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DOE OSTI2021

Efficient Removal of Per- and Polyfluoroalkyl Substances from Water with Zirconium-Based Metal–Organic Frameworks

Per- and polyfluoroalkyl substances (PFASs) are an emerging class of contaminants raising increased levels of concern due to their toxic, bioaccumulative, and persistent nature. Current solutions for removing PFAS from contaminated water rely on adsorption-based methods where commonly used sorbents, for example, activated carbons and ion-exchange resins, exhibit low adsorption capacity and a long equilibration time. Motivated by the generally deficient performance of these current materials, this work addresses the need for the discovery of advanced sorbents for high capacity and efficient PFAS removal. The zirconium-based metal–organic framework (MOF) NU-1000 was characterized for the adsorption of three perfluorosulfonic acids (PFSAs, C4–C8) and six perfluorinated carboxylic acids (PFCAs, C1–C9) from aqueous solutions. Here, the results indicate that NU-1000 exhibits outstanding adsorption capacities of 400–620 mg/g for PFSAs and 201–604 mg/g for PFCAs coupled with ultrafast adsorption kinetics featuring equilibrium times of <1 min. Complementary density functional theory calculations reveal that the PFAS@MOF adsorption mechanism is dominated by a combination of hydrogen bonding, electrostatic, and hydrophobic non-covalent PFAS–MOF interactions. Excellent regeneration and reusability characteristics were found, particularly nearly quantitative removal and recovery rates of NU-1000 after five consecutive adsoption and desorption cycles of PFAS. Additional adsorption testing using PFAS-contaminated groundwater samples obtained from U.S. Air Force bases revealed impressive PFAS removal rates of 75–98% within 10 min regardless of the presence of co-contaminants. To the best of our knowledge, the suite of herein presented PFAS sorption characteristics—capacity, kinetics, regeneration, and reusability—significantly outperforms other current sorbents, rendering NU-1000 as a promising platform for the rapid and effective removal of PFAS from aqueous media.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Insights into Cation Ordering of Double Perovskite Oxides from Machine Learning and Causal Relations

This work investigates origins of cation ordering in double perovskites using first-principles theory computations combined with machine learning (ML) and causal relations. We have considered various oxidation states of A, A', B, and B' from the family of transition metal ions to construct a diverse compositional space. A conventional framework employing traditional ML classification algorithms such as Random Forest (RF) coupled with appropriate features including geometry-driven and key structural modes leads to accurate prediction (~98%) of A-site cation ordering. We have evaluated the accuracy of ML models by employing analyses of decision paths, assignments of probabilistic confidence bound, and finally a direct non-Gaussian acyclic structural equation model to investigate causality. Our study suggests that structural modes are crucial for classifying layered, columnar, and rock-salt ordering. The charge difference between A and A' is the most important feature for predicting clear layered ordering, which in turn depends on the B and B' charge separation. We have also designed mathematical relationships with these features to derive energy differences to form clear layered ordering. Here, the trilinear coupling between tilt, in-phase rotation, and A-site antiferroelectric displacement in the Landau free-energy expansion becomes the necessary condition behind formation of A-site cation ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structural Phase Transitions in the van der Waals Ferromagnets Fe x Pd y Te 2

