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At least 433 records · Page 24

Amphiphile Organization in Organic Solutions: An Alternative Explanation for Small-Angle X-ray Scattering Features in Malonamide/Alkane Mixtures

In this work, the role of different intermolecular interactions in the aggregation of amphiphiles in an organic solvent is studied for systems of relevance to liquid-liquid extraction (LLE), a chemical process used to selectively recover metals from complex mixtures. Of specific interest is the role, or lack thereof, of hydrogen bonding, which is often assumed to be a main driver of the organic phase structural organization that has been linked to separation efficacy. Toward that end, a series of malonamide extractants in n-dodecane have been studied in the absence of any extracted aqueous solutes, including water. The series of extractants includes N,N'-dimethyl-N,N'-dibutyltetradecylmalonamide (DMDBTDMA), two of its homologs, and N,N'-dimethyl-N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). This simplified model LLE system enables systematic investigation of the role of dipole-dipole and alkyl tail steric interactions in amphiphile aggregation. Small-angle X-ray scattering (SAXS) profiles computed from molecular dynamics trajectories are in good agreement with experimental SAXS data. Molecular dynamics simulations show that malonamide aggregation results from dipole-driven self-association and lacks characteristic aggregate sizes. Mid-q correlation peaks in the SAXS profiles emerge at high concentration for each malonamide. In those densely packed solutions, the correlation peaks are observed to result from alkyl tail-induced spacing between electron-rich polar head groups, with peak positions determined by the different alkyl tail lengths present in the malonamide molecule. This explanation of the SAXS correlation peaks contrasts with the prevailing literature, which attributes mesoscale features observed in small-angle scattering to the formation of microemulsions. Instead, this work finds that these features are present in the absence of water or any reverse micellar organization of the malonamides. As such, molecular-scale malonamide self-association and packing, rather than microemulsion-based colloidal-scale descriptions, is a more appropriate framework for these LLE systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

EF-Hand Battle Royale: Hetero-ion Complexation in Lanmodulin

The lanmodulin (LanM) protein has emerged as an effective means for rare earth element (REE) extraction and separation from complex feedstocks without the use of organic solvents. Whereas the binding of LanM to individual REEs has been well characterized, little is known about the thermodynamics of mixed metal binding complexes (i.e., heterogeneous ion complexes), which limits the ability to accurately predict separation performance for a given metal ion mixture. In this paper, we employ the law of mass action to establish a theory of perfect cooperativity for LanM-REE complexation at the two highest-affinity binding sites. The theory is then used to derive an equation that explains the nonintuitive REE binding behavior of LanM, where separation factors for binary pairs of ions vary widely based on the ratio of ions in the aqueous phase, a phenomenon that is distinct from single-ion-binding chemical chelators. We then experimentally validate this theory and perform the first quantitative characterization of LanM complexation with heterogeneous ion pairs using resin-immobilized LanM. Importantly, the resulting homogeneous and heterogeneous constants enable accurate prediction of the equilibrium state of LanM in the presence of mixtures of up to 10 REEs, confirming that the perfect cooperativity model is an accurate mechanistic description of REE complexation by LanM. We further employ the model to simulate separation performance over a range of homogeneous and heterogeneous binding constants, revealing important insights into how mixed binding differentially impacts REE separations based on the relative positioning of the ion pairs within the lanthanide series. In addition to informing REE separation process optimization, these results provide mathematical and experimental insight into competition dynamics in other ubiquitous and medically relevant, cooperative binding proteins, such as calmodulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Innovation and Winemaking By-Product Valorization: An Ohmic Heating Approach

The by-products of the winemaking process can represent chances for the development of new products. This study focused on the “zero waste” strategy development for by-products generated within winemaking from white and red grape varieties cultivated in the north of Portugal. The phytochemical properties of by-products were identified and characterized. Ohmic heating (OH) as a green extraction method was also applied to grape pomace due to their unknown effects on centesimal and phytochemical compositions. Both protein and carbohydrates were shown to be higher in grape bagasse than in stems. Additionally, red bagasse is richer in bioactive compounds (BC) than white bagasse. The sugar content was 21.91 and 11.01 g/100 g of DW in red and white grape bagasse, respectively. The amount of protein was 12.46 g/100 g of DW for red grape bagasse and 13.18 g/100 g of DW for white. Regarding the extraction methods, two fractions were obtained, a liquid fraction and solid (the remainder after the methodology application). OH presented a higher antioxidant capacity than a conventional (CONV) method. In addition, both extracts presented similar contents of anthocyanins, e.g., delphinidin-3-O-glucoside, petunidin-3-O-glucoside, and peonidin-3-O-glucoside. The solid fraction presented higher amounts of protein and phenols bound to fiber than CONV, which allows its use as a functional ingredient. In conclusion, OH can be an alternative extraction method compared with CONV methods, avoiding non-food grade solvents, thus contributing to circular economy implementation.

