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At least 271 records · Page 15

Local Distortions and Metal–Semiconductor–Metal Transition in Quasi-One-Dimensional Nanowire Compounds AV 3 Q 3 O δ (A = K, Rb, Cs and Q = Se, Te)

Metal cluster compounds have garnered renewed interest in the search for novel superconductors and topological semimetals owing to structural instabilities of metal-cluster geometries and broken symmetries. Here we synthesized needle-like crystals of the V-cluster-based quasi-one-dimensional (Q1D) materials AV 3 Q 3 O δ (A = K, Rb, Cs, Q= Se, Te) which can also be viewed as being composed of parallel nanowires. We examine how changes in their average and local structure control their electronic properties. All compounds crystallize in the TIFe 3 Te 3 -type structure (P6 3 /m space group) with infinite (V 3 )Q 3 ) - double-walled columnar chains separated by A + cations. Our single-crystal and synchrotron powder diffraction studies indicate oxygen atoms partially occupy the center site of the V 6 octahedral metal cluster cages in KV 3 Te 3 O 0.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 , whereas KV 3 Se 3 is structurally oxygen-free. Our synchrotron X-ray pair distribution function (PDF) analyses indicate that the oxygen-free V 6 cluster octahedra in KV 3 Se 3 are highly distorted perpendicular to the chain direction even at room temperature, reducing the symmetry of the average structure from hexagonal P6 3 /m to monoclinic P2 1 /m. Our theoretical calculation supports this P2 1 /m distortion and suggests the structure further distorts to P2 1 or P2 1 /c at lower temperatures. In contrast, the oxygen-centered V-cluster in KV 3 Te 3 O 0.33 exhibits a V-3-triangle-trimerization along the chain direction. This feature is discernible from the local PDF and is consistent with lattice dynamical calculations based on density functional theory. Resistivity measurements indicate that KV 3 Se 3 exhibits metallic behavior, whereas a dramatic metal-semiconductor-metal transition emerges in KV 3 Te 3 O 6.33 , RbV 3 Te 3 O 0.32 , and CsV 3 Te 3 O 0.35 because of oxygen disorder and changes in local structure captured from our electronic structure analyses of the Fermi surface. Our investigation of the AV 3 Q 3 O 6 family demonstrates the importance of understanding local changes in structure driven by electronic instabilities, which can guide the search for new quantum materials in other low-dimensional cluster-compound materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic Insights into Lithium–Glyme Solvate Ionic Liquids: Effects of Chain Length and Anion Coordination

For this study, mixtures of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in diglyme (G2), triglyme (G3) and tetraglyme (G4) at solvate ionic liquid (SIL) concentrations were investigated using classical molecular dynamics (cMD) simulations with a physically motivated force-field specifically developed for modeling these systems. The structural and dynamical properties of the mixtures were computed and analyzed. Lithium solvation shells, radial distribution functions, and X-ray structure factors were studied across the different SIL systems. Translational diffusion and rotational relaxation times were also evaluated, exhibiting similar trends with increasing glyme chain length. The results are consistent with experimental data and in good agreement with previous computational studies on G3 and G4. These findings validate the accuracy of the force field in modeling glyme systems and its use for describing the [Li(G2) 4/3 ][TFSI] mixture. Additionally, the thermal and electrochemical stability of these electrolytes were systematically examined. The thermal stability appears to be governed by cooperative interactions among glyme molecules, while the electrochemical stability is primarily influenced by Li + -anion interactions, which vary significantly with glyme chain length. Overall, the study sheds light on the crucial role of the anion in these glyme-based SILs and offers valuable insights into Li + -glyme systems at SIL concentrations, highlighting their promise as potential Li-ion battery electrolytes.

anions↗

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. In this work, we report on the use of high-resolution ion mobility spectrometry separations in our structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) platform for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 meter SLIM IMS separation the various drug bound antibody species could be well resolved for both chains. Furthermore, we also show that higher resolution separations were possible with SLIM IMS as compared to ones performed on a commercially available (~1 meter) drift tube IMS-MS platform. Interestingly, additional gas-phase substructures become evident with longer path length SLIM IMS, potentially providing insight related to how drug conjugation may alter the structural properties of a monoclonal antibody and thus affect its overall potency and/or selectivity for a given antigen. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly for structural confirmation to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polyethylene upcycling to fuels: Narrowing the carbon number distribution in n-alkanes by tandem hydropyrolysis/hydrocracking