Two-dimensional van der Waals (vdW) magnets are attracting significant attention, both as platforms for studying fundamental magnetic interactions and for the exciting possibility of utilizing them as building blocks in devices and heterostructures, which may lead to new physical phenomena and functionalities. Here, we provide a detailed study of the crystal structure and physical properties of the recently discovered vdW ferromagnet FePd 2 Te 2 . We find this compound has a relatively wide width of formation, and grow single crystals with compositions Fe x Pd y Te 2 where x ranges from 0.9 to 1.1 and y from 1.8 to 2.5, respectively. Temperature-dependent X-ray diffraction and transport measurements reveal that a first-order structural transition occurs in the range of T = 360–420 K, where the critical temperature, modulation wave vector, and corresponding room-temperature crystal structures all depend on chemical composition. Above the transition, the compounds with Pd fraction y > 2 adopt a disordered derivative of the tetragonal FeTe structure, with the Fe layer showing mixed Fe/Pd occupancy and the extra Pd atoms partially occupying interstitial sites. Below 370 K, the structure is incommensurately modulated, likely associated with the complex ordering of Pd/Fe atoms in the metal layers or the interstitial Pd in the vdW gaps. For y < 2, the composition Fe 1.1 Pd 1.8 Te 2 has monoclinic symmetry at room temperature that is consistent with the reported structure of FePd 2 Te 2 . This phase undergoes a structural transition at 420 K for which the high temperature structure is yet to be determined; however, based on the similarities with the y > 2 compounds, we speculate that its T > 420 K structure is also tetragonal. Importantly, the high temperature, symmetry-breaking structural transition observed here provides a likely explanation for the origin of the structural domains previously observed in FePd 2 Te 2 . All compounds investigated in the Fe x Pd y Te 2 series show metallic behavior, with magnetic characterization indicating that they are easy-plane, hard, ferromagnets with T C spanning 98–180 K. Both the critical temperature for the structural transition and the Curie temperature are moderately suppressed with increasing Pd fraction y and corresponding decreasing Fe fraction x, indicating that synthetic control over x and y paves way for the further exploration of these compounds.

crystal structure↗

DOE OSTI2023

Several Small or Single Large? Quantifying the Catchment-Wide Performance of On-Site Wastewater Treatment Plants with Inaccurate Sensors

On-site wastewater treatment plants (OSTs) often lack monitoring, resulting in unreliable treatment performance. They thus appear to be a stopgap solution despite their potential contribution to circular water management. Low-maintenance but inaccurate soft sensors are emerging that address this concern. However, how their inaccuracy impacts the catchment-wide treatment performance of a system of many OSTs has not been quantified. Here, we develop a stochastic model to estimate catchment-wide OST performances with a Monte Carlo simulation. In our study, soft sensors with a 70% accuracy improved the treatment performance from 66% of the time functional to 98%. Soft sensors optimized for specificity, indicating the true negative rate, improve the system performance, while sensors optimized for sensitivity, indicating the true positive rate, quantify the treatment performance more accurately. This new insight leads us to suggest programming two soft sensors in practical settings with the same hardware sensor data as input: one soft sensor geared to high specificity for maintenance scheduling and one geared to high sensitivity for performance quantification. Our findings suggest that a maintenance strategy combining inaccurate sensors with appropriate alarm management can vastly improve the mean catchment-wide treatment performance of a system of OSTs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Revealing Hidden Quinones Through Diagnostic MS² Fragmentation of Peptide–Quinone Adducts

Quinones are redox-active components of natural organic matter that mediate electron transfer and influence biogeochemical processes, but many quinones in pyrogenic organic matter (PyOM) remain unresolved because they ionize poorly by mass spectrometry. Here, we present a peptide-tagging approach to improve detection of cysteine-reactive electrophiles in PyOM, with quinones expected to be a dominant subset based on reaction chemistry and selectivity experiments. A cysteine-containing peptide was used to form Michael-addition adducts, enhancing electrospray ionization and enabling untargeted screening by high-performance liquid chromatography-high-resolution tandem mass spectrometry. The method was benchmarked with five quinone standards and applied to extracts from charred plant material as a discovery-level screen for cysteine-reactive targets. We identified 98 quinone-candidate adducts (mean neutral mass ~603 Da), of which more than 70% were not detectable in native MS1 data. Among formula-assigned features, hidden quinone candidates had median (O+N)/C of 0.391 and normalized oxidation state of carbon of -0.281, consistent with relatively low polarity and low oxidation state. These results reveal a previously inaccessible pool of hidden redox-active compounds in PyOM and provide a framework for prioritizing quinone-like electrophiles for confirmation and incorporation into models of fire-driven biogeochemical cycling.