Coelho, Marta C. (ORCID:000000026542175X)↗

Radiological Degradation of Tetraoctyl Diglycolamide in n-Alkyl Solvents: Influence of Solvent Ionization Potential

Reprocessing of used nuclear fuel reduces the requirements for long-term storage repositories. Cost-efficient processes depend on knowledge of radiation effects, but gaps occur in understanding how radiation results in the degradation of fuel separation molecules. This project investigates the influence of different n-alkyl solvents on the radiolytic fragmentation behavior of N,N,N',N'-Tetraoctyl-3-oxapentane-1,5-diamide (TODGA), a promising ligand for extraction of the lanthanides and minor actinides from dissolved nuclear fuel. Findings from this work suggest a linkage between the ionization potential of the solvent and the degradation products observed in the resulting mass spectrum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Nanostructure Scaling in Semi-Dilute Triblock Copolymer Gels

Here, there is a considerable body of work that describes the scaling of diblock copolymer micelle dimensions in dilute and semi-dilute solution based upon block degrees of polymerization and copolymer concentration. However, there is a lack of analogous information for semi-dilute ABA triblock copolymer gels, which consist of ABA triblock copolymer dissolved in midblock-selective (B-selective) solvent. The present study uses small angle X-ray scattering to extract micelle dimensions for numerous triblock copolymer gels that vary in copolymer identity (and hence block lengths) and copolymer concentration, as well as gels that contain various ratios of two unique triblock copolymers. Analysis of micelle structural data subsequently translates to universal scaling expressions for the micelle core radius – r A ≈ N A 0.53 N B -0.14 $\phi$ ABA 0.16 where N A and N B are the endblock and midblock degrees of polymerization, respectively, and $\phi$ ABA is the volume fraction of triblock copolymer in the gel – and for the intermicelle spacing – l AA ≈ N A 0.09 N B 0.29 $\phi$ ABA -0.35 . Each scaling expression describes the full collection of experimental data very well. Additionally, these scaling expressions are partially in line with expectations from semi-dilute diblock copolymer solution theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Green pretreatment strategies for enhanced microbial lipid fermentation and synergistic high-quality lignin recovery for next-generation integrated biorefineries

Miscanthus × giganteus (Mxg) is a warm-season perennial grass being commercialized as a biomass feedstock for temperate farms. Three process strategies were compared for converting Mxg into single-cell oil and extracted lignin intermediates, as hydrothermal (HT) processing and two natural deep eutectic solvents (NADES), ChCl:LA (choline chloride:lactic acid) and ChCl:Gly (choline chloride:glycerol). Pretreatments were performed at 10% and 50% solids loading at 140 °C, 2 h; HT: 190 °C, 10 min. Enzymatic hydrolysates, generated at 10% solids using washed and unwashed biomass, were evaluated for microbial lipid production. Maximum glucose conversions from washed biomass reached 83.5% (ChCl:LA), 52.7% (ChCl:Gly), and 74.0% (HT). Remarkably, NADES-derived hydrolysates effectively replaced refined sugars for the cultivation of the oleaginous yeast Rhodotorula toruloides, achieving ∼51% higher biomass (OD 90.7) and lipid titers of 19.36 g/L within 45 h using a two-stage fermentation strategy. Lipid contents ranged from 34.5–44.5% dry weight, demonstrating reduced reliance on purified sugars. Beyond carbohydrate valorization, ChCl:LA pretreatment enabled high-purity lignin recovery (>89%) in a lignin-first strategy. Structural analyses (2D-HSQC and ³¹P NMR) showed syringyl (78.15%), guaiacyl (15.15%), and p-hydroxyphenyl (6.41%) units, with higher phenolic hydroxyl content (0.91 mmol/g) and a lower S/G ratio (0.19) than HT lignin (0.87 mmol/g, S/G 0.22). These attributes favor downstream lignin depolymerization into low-molecular-weight aromatics. Overall, NADES pretreatment simultaneously enhances microbial lipid yields and recovers high-quality lignin, advancing the economic feasibility of renewable diesel and sustainable aviation fuel (SAF) production from bioenergy crops within an integrated biorefinery framework.

