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At least 685 records · Page 38

Advances and Challenges in Low‐Temperature Upcycling of Waste Polyolefins via Tandem Catalysis

Abstract Polyolefin waste is the largest polymer waste stream that could potentially serve as an advantageous hydrocarbon feedstock. Upcycling polyolefins poses significant challenges due to their inherent kinetic and thermodynamic stability. Traditional methods, such as thermal and catalytic cracking, are straightforward but require temperatures exceeding 400 °C for complete conversion because of thermodynamic constraints. We summarize and critically compare recent advances in upgrading spent polyolefins and model reactants via kinetic (and thermodynamic) coupling of the endothermic C─C bond cleavage of polyolefins with exothermic reactions including hydrogenation, hydrogenolysis, metathesis, cyclization, oxidation, and alkylation. These approaches enable complete conversion to desired products at low temperatures (<300 °C). The goal is to identify challenges and possible pathways for catalytic conversions that minimize energy and carbon footprints.

Zhang, Wei [State Key Laboratory of Petroleum Mole↗

Advances and Challenges in Low‐Temperature Upcycling of Waste Polyolefins via Tandem Catalysis

Abstract Polyolefin waste is the largest polymer waste stream that could potentially serve as an advantageous hydrocarbon feedstock. Upcycling polyolefins poses significant challenges due to their inherent kinetic and thermodynamic stability. Traditional methods, such as thermal and catalytic cracking, are straightforward but require temperatures exceeding 400 °C for complete conversion because of thermodynamic constraints. We summarize and critically compare recent advances in upgrading spent polyolefins and model reactants via kinetic (and thermodynamic) coupling of the endothermic C─C bond cleavage of polyolefins with exothermic reactions including hydrogenation, hydrogenolysis, metathesis, cyclization, oxidation, and alkylation. These approaches enable complete conversion to desired products at low temperatures (<300 °C). The goal is to identify challenges and possible pathways for catalytic conversions that minimize energy and carbon footprints.

C-C cleavage↗

Thermodynamic properties of the Nd-Bi system via emf measurements, $\mathrm{DFT}$ calculations, machine learning, and $\mathrm{CALPHAD}$ modeling

Thermodynamic properties of the Nd-Bi system were investigated using a combination of experimental measurements, first-principles calculations based on density functional theory (DFT), data mining and machine learning (DM + ML) predictions, and calculation of phase diagrams (CALPHAD) modeling. The electromotive force (emf) of Nd-Bi alloys in molten LiCl-KCl-NdCl 3 at 773–973 K was measured via coulometric titration of Nd into Bi for the determination of thermochemical properties such as activity coefficients and solubilities of Nd in Bi. A new peritectic reaction of [liquid + NdBi 2 = Nd 3 Bi 7 ] at 774 K was confirmed using differential scanning calorimetry, structural (X-ray diffraction), and microstructural (scanning electron microscopy) analyses. The unknown crystal structure of NdBi2 was suggested to be a mixture of the anti-La 2 Sb configuration and the La 2 Te-type configuration based on ML predictions for over 26,000 data-mined AB 2 -type configurations together with DFT-based verifications. Using the newly acquired experimental data and DFT-based calculations, the thermodynamic description of the Nd-Bi system was remodeled, and a more complete Nd-Bi phase diagram was calculated, including the Nd 3 Bi 7 compound, invariant transition reactions, and liquidus temperatures.

36 MATERIALS SCIENCE↗

Ionic Pairs-Engineered Fluorinated Covalent Organic Frameworks Toward Direct Air Capture of CO 2

The covalent organic frameworks (COFs) possessing high crystallinity and capability to capture low-concentration CO 2 (400 ppm) from air are still underdeveloped. The challenge lies in simultaneously incorporating high-density active sites for CO 2 insertion and maintaining the ordered structure. Herein, a structure engineering approach is developed to afford an ionic pair-functionalized crystalline and stable fluorinated COF (F-COF) skeleton. The ordered structure of the F-COF is well maintained after the integration of abundant basic fluorinated alcoholate anions, as revealed by synchrotron X-ray scattering experiments. The breakthrough test demonstrates its attractive performance in capturing (400 ppm) CO 2 from gas mixtures via O$-$C bond formation, as indicated by the in situ spectroscopy and operando nuclear magnetic resonance spectroscopy using 13 C-labeled CO 2 sources. Both theoretical and experimental thermodynamic studies reveal the reaction enthalpy of ≈-40 kJ mol -1 between CO 2 and the COF scaffolds. This implies weaker interaction strength compared with state-of-the-art amine-derived sorbents, thus allowing complete CO 2 release with less energy input. The structure evolution study from synchrotron X-ray scattering and small-angle neutron scattering confirms the well-maintained crystalline patterns after CO 2 insertion. In conclusion, the as-developed proof-of-concept approach provides guidance on anchoring binding sites for direct air capture (DAC) of CO 2 in crystalline scaffolds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision, and Reproducibility