The extensive use of plastics in modern life has resulted in a global waste crisis to the environment. Polyethylene (PE) is one of the most popular and hardest plastics to recycle because of its strong C(sp 3 )-C(sp 3 ) bonds. In this study, a tandem conversion process, i.e., hydropyrolysis and subsequent vapor-phase hydrocracking of primary intermediates (C n>5 alkenes and long-chain alkanes), was conducted via a two-step pressurized flow-through fixed-bed reactor over a CoAl 2 O 4 spinel-derived catalyst. The product distribution could be flexibly tuned by regulating operating parameters in the cascade fixed-bed reactor and Co/Al molar ratio in CoAl 2 O 4 spinel catalysts. Under optimal reaction conditions (0.2 MPa H 2 , 550 °C for hydropyrolysis in the 1st reactor, 300–325 °C for hydrocracking in the 2nd reactor, 20 s -1 of gas hourly space velocity), the maximum single-pass yields of gasoline (C 5 -C 12 ) and jet-fuel (C 8 -C 16 ) range n-alkanes reached 86.0 wt% and 68.1 wt%, respectively. The CoAl 2 O 4 spinel catalysts also gained high activity in degrading realistic post-consumer plastics such as linear low-, low-, and high-density PE, and a ~ 73.1 wt% gasoline yield and a ~ 54.7 wt% C 8 -C 16 yield were retained even after 3 cycles in-situ regeneration of deactivated CoAl 2 O 4 catalysts. This work provides an efficient and tunable approach to upcycle PE wastes into liquid fuels with an ideal carbon length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States

This study evaluated the economic feasibility of fast pyrolysis biorefineries fed with blended pine residues and switchgrass in the Southeastern U.S. with different supply chain design. Previous techno-economic analyses (TEA) have focused on either blended biomass or decentralized preprocessing without investigating the impacts of varied process parameters, technology options, and real-world biomass distribution. This study fills the literature gap by modeling scenarios for different biomass blending ratios, biorefinery and preprocessing site (so-called depot) capacities, and alternative preprocessing technologies. High-resolution, real-world geospatial data were analyzed using Geographic Information Systems to facilitate supply chain design and TEA. For a decentralized system, the minimum fuel selling price (MFSP) of biofuel was 3.92–4.33 per gallon gasoline equivalent (GGE), while the MFSP for the centralized biorefinery at the same capacities ranged between 3.75–4.02/GGE. Implementing a high moisture pelleting process depot rather than a conventional pelleting process lowered the MFSP by 0.03–0.17/GGE. Scenario analysis indicated decreased MFSP with increasing biorefinery capacities but not necessarily with increasing depot size. Medium-size depots (500 OMDT/day) achieved the lowest MFSP. Here, this analysis identified the optimal blending ratios for two preprocessing technologies at varied depot sizes. Counterintuitively, increasing the proportion of higher cost switchgrass reduced the MFSP for large biorefineries (>5000 ODMT/day), but increased the MFSP for small biorefineries (1000–2500 ODMT/day). Although the decentralized systems have a higher MFSP based on current analysis, it has other potential benefits such as mitigated supply chain risks and improved feedstock quality that are difficult to be quantified in this TEA.

09 BIOMASS FUELS↗

Overcoming mechanical fragility in Sm-Co permanent magnet materials

Samarium-cobalt alloys are used in some of the strongest permanent magnets, particularly for applications between about 200 and 550°C, but the utilization of these materials is restricted by their brittleness. Improving their mechanical resilience would allow them to be used more widely and, in some cases, substitute for neodymium-based magnet alloys which are subject to supply-chain risks. In this work, we have engineered a series of novel microstructures with bi-modal grain size distributions to achieve unprecedented combinations of mechanical and magnetic properties. Improvements up to 73% are obtained in the flexural strength of Sm 2 (CoFeCuZr) 17 sintered magnets, with negligible impact on the magnetic properties. Our mechanically-robust, high-performance Sm-Co magnets are made without changing the chemical compositions of the materials or their heat treatment procedures, making them highly compatible with existing manufacturing processes.

