferrite coating (Ni 0.5-x Mn x Zn 0.5 Fe 2 O 4 , x = 0.0–0.5) was applied via deposition of ferrite powder produced using a “wet chemistry-based” co-precipitation method; the ferrite was distributed through the Fe micropowder via either ball milling or ultrasonic mixing. Powder cores were prepared by compaction of the synthesized composites. Relative magnetic permeability and core loss were measured at excitation frequencies to 200 kHz. A core loss of 127 kW/m 3 was measured at excitation frequency of 100 kHz and magnetization of 0.02 T. This value improves on the 199.3 kW/m 3 reported in literature at identical excitation conditions for a compact formed from a composite comprising Fe microparticles coated with low-permeability Ni 0.5 Zn 0.5 Fe 2 O 4 . Ultrasonic mixing resulted in slightly lower core loss than ball milling, possibly because ball milling causes loss-increasing deformation of the Fe micropowder. XRD and SEM were used to observe composite composition and core cross-section microstructure.

36 MATERIALS SCIENCE↗

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