LC-MS/MS↗

DOE OSTI2026

Designing a Robust MEA-Based Post-Combustion Carbon Capture Process with Capture Rate Guarantees

This work presents an application of the nonlinear two-stage robust optimization solver PyROS to the model-based design and operation of a monoethanolamine scrubbing process for CO2 capture under epistemic uncertainty. Through this application, risk-averse process designs are successfully obtained for CO2 capture targets ranging from 90% to over 99%. In particular, the risk-averse solutions for CO2 capture targets of up to 98% are shown to be only marginally more expensive than their nominally optimal counterparts. Thus, the results demonstrate the utility of recently developed nonlinear robust optimization approaches for the solution of large-scale chemical process models under uncertainty.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Harnessing Intermolecular Interactions to Promote Long-Lived Photoinduced Charge Separation from Copper Phenanthroline Chromophores

In this study, facilitating photoinduced electron transfer (PET) while minimizing rapid charge-recombination processes to produce a long-lived charge-separated (CS) state represents a primary challenge associated with achieving efficient solar fuel production. Natural photosynthetic systems employ intermolecular interactions to arrange the electron-transfer relay in reaction centers and promote a directional flow of electrons. This work explores a similar tactic through the synthesis and ground- and excited-state characterization of two Cu(I)bis(phenanthroline) chromophores with homoleptic and heteroleptic coordination geometries and which are functionalized with negatively charged sulfonate groups. The addition of sulfonate groups enables solubility in pure water, and it also induces assembly with the dicationic electron acceptor methyl viologen (MV 2+ ) via bimolecular, dynamic electrostatic interactions. The effect of the sulfonate groups on the ground- and excited-state properties was evaluated by comparison with the unsulfonated analogues in 1:1 acetonitrile/water. The excited-state lifetimes for all sulfonated complexes are similar to what we expect from previous literature, with the exception of the sulfonated heteroleptic complex whose metal-to-ligand charge-transfer (MLCT) lifetime in water has two components that are fit to 10 and 77 ns. For the sulfonated complexes, we detected reduced MV +$\bullet$ in both solvent environments following MLCT excitation, but control measurements in 1:1 acetonitrile/water with the unsulfonated analogues showed no PET to MV 2+ , indicating that electrostatically driven supramolecular assemblies of the sulfonated complexes with MV 2+ facilitate the observed PET. Additionally, the strength of the intermolecular interactions driving the formation of these assemblies changes drastically with the solvent environment. In 1:1 acetonitrile/water, PET occurred from both sulfonated complexes with quantum yields (Φ ET ) of 2-3% but increased to a remarkable 98% for the sulfonated heteroleptic complex with a 3 μs CS-state lifetime in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. In this work, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (~98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ~1.5 million atoms is discussed in the context of MuMMI.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Accurate Machine Learning for Predicting the Viscosities of Deep Eutectic Solvents

Deep eutectic solvents (DESs) are emerging as environmentally friendly designer solvents for mass transport and heat transfer processes in industrial applications; however, the lack of accurate tools to predict and thus control their viscosities under both a range of environmental factors and formulations hinders their general application. While DESs may serve as designer solvents, with nearly unlimited combinations, this unfortunately makes it experimentally infeasible to comprehensively measure the viscosities of all DESs of potential industrial interest. To assist in the design of DESs, we have developed several new machine learning (ML) models that accurately and rapidly predict the viscosities of a diverse group of DESs at different temperatures and molar ratios using, to date, one of the most comprehensive data sets containing the properties of over 670 DESs over a wide range of temperatures (278.15–385.25 K). Three ML models, including support vector regression (SVR), feed forward neural networks (FFNNs), and categorical boosting (CatBoost), were developed to predict DES viscosity as a function of temperature and molar ratio and contrasted with multilinear and two-factor polynomial regression baselines. Further, quantum chemistry-based, COSMO-RS-derived sigma profile (σ-profile) features were used as inputs for the ML models. The CatBoost model is excellent at externally predicting DES viscosity, as indicated by high R 2 (0.99) and low root-mean-square-error (RMSE) and average absolute relative deviations (AARD) (5.22%) values for the testing data sets, and 98% of the data points lie within the 15% of AARD deviations. Furthermore, SHapley additive explanation (SHAP) analysis was employed to interpret the ML results and rationalize the viscosity predictions. The result is an ML approach that accurately predicts viscosity and will aid in accelerating the design of appropriate DESs for industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗