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat a myriad of diseases. In this work, we examine the computation of alchemical relative binding free energies with an eye for assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2, and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2, and NAMD3 alpha. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between them of 0.50 kcal/mol. The correlation between packages is very good, with the lowest Spearman’s, Pearson’s and Kendall’s tau correlation coefficients being 0.92, 0.91, and 0.76, respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Enzyme Thermostability via Computationally Guided Covalent Stapling and Structural Basis of Enhanced Stabilization

Enhancing the thermostability of enzymes without impacting their catalytic function represents an important yet challenging goal in protein engineering and biocatalysis. We recently introduced a novel method for enzyme thermostabilization that relies on the computationally guided installation of genetically encoded thioether “staples” into a protein via cysteine alkylation with the noncanonical amino acid O-2-bromoethyl tyrosine (O2beY). Here, we demonstrate the functionality of an expanded set of electrophilic amino acids featuring chloroacetamido, acrylamido, and vinylsulfonamido side-chain groups for protein stapling using this strategy. Using a myoglobin-based cyclopropanase as a model enzyme, our studies show that covalent stapling with pchloroacetamido-phenylalanine (pCaaF) provides higher stapling efficiency and enhanced stability (thermodynamic and kinetic) compared to the other stapled variants and the parent protein. Interestingly, molecular simulations of conformational flexibility of the cross-links show that the pCaaF staple allows fewer energetically feasible conformers than the other staples, and this property may be a broader indicator of stability enhancement. Using this strategy, pCaaF-stapled variants with significantly enhanced stability against thermal denaturation (ΔT m ' = +27 °C) and temperature-induced heme loss (ΔT 50 = +30 °C) were obtained while maintaining high levels of catalytic activity and stereoselectivity. Crystallographic analyses of singly and doubly stapled variants provide key insights into the structural basis for stabilization, which includes both direct interactions of the staples with protein residues and indirect interactions through adjacent residues involved in heme binding. This work expands the toolbox of protein stapling strategies available for protein stabilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental and DFT Calculated IR Spectra of Guests in Zeolites: Acyclic Olefins and Host-Guest Interactions

We performed experimental and periodic density functional theory (DFT) IR spectroscopy to investigate the adsorption of acyclic olefins over both acidic and non-acidic zeolites. Two conjugated polyenes, 2,4-dimethyl-1,3-pentadiene (I) and 2,6-dimethyl-2,4,6-octatriene (II) were studied to probe organic intermediates that can form during methanol conversion, and that can lead to deactivating species known collectively as “coke.” We computed vibrational spectra using zeolite-adsorbed and gas-phase models for both neutral and protonated forms of I and II, and compared these DFT results to diffuse reflectance IR Fourier transform (DRIFT) spectra of zeolite-guest systems. Our experimental and computational results are precise enough to pinpoint that the gauche s-cis conformation of species I predominates during adsorption over de-aluminated zeolite beta. Computed zeolite-adsorbed spectra of the protonated species I and II best represent the DRIFT spectra obtained after the adsorption of the olefins on HMOR at 20 ?, with computed bands at 1543 and 1562 cm–1 for molecules I+ and II+, respectively, attributed to the allylic stretching mode, ?(C=C–C+). These computed band frequencies are within 6 cm–1 of experimental data and confirm that the interaction between neutral acyclic olefins and acidic zeolites leads to protonation of the olefin. Comparison of computed spectra of the protonated species in the gas phase to those in the zeolite indicates that the electrostatic interaction between alkenyl and alkadienyl cations and negative zeolite framework does not significantly impact the position of the allylic stretching bands. These results highlight that computed spectroscopy and thermodynamics coupled with experimental spectra can be used for elucidating complex mixtures in zeolites, and certain spectral features of adsorbed olefins can be accurately modeled by gas-phase calculations. ACKNOWLEDGMENTS BM and SMA were supported by the National Science Foundation under Award # CBET-1512442. Acknowledgment is made to the Donors of the American Chemical Society Petroleum Research Fund for support (or partial support) of this research (#589978-ND5, EDH and FCJ). MDB was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences (BES), Division of Materials Science and Engineering. CJM was supported by the DOE, Office of Science, BES, Division of Chemical Sciences, Geosciences, and Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated by Battelle for the U.S. DOE. Computing resources were generously provided through PNNL’s institutional computing (PIC).

Manookian, Babgen↗

Quantum speed limit for the out-of-time-ordered correlator from an open-system perspective

Scrambling, the delocalization of initially localized quantum information, is commonly characterized by the out-of-time-ordered correlator (OTOC). Employing the OTOC–Renyi-2 entropy theorem, we derive a quantum speed limit for the OTOC, which sets a lower bound for the rate with which information can be scrambled. This bound becomes particularly tractable by describing the scrambling of information in a closed quantum system as an effective decoherence process of an open system interacting with an environment. We prove that decay of the OTOC can be bounded by the strength of the system-environment coupling and two-point environmental correlation functions. We validate our analytic bound numerically using the nonintegrable transverse field Ising model. Furthermore, our results provide a universal and model-agnostic quantitative framework for understanding the dynamical limits of information spreading across quantum many-body physics, condensed matter systems, and engineered quantum platforms.