36 MATERIALS SCIENCE↗

A Stochastic Transport Model for the Cumulative Number of Fissions and Deposited Fission Energy

The stochastic theory of neutron transport is extended to describe the cumulative distribution of fission numbers and deposited fission energy in a multiplying assembly. Solutions for the probability distributions are obtained using analytical approximations and Monte Carlo simulation in lumped geometry and in symmetric homogeneous and heterogeneous spheres. The results show the development of a power-law tail in the steady state fission number and deposited energy distributions when the medium is critical, independent of the fission neutron multiplicity distribution and domain heterogeneity. In contrast, the asymptotic decay is faster than exponential in subcritical media due to rapid chain extinction and in supercritical media due to the increasing probability of chain divergence. Here, a formal asymptotic analysis of the problem in lumped geometry with an arbitrary fission neutron multiplicity confirms the existence of power-law tails at critical.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Power Electronics for Electrolyzer Applications to Enable Grid Services

The Power Electronics for Electrolyzer Applications to Enable Grid Services project aims to develop smart converter for dedicated electrolyzer applications to enable grid services via standardization of control interfaces between hydrogen electrolyzer system low-level controls and power converter controls. The project provides additional revenue source for electrolyzer through participation in grid services and reduces the cost of deployment and controls integration through standardization and risk due to supply-chain issues. It also enables the adoption of green hydrogen via standardizing the integration of energy storage, renewables, and distributed energy resources. Furthermore, the work provides a controlled validation environment to evaluate scalable integration solution for hydrogen production technologies, improves overall reliability and maintainability of the electrolyzer system for grid applications, and directly contributes to DOE HFTO's "Hydrogen Shot" goal.

energy transitions↗

One-directional polarization transport in electron/nuclear spin chains with loss and gain

Understanding the joint dynamics of electron and nuclear spins is central to core concepts in solid-state magnetic resonance such as spin-lattice relaxation and dynamic nuclear polarization, but a generalization that capitalizes on competing polarization loss and gain channels is still lacking. Here, we study theoretically the non-Hermitian dynamics of hybrid electron/nuclear spin systems in the simultaneous presence of electron spin pumping and spin-lattice relaxation. Focusing on periodic, one-dimensional chains, we find that, by adjusting the electron spin pumping to a critical level, it is possible to steer the flow of nuclear polarization to create site-dependent distributions where either end of the array polarizes in opposite ways, irrespective of the initial state. By contrast, we show that ring-like patterns—where the limit nuclear polarization is uniform—exhibit a non-decaying, externally driven nuclear spin current. Interestingly, cyclic magnetic field modulation can render these processes largely robust to defects in the chain, a response featuring some interesting similarities—and differences—with recent findings in other non-Hermitian physical platforms.

36 MATERIALS SCIENCE↗

Distributed Optimization in Distribution Systems: Use Cases, Limitations, and Research Needs

We report electric distribution grid operations typically rely on both centralized optimization and local non-optimal control techniques. As an alternative, distribution system operational practices can consider distributed optimization techniques that leverage communications among various neighboring agents to achieve optimal operation. With the rapidly increasing integration of distributed energy resources (DERs), distributed optimization algorithms are growing in importance due to their potential advantages in scalability, flexibility, privacy, and robustness relative to centralized optimization. Implementation of distributed optimization offers multiple challenges and also opportunities. This paper provides a comprehensive review of the recent advancements in distributed optimization for electric distribution systems and classifications using key attributes. Problem formulations and distributed optimization algorithms are provided for example use cases, including volt/var control, market clearing process, loss minimization, and conservation voltage reduction. Finally, this paper also presents future research needs for the applicability of distributed optimization algorithms in the distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Blockchain Enabled Intelligence of Federated Systems (BELIEFS): An attack-tolerant trustable distributed intelligence paradigm

In this article, a Blockchain Enabled Intelligence of Federated Systems (BELIEFS) is proposed to conduct cooperative control for the multi-regional large-scale power system with a multi-agents system (MAS). By establishing a two levels blockchain, each regional AI agent can simultaneously manage intra-regional controllers and cooperate with other AI agents. Under the consensus mechanism, the agents, which respectively conducted distributed deep reinforcement learning (DDRL) algorithm in multi-regions, can have the tolerant capability of malicious attacks in their training process. The demonstration of the proposed approach is within a multi-regional large-scale interconnected power system. Under the mode of "centralized dispatching and hierarchical management", this article aims to definite a mathematical model to deal with the control problem of the power systems. With the comparison experiments, the effectiveness and efficiency of our proposed method in the training process are verified. In addition, malicious attacks are set on the main chain and shard chains to verify the attack-tolerant capability. We expect that such approach and results can suggest a new paradigm of attack-tolerant trustable distributed AI deployment.