DOE OSTI2020

Extracting the Frequency-Dependent Dynamic Stokes Shift from Two-Dimensional Electronic Spectra with Prominent Vibrational Coherences

The dynamic Stokes shift is a common means for characterizing ultrafast solvation dynamics of electronically excited states. Here we extract the excitation frequency-dependent dynamic Stokes shift from two-dimensional electronic spectra (2DES) of cresyl violet, a molecule with a well-defined vibronic progression. The extracted dynamic Stokes shift function, S(t), exhibits oscillatory behavior, and the oscillatory components are assigned to intramolecular vibrational modes through DFT and TD-DFT calculations. Here, the well-characterized oscillations are incorporated into the fitting procedure of S(t). The excitation frequency dependence of the ultrafast response is examined through the analysis of S(t) obtained from slices taken at different excitation frequencies of the 2DES spectra. The extracted ultrafast timescales range from 36 to 98 fs, and we interpret the frequency dependence of the timescales in the context of other dynamic processes that also lead to lineshape changes in the 2DES spectrum, such as vibrational energy relaxation and spectral diffusion. Through comparison of the extracted timescales, we find that the fastest timescales are extracted over a range of excitation frequencies, where contributions from vibrational relaxation and spectral diffusion can be minimized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Probing Conformational Evolution and Associated Dynamics of Mg(N(SO 2 CF 3 ) 2 ) 2 ·Dimethoxyethane Adduct Using Solid-State 19 F and 1 H NMR

Bis(trifluoromethanesulfonimide) or TFSI is widely used as a counter anion in electrolyte design due to its structural flexibility and chemical stability. Here we studied the conformational variations and associated dynamics of TFSI in adduct of Mg(TFSI) 2 with dimethoxyethane (DME), a solvate crystalline material using solid-state 1 H and 19 F NMR. TFSI molecular motion in this solvate structure falls within the timescale of the 19 F NMR experiment, yielding spectroscopic signatures for unique TFSI conformers under the coordination environment of Mg 2+ cation. Within the temperature range of -5 to 82 °C, we observe nine distinct TFSI sites in both crystalline and disordered regions using 19 F NMR, reflecting complexity of structural and dynamics of TFS1 anions within solvate structure. The four distinguishable sites in the disordered region for the two CF 3 groups of the same TFSI molecule are identified using chemical shift analysis. The exchange rate constants from site to site are calculated through variable temperature 19 F NMR and two-dimensional (2D) exchange spectroscopy (EXSY) experiments, along with respective activation enthalpies using Eyring's formulation. The flip rate of CF 3 around the S-C bond is estimated as ~ 15 s -1 at 8 °C with ΔH ≠ ~ 22 kJ/mol, but the rotation of the entire TFSI is 4.8 s -1 at 8 °C with a significantly greater ΔH ≠ = 98 ± 10 kJ/mol. Furthermore, the slow conversion of trans to cis conformers at a lower temperature (T ≤ 1 °C) in the crystalline region is monitored, with a conversion rate of ~ 2 x 10 -5 s -1 at -5 °C. Density functional theory (DFT)-based calculations were performed to support further the assignment of experimental chemical shifts, and the activation energy E a = 21.1 kJ/mol obtained for the cis to trans transition is consistent with experimental values. The combined set of 19 F and 1 H under both one-dimensional (1D) and 2D NMR methods demonstrated here can be further used for examining electrode-electrolyte interfaces to probe the motions of various constituents that can enable detailed studies of interfacial processes and dynamics. Ultimately, such studies will aid in the design and discovery of interfacial constructs in which directed defect chemistry, chemical moiety distribution, and nanostructure are employed to drive efficient charge transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Evidence for Field-Dependent Charge Separation Caused by Mixed Phases in Polymer–Fullerene Organic Solar Cells