2D HSQC↗

Nondestructive flash cathode recycling

Effective recycling of end-of-life Li-ion batteries (LIBs) is essential due to continuous accumulation of battery waste and gradual depletion of battery metal resources. The present closed-loop solutions include destructive conversion to metal compounds, by destroying the entire three-dimensional morphology of the cathode through continuous thermal treatment or harsh wet extraction methods, and direct regeneration by lithium replenishment. Here, we report a solvent- and water-free flash Joule heating (FJH) method combined with magnetic separation to restore fresh cathodes from waste cathodes, followed by solid-state relithiation. The entire process is called flash recycling. This FJH method exhibits the merits of milliseconds of duration and high battery metal recovery yields of ~98%. After FJH, the cathodes reveal intact core structures with hierarchical features, implying the feasibility of their reconstituting into new cathodes. Relithiated cathodes are further used in LIBs, and show good electrochemical performance, comparable to new commercial counterparts. Life-cycle-analysis highlights that flash recycling has higher environmental and economic benefits over traditional destructive recycling processes.

25 ENERGY STORAGE↗

A naphthalene diimide side-chain polymer as an electron-extraction layer for stable perovskite solar cells

Poly(N-(5-(5-norbornene-2-carbonyl)oxy)pentyl)-N'-n-hexyl-naphthalene-1,8:4,5-bis(dicarboximide) has been synthesized by esterification of (N-(5-hydroxypentyl)-N'-n-hexyl-naphthalene-1,8:4,5-bis(dicarboximide)) with exo-5-norbornene-2-carboxylic acid, and has been polymerized using the first-generation Grubbs initiator. This side-chain polymer exhibits good transparency throughout the visible (absorption onset at ca. 400 nm), good solubility in common low- and medium-polarity organic solvents, good resistance to dimethylformamide, and appropriate electron affinity for use as an electron-extraction layer in lead-halide perovskite solar cells. The performance of this polymer in n-i-p perovskite solar cells was compared to that of several small-molecule naphthalene-1,8:4,5-bis(dicarboximide) derivatives and of SnO 2 . Solar cells using the polymer exhibited open-circuit voltages of up to 1.02 V, short-circuit currents of over 21 mA cm –2 , and power conversion efficiencies (PCE) reaching 14% which stabilize at 13.8% upon 90 s of illumination. Meanwhile control SnO 2 devices exhibited a PCE of ca. 16%, and small-molecule devices gave PCE values of less than 10%. Here, the devices employing the polymer exhibited improved long-term stability relative to the SnO 2 control devices under continuous illumination.

36 MATERIALS SCIENCE↗

Modeling the partitioning of amphiphilic molecules and co-solvents in biomembranes

We report amphiphilic co-solvents can have a significant impact on the structure, organization and physical properties of lipid bilayers. Describing the mutual impact of partitioning and induced structure changes is therefore a crucial consideration for a range of topics such as anesthesia and other pharmacokinetic effects, as well as microbial solvent tolerance in the production of biofuels and other fermentation products, where molecules such as ethanol, butanol or acetic acid might be generated. Small-angle neutron scattering (SANS) is a key method for studying lipid and polymer bilayer structures, with many models for extracting bilayer structure (thickness, area per lipid etc.) from scattering data in use today. However, the molecular details of co-solvent partitioning are conflated with induced changes to bilayer structure, making interpretation and modeling of the scattering curves a challenge with the existing set of models. To address this, a model of a bilayer structure is presented which invokes a two-term partition constant accounting for the localization of the co-solvent within the bilayer. This model was validated using a series of SANS measurements of lipid vesicles in the presence of the co-solvent tetrahydrofuran (THF), showing several strategies of how to deploy the two-parameter partition constant model to describe scattering data and extract both structure and partitioning information from the data. Molecular dynamics simulations are then used to evaluate assumptions of the model, provide additional molecular scale details and illustrate its complementary nature to the data fitting procedure. This approach results in estimates of the partition coefficient for THF in 1,2-dimyristoyl-sn-glycero-3-phosphocholine at 35°C, along with an estimate of the fraction of THF residing in the hydrophobic core of the membrane. The authors envision that this model will be applicable to a wide range of other bilayer/amphiphile interactions and provide the associated code needed to implement this model as a fitting algorithm for scattering data in the SasView suite.