97 MATHEMATICS AND COMPUTING↗

Adversarial autoencoder ensemble for fast and probabilistic reconstructions of few-shot photon correlation functions for solid-state quantum emitters

Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Green-Solvent Processed Blade-Coating Organic Solar Cells with an Efficiency Approaching 19% Enabled by Alkyl-Tailored Acceptors

Power-conversion-efficiencies (PCEs) of organic solar cells (OSCs) in laboratory, normally processed by spin-coating technology with toxic halogenated solvents, have reached over 19%. However, there is usually a marked PCE drop when the blade-coating and/or green-solvents toward large-scale printing are used instead, which hampers the practical development of OSCs. Here, a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused end-group. Thanks to the N-alkyl engineering, NIR-absorbing YR-SeNF series show different crystallinity, packing patterns, and miscibility with polymeric donor. The studies exhibit that the molecular packing, crystallinity, and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains, providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YR-SeNF-based OSCs. As a result, a record-high PCE approaching 19% is achieved in the blade-coating OSCs fabricated from a green-solvent o-xylene with high-boiling point. Notably, ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep > 80% of the initial PCEs for even over 400 h. Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs, which paves a way for industrial development.

14 SOLAR ENERGY↗

Modeling Plutonium Decorporation in a Female Nuclear Worker Treated with Ca-DTPA after Inhalation Intake

The present work models plutonium (Pu) biokinetics in a female former nuclear worker. Her bioassay measurements are available at the US Transuranium and Uranium Registries. The worker was internally exposed to a plutonium-americium mixture via acute inhalation at a nuclear weapons facility. She was medically treated with injections of 1 g Ca-DTPA on days 0, 5, and 14 after the intake. Between days 0 and 20, fecal and urine samples were collected and analyzed for 239 Pu and 241 Am. Subsequently, she was followed up for bioassay monitoring over 14 y, with additional post-treatment urine samples collected and analyzed for 239 Pu. The uniqueness of this dataset is due to the availability of: (1) both early and long-term bioassay data from a female with plutonium intake; (2) data on chelation therapy for a female; and (3) fecal measurement results. Chelation therapy with Ca- and/or Zn-salts of DTPA is known to aid in reducing the internal radiation dose by enhancing the excretion of plutonium and americium from the body. Such enhancement affects plutonium biokinetics in the human body, posing a challenge to the internal dose assessment. The current radiation dose assessment practice is to exclude the data affected by Ca-DTPA from the analysis. The present analysis is the first to explicitly model the chelation-affected bioassay data in a female by using a newly developed chelation model. Thus, the bioassay data collected during and after the Ca-DTPA administrations were used for biokinetic modeling and dose assessment. The Markov Chain Monte Carlo method was used to investigate model parameter uncertainty, based on the bioassay data and assumed prior probability distributions. A χ 2 /nData (number of data points) ≈ 1 was observed in this study, which indicates self-consistency of the data with the model. Results of this study show that the worker’s 239 Pu intake was 12 Bq, with a committed effective dose to the whole-body of 1.2 mSv and a committed equivalent dose to the bone surfaces, liver, and lungs of 37.8, 9.1, and 0.8 mSv, respectively. This study also discusses the worker’s dose reduction due to chelation treatment.