As organic photovoltaic performance approaches 20% efficiencies, causal structure–performance relationships must be established for devices to realize theoretical limits and become commercially competitive. Here, we reveal evidence of a causal relationship between mixed donor–acceptor interfaces and charge generation in polymer–fullerene solar cells. To do this, we combine a holistic loss analysis of device performance with quantitative synchrotron X-ray nanocharacterization to identify a >98% anticorrelation between field-dependent geminate recombination and nanodomain purity. Importantly, our analysis eliminates other possible explanations of the performance trends, a requirement to establish causality. The unprecedented granular level of our analysis also separates field-dependent and field-independent recombination at the interface, where we find for the first time that this system is free of field-independent recombination, a loss channel that plagues high-performance systems, including those with non-fullerene acceptors. Furthermore, this result broadens the case that minimizing mixed phases to promote sharp interfaces between pure aggregated domains is the ideal nanostructure for realizing theoretical efficiency limits of organic photovoltaics.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Chain Conformations of TEMPO-Based Organic Radical Polymers with Varying Radical Loading and Temperature in Battery-Relevant Solvents

Poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl methacrylate) (PTMA) is an organic radical polymer that is a promising active material in organic batteries. The proximity of the radical groups impacts the nature of charge transfer, in which closer packing promotes electron exchange; however, the chain conformation of PTMA is not well understood. Here, the conformation of PTMA in, and its thermodynamic interactions with, battery-relevant solvents is determined using small-angle neutron scattering (SANS). N-methyl-2-pyrrolidone (NMP) and 50:50 (wt %) ethylene carbonate/dimethyl carbonate (EC/DMC) mixtures with PTMA of varying radical content (68 vs 98%) and temperature (25 and 60 °C) are examined. Both solvents are theta solvents for PTMA irrespective of radical loading and temperature. PTMA attains an expanded chain conformation in NMP and a more compact polymer chain conformation in EC/DMC. Lastly, the electrochemical performance of PTMA films formed from EC/DMC shows improved performance relative to those cast from NMP, which is interpreted to indicate that the compact conformation of PTMA in EC/DMC enables improved inter- and intrachain charge transfer.

25 ENERGY STORAGE↗

DOE OSTI2024

Sulfonated Aromatic Polypentenamers: Scope of the Acetyl Sulfate Reaction

A precision polymer featuring one phenyl pendant at every fifth carbon on a polyethylene backbone was modified to varying degrees of sulfonation (DS = 33–98%) using acetyl sulfate with standard conditions by varying reaction times (up to 48 h). This soft, homogeneous method allows for evenly distributed phenylsulfonic acid groups with minimal side reactions and results in light brown, transparent materials with glass transition temperatures of 33–78 °C that increase with DS and parent polymer molar mass. The DS was accurately determined through well-resolved 1 H NMR (DSHNMR) signals of the regularly spaced phenyl groups and corroborated by inverse-gated decoupling 13 C NMR analysis. These analyses were compared to a series of other commonly accepted methods for DS determination including titration and elemental analysis (EA). The DS by titration (DS titr ) also increased with reaction time but was consistently lower than those determined by NMR. Significant discrepancies between theoretical and measured sulfur mass were observed for several samples through EA. Qualitative methods, such as infrared spectroscopy and thermal analyses, were also performed and correlated well with the DS determined by NMR. Here, this study presents a promising method to achieve a complete scope of homogeneous sulfonation from mild reaction conditions and presents a case to determine DS through multiple methods, with spectroscopic analyses, such as NMR, being potentially the most valuable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Decoding Active Sites for Highly Efficient Semihydrogenation of Acetylene in Palladium–Copper Nanoalloys