59 BASIC BIOLOGICAL SCIENCES↗

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.

Chemistry↗

Solvent Selection for the Separation of Lignin-Derived Monomers Using the Conductor-like Screening Model for Real Solvents

The separation of desired monomers from a liquid-phase mixture of lignin depolymerization products is necessary to facilitate their upscaling and upgrading for industrial applications. One effective method to separate multiple liquid-phase products is countercurrent chromatography (CCC), which is a common liquid chromatography technique that separates target solutes based on differences in their partitioning in a biphasic solvent system. Effective CCC separation requires the selection of solvent compositions to tune solute partition coefficients. Here, to alleviate the experimental burden of selecting optimal solvent systems, we apply the conductor-like screening model for real solvents (COSMO-RS) method to compute partition coefficients of representative lignin monomers from four currently used depolymerization strategies in standard solvent systems. We further design new ternary and quaternary solvent systems that are predicted to further improve separation efficacy. On the basis of these predicted partition coefficients and empirical solvent selection criteria for CCC measurements, we suggest a range of solvent systems that would be suitable for the effective separation of aromatic lignin-derived products via CCC or similar liquid–liquid extraction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Top-Down Strategy to Engineer ActiveLayer Morphology for Highly Efficient and Stable All-Polymer Solar Cells

A major challenge hindering the further development of all-polymer solar cells (all-PSCs) employing polymerized small-molecule acceptors is the relatively low fill factor (FF) due to the difficulty in controlling the active-layer morphology. The issues typically arise from oversized phase separation resulting from the thermodynamically unfavorable mixing between two macromolecular species, and disordered molecular orientation/packing of highly anisotropic polymer chains. Herein, a facile top-down controlling strategy to engineer the morphology of all-polymer blends is developed by leveraging the layer-by-layer (LBL) deposition. Optimal intermixing of polymer components can be achieved in the two-step process by tuning the bottom-layer polymer swelling during top-layer deposition. Consequently, both the molecular orientation/packing of the bottom layer and the molecular ordering of the top layer can be optimized with a suitable top-layer processing solvent. A favorable morphology with gradient vertical composition distribution for efficient charge transport and extraction is therefore realized, affording a high all-PSC efficiency of 17.0% with a FF of 76.1%. The derived devices also possess excellent long-term thermal stability and can retain >90% of their initial efficiencies after being annealed at 65 °C for 1300 h. In conclusion, these results validate the distinct advantages of employing an LBL processing protocol to fabricate high-performance all-PSCs.

14 SOLAR ENERGY↗

PNNL-Predictive-Phenomics/ProCaliper

ProCaliper is a Python library that curates, organizes, and computes protein structure features in a way that easily interfaces with user-provided experimental data. It extracts or computes protein binding site, active site, charge, pLDDT (order/disorder), acid dissociation, protonation, solvent accessible surface area, disulfide bond distance, and protein secondary structure data using precomputed protein structures and publicly available databases. It provides a unified API for integrating additional residue-level data and for visualizing residue features in 3D.

Rozum, Jordan [Pacific Northwest National Lab]↗

Using Separation-Enhanced Isotope Ratio Mass Spectrometry to Enable Increased Renewable Carbon Content in Transportation Fuels (CRADA 525)