61 RADIATION PROTECTION AND DOSIMETRY↗

Bug fixes / enhancements to Parallel tempering Markov chain Monte Carlo sampler (PTMCMCSampler) v3

Markov chain Monte Carlo sampler useful for a variety of problems for optimization, numerical integration, and generating draws from a probability distribution. They are often used in physical and mathematical problems, especially when it is difficult or impossible to use other approaches. This disclosure is for new bug fixes and enhancements to an existing open source library that is already in the public domain under the MIT license. https://github.com/jellis18/PTMCMCSampler

Forrer, Mark↗

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗

Catalytic Upgrading of Ethanol to C8+ Distillate Range Ethers via Guerbet Coupling and Etherification

Guerbet coupling followed by etherification is a two step process for conversion of ethanol into distillate range molecules. This involves first alcohol oligomerization, followed by acid-catalyzed dehydration. As we will show in this presentation, ethanol can be converted to higher linear and α-branched alcohols by C-C coupling reactions (ethanol oligomerization) as well as to high molecular weight esters by C-O coupling reactions with Cu/MgxAlOy (CuHT) catalysts. Alcohols may be converted to ethers via bimolecular dehydration in a subsequent step. We have identified more than 160 number of species in the products including alcohols, esters, aldehydes, ketonces, and olefins. Alcohols range from C4 to C10. Both alcohols and esters follow a Schulz-Flory chain growth model. We show the relationship between the catalyst properties (BET surface area, acid and base site count and Cu loading and synthesis method) and the performance in the reactions. We also show that physical mixtures of CuHT and HT can have similar product selectivity of low loading CuHT catalysts. The selectivity towards diesel fuel precursor compounds (hereafter ‘DFPC’) increased with conversion until reaching a plateau at high ethanol conversion (~70%). Alcohol selectivity follows a Schultz-Flory distribution at all studied conversions, and that adsorbed ethanol-derived species may undergo surface oligomerization into 1-butanol and higher alcohols before desorbing in a chain-growth mechanism. Zeolite catalysts convert the C4+ alcohols into C8+ ethers in both batch and continuous flow reactors. Selectivities of up to 80% to C8+ ethers at around 70% conversion using a single pass continuous flow system are able to be achieved. The final product feedstocks obtained from etherification have been used in technoeconomic (TEA) and lifecycle analysis (LCA), which indicate a reduction in greenhouse gas (GHG) emissions of 50% relative to conventional diesel. These final feedstocks are undergoing engine testing to elucidate the physiochemical properties and will be compared to diesel #2 ASTM standards as a reference and will serve as a basis to improve the final bio-diesel blendstocks from etherification.

Huber, George↗

Catalytic upgrading of ethanol to C8+ distillate range ethers via Guerbet coupling and etherification

In this presentation we describe the catalytic approaches for conversion of ethanol into diesel fuel ethers. This involves first alcohol oligomerization, followed by acid-catalyzed dehydration. As we will show in this presentation, ethanol can be converted to higher linear and α-branched alcohols by C-C coupling reactions (ethanol oligomerization) as well as to high molecular weight esters by C-O coupling reactions with Cu/MgxAlOy (CuHT) catalysts. Alcohols may be converted to ethers via bimolecular dehydration in a subsequent step. We have identified more than 160 number of species in the products including alcohols, esters, aldehydes, ketones, and olefins. Alcohols range from C4 to C10. Both alcohols and esters follow a Schulz-Flory chain growth model. We show the relationship between the catalyst properties (BET surface area, acid and base site count and Cu loading and synthesis method) and the performance in the reactions. We also show that physical mixtures of CuHT and HT can have similar product selectivity of low loading CuHT catalysts. The selectivity towards diesel fuel precursor compounds (hereafter ‘DFPC’) increased with conversion until reaching a plateau at high ethanol conversion (~70%). Alcohol selectivity follows a Schultz-Flory distribution at all studied conversions, and that adsorbed ethanol-derived species may undergo surface oligomerization into 1-butanol and higher alcohols before desorbing in a chain-growth mechanism. Zeolite catalysts convert the C4+ alcohols into C8+ ethers in both batch and continuous flow reactors. Selectivities of up to 80% to C8+ ethers at around 70% conversion using a single pass continuous flow system are achieved. The final product feedstocks obtained from etherification have been used in technoeconomic (TEA) and lifecycle analysis (LCA), which indicate a reduction in greenhouse gas (GHG) emissions of 50% relative to conventional diesel and diesel fuel prices that are lower than biodiesel. These final feedstocks are undergoing engine testing to elucidate the physiochemical properties and compare well to diesel #2 ASTM standards.

Huber, George↗