Accurately decoding the three-dimensional atomic structure of surface active sites is essential yet challenging for a rational catalyst design. Here, we used comprehensive techniques combining the pair distribution function and reverse Monte Carlo simulation to reveal the surficial distribution of Pd active sites and adjacent coordination environment in palladium-copper nanoalloys. After the fine-tuning of the atomic arrangement, excellent catalytic performance with 98% ethylene selectivity at complete acetylene conversion was obtained in the Pd 34 Cu 66 nanocatalysts, outperforming most of the reported advanced catalysts. Further, t he quantitative deciphering shows a large number of active sites with a Pd-Pd coordination number of 3 distributed on the surface of Pd 34 Cu 66 nanoalloys, which play a decisive role in highly efficient semihydrogenation. This finding not only opens the way for guiding the precise design of bimetal nanocatalysts from atomic-level insight but also provides a method to resolve the spatial structure of active sites.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Heterogeneous Organochromium Catalysts for Stereoselective Isoprene Polymerization

In this study, heterogeneous organochromium catalysts have been developed via surface lithiation of traditional surface organometallic complexes to mediate stereoselective isoprene polymerization. Chemisorption of the molecular complex Cr(CH 2 SiMe 3 ) 4 on high surface area anatase titania nanoparticles as well as on a silica support led to the bipodal complexes Cr/TiO 2 and Cr/SiO 2 , respectively. Subsequent reductive lithium intercalation with n-butyllithium led to the formation of lower valent Cr 2+ species Cr/LTO and Cr/Li/SiO 2 . Alternatively, Cr(CH 2 SiMe 3 ) 4 was allowed to react with nBuLi-reduced anatase titania (LTO) to provide Cr/LTO Inv . Cr/LTO and Cr/Li/SiO 2 both polymerize isoprene with very high activities (154 and 174 kg molCr –1 h –1 , respectively) to provide polyisoprene with cis-1,4 selectivity up to 82% in toluene at 50 °C. On the other hand, Cr/SiO 2 provides polyisoprene with excellent trans-1,4 selectivity up to 98% (16 kg molCr –1 h –1 ), and Cr/TiO 2 was catalytically inactive. Cr/LTO Inv is less active and selective, and X-ray absorption spectroscopy (XAS) measurements of the precatalyst revealed the presence of a mixture of metallic Cr 0 , Cr 4+ , and only minor Cr 2+ species. Thus, surface lithiation can promote the formation of lower valent metal centers which enable stereocontrol in isoprene polymerizations and may be extended as a general protocol to other catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Insights into Chemical Prelithiation of SiO x /Graphite Composite Anodes through Scanning Electron Microscope Imaging

Initial Coulombic efficiency (ICE) is critical for determining the energy density of lithium-ion batteries (LIBs) used for practical applications; however, it is typically disregarded in anode research. We used SiO x and graphite composite anodes for commercial lithium-ion batteries in our preliminary research to achieve a balance between ICE, capacity, and cycling life. ICE reached 88%; however, it needs further improvement for commercial applications. Prelithiation is a process that involves the introduction of extra lithium ions into LIBs during their manufacturing to enhance the overall performance of the LIBs. We applied a chemical prelithiation method on our SiO x /graphite composite anodes, which comprised 95 wt % of the active material mass loading on the electrode. The ICE increased from 88% to 98% using an aryllithium reagent impregnation method within 2 min of prelithiation. The anode’s specific capacity density, rate, and cycle performance also significantly improved. Scanning electron microscopy (SEM) imaging enhanced by an osmium tetroxide staining method indicated that the P-anode contained a stable solid electrolyte interface (SEI) layer after the prelithiation process and cycling electrochemical test. The P-anode’s stable charge differential peak over 500 cycles also showcases a robust artificial SEI layer that was generated by the prelithiation procedure. Here, this prelithiation process has significant potential for adoption in the LIB industry’s current electrode manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