Stable isotope ratio measurements of carbon atoms using isotope ratio mass spectrometry (IRMS) can be an effective tool for quantifying biogenic carbon in co-processed fuels, with results approaching the precision and accuracy of accelerator mass spectrometry (AMS). The lower cost of an IRMS may enable deployment to refineries, improving access and analysis turnaround times (≤2 hours), and, by extension, provide data that can allow process optimization to maximize renewable carbon in desired refinery products. This project explored the integration of chemical separation with IRMS analyses to enable highly detailed tracking of biogenic carbon into fuel product streams separated by boiling point range, chemical class, or specific compound. Forty-nine fuels and fuel components of fossil and biogenic origin, spanning gasoline and diesel boiling point ranges, were received from three refiners and were analyzed for their δ 13 C values via IRMS. Results spanned a 13 C range from ca. 10‰ to 44‰ and reflect materials derived from sustainable sources (e.g., C4 or C3 plants, animal-based pathways, syngas) or from fossil-derived fuels. Common ranges are approximately 18‰ to 9‰ and approximately 30‰ to 20‰ for C4 and C3 plants, respectively, and approximately 34‰ to 24‰ and approximately 70‰ to 33‰ for petroleum-derived fuels and methane, respectively. Fuel-like standards were developed and tested using direct-injection elemental analyzer (EA) IRMS for liquid fuels. This method was compared with the published methods, yielding statistically similar results. Four blend curve sets were produced ranging from 0% to 100% of a fuel containing biogenic carbon, focusing on 0% to 10% biogenic carbon. Linear fits were the most applicable for two of the four blend curve sets; however, two sets were found to exhibit slightly quadratic behavior, which was more pronounced in low biogenic blend samples, necessitating second-order fits. The origin of the slight quadratic behavior remains unclear; however, the discussion points to possible interpretations. CanmetENERGY thoroughly characterized a majority of the samples using one- and two-dimensional gas chromatography (GC and GC×GC, respectively) and other analyses. Selected samples were subjected to solid phase extraction (SPE) for saturate, olefin, aromatic, and polar (SOAP) analysis, and the resulting solvent-diluted fractions containing saturates and aromatics were returned to Pacific Northwest National Laboratory (PNNL), where the solvent was removed via evaporation or physical separation using GC techniques. Characterization and separations provided an understanding of saturate and aromatic content, as well as boiling point ranges for each sample and sample fraction. Samples resulting from SPE were examined using EA-IRMS and gas chromatography combustion IRMS (GC-C-IRMS) analyses. Both approaches suggest that the range in values between end-members can be increased by selecting the paraffinic or aromatic fraction of the end-member or by selecting among individual compounds resulting from GC separation of the paraffinic fractions. Considerable work remains to put these approaches into practice and statistically validate the benefit for using a fraction or individual compound over bulk analysis of a sample. However, initial results suggest that separations provide advantages for samples having blend ratios of less than 10% biogenic blendstocks. 13 C results showed statistically similar biofuel blend results to those obtained at PNNL, although additional work is needed to obtain better reproducibility. Select samples were sent to Los Alamos National Laboratory (LANL) for IRMS measurements and Beta Analytics for AMS measurements. This work suggests that IRMS and AMS yield closely comparable results and in some circumstances, IRMS could serve as a surrogate for AMS. While additional work is needed to better resolve statistical advantages for separations and better show the comparable nature of IRMS and AMS in both the biogenic carbon analysis of bulk chemical classes, initial results from this study suggest that these should be pursued in order to proliferate this approach for quantifying biogenic carbon in transportation fuels to the refinery level, thereby potentially enabling process optimization in co-processing scenarios.

09 BIOMASS FUELS↗

Actinide Separation Inspired by Self-Assembled Metal–Polyphenolic Nanocages

The separation of actinides has a vital place in nuclear fuel reprocessing, recovery of radionuclides, and remediation of environmental contamination. Here we propose a new paradigm of nanocluster-based actinide separation, namely, nanoextraction, that can achieve efficient sequestration of uranium in an unprecedented form of giant coordination nanocages using a cone-shaped macrocyclic pyrogallol[4]arene as the extractant. The U 24 -based hexameric pyrogallol[4]arene nanocages with distinctive [U 2 (PG) 2 ] binuclear units (PG = pyrogallol) that rapidly assembled in situ in monophasic solvent were identified by single-crystal X-ray diffraction, MALDI-TOF mass spectrometry, NMR spectroscopy, and small-angle X-ray and neutron scattering. Furthermore, comprehensive biphasic extraction studies showed that this novel separation strategy has enticing advantages such as fast kinetics, high efficiency, and good selectivity over lanthanides, thereby demonstrating its potential for efficient separation of actinide ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks

Abstract We report a workflow and the output of a natural language processing (NLP)-based procedure to mine the extant metal–organic framework (MOF) literature describing structurally characterized MOFs and their solvent removal and thermal stabilities. We obtain over 2,000 solvent removal stability measures from text mining and 3,000 thermal decomposition temperatures from thermogravimetric analysis data. We assess the validity of our NLP methods and the accuracy of our extracted data by comparing to a hand-labeled subset. Machine learning (ML, i.e. artificial neural network) models trained on this data using graph- and pore-geometry-based representations enable prediction of stability on new MOFs with quantified uncertainty. Our web interface, MOFSimplify, provides users access to our curated data and enables them to harness that data for predictions on new MOFs. MOFSimplify also encourages community feedback on existing data and on ML model predictions for community-based active learning for improved MOF stability models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