Fermions↗

Nonperturbative Lorentz violation and field quantization

Regimes of Lorentz-violating effective field theories are studied in which departures from Lorentz symmetry are nonperturbative. Within a free toy theory exhibiting Lorentz breakdown involving an operator of mass dimension three, it is shown that conventional methods suffice to achieve field quantization and Fock-space construction. However, the absence of an observer-invariant energy-positivity condition requires physical input beyond the free theory for the unambiguous identification of a ground state. An investigation of the role of thermodynamics in this context is instigated.

Ground state↗

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R 2 = 0.43–0.70) previous state-of-the-art thermodynamic and kinetic models (R 2 = 0.04–0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Implementation of Ion Exchange Processes for Carbon Dioxide Mineralization Using Industrial Waste Streams

Sequestration of CO 2 within stable mineral carbonates (e.g., CaCO 3 ) represents an attractive emission reduction strategy because it offers a leakage-free alternative to geological storage of CO 2 in an environmentally benign form. However, the pH of aqueous streams equilibrated with gaseous streams containing CO 2 (pH < 4) are typically lower than that which is required for carbonate precipitation (pH > 8). Traditionally, alkalinity is provided by a stoichiometric reagent (e.g., NaOH) which renders these processes environmentally hazardous and economically unfeasible. This work investigates the use of regenerable ion-exchange materials to induce alkalinity in CO 2 -saturated aqueous solutions such that the pH shift required for mineralization occurs without the need for stoichiometric reagents. Na + -H + exchange isotherms (at [H + ] = 10 −8 –10 −1 M) and rates were measured for 13X and 4A zeolites and TP-207 and TP-260 organic exchange resins in batch equilibrium and fixed-bed exchange experiments, respectively. At solutions equilibrated with CO 2 at 1.0 atm (pH = 3.9), H + exchange capacities for the materials were similar (1.7–2.4 mmol H + /g material) and resulted in pH increases from 3.9 to greater than 8.0. Multi-component mixtures using Ca 2+ and Mg 2+ cations (at 10 −3 –10 −1 M) in CO 2 -saturated water were used to probe competitive ion exchange. The presence of divalent cations in solution inhibited H + exchange, reducing capacities to as low as 0.2 mmol H + /g for both resins and zeolites. Dynamic H + exchange capacities in fixed-bed ion exchange columns were similar to equilibrium values for resins (∼1.5 mmol/g) and zeolites (∼0.8 mmol/g) using inlet solutions that were equilibrated with gaseous streams of CO 2 at 1.0 atm. However, exchange kinetics were limited by intraparticle diffusion as indicated by the increased rate parameters with increasing inlet flow rates (20–160 cm 3 min −1 ). Experimental calcite precipitation from mixing the alkaline CO 3 2− -rich water solution obtained from the ion-exchange column with a simulated liquid waste stream solution achieved thermodynamic maximum yields. The results from these studies indicate that ion exchange processes can be used as an alternative to the addition of stoichiometric bases to induce alkalinity for the precipitation of CaCO 3 , thereby opening a pathway toward sustainable and economic mineralization processes.

42 ENGINEERING↗

The MOOSE fluid properties module

The fluid properties module in MOOSE~\cite{lindsay2022moose} serves a variety of fluid simulation applications based on MOOSE, including the MOOSE Navier Stokes module~\cite{moose_ns}, Pronghorn~\cite{pgh}, the MOOSE thermal hydraulics module, SAM~\cite{sam}, RELAP-7~\cite{relap7}, Sockeye~\cite{sockeye}, Pronghorn-subchannel~\cite{subchannel} and the MOOSE porous flow module~\cite{porous}. These applications are used to solve coarse mesh multi-dimensional thermal-hydraulics~\cite{pgh}, 1D systems analysis~\cite{sam,relap7} in nuclear reactor analysis, heat pipe modeling~\cite{sockeye} and porous flow simulations~\cite{porous} for underground gas storage and water seepage. The use of consistent fluid properties across fluid flow applications facilitates coupled flow simulations~\cite{anl_sam_pgh,osti_1889653}. Each application has historically driven the implementation of several fluid properties, which were later extended to be compatible with other applications. The unique diversity of applications of the module, due to its presence in MOOSE, has driven its expansion to new fluids, such as advanced nuclear reactor coolants and, more recently, arbitrary functions or tables-based property definitions, as detailed in section~\ref{content}, as well as numerous thermophysical properties and variable sets, as detailed in subsection~\ref{sec:prop}. The need for different discretizations of flow equations based on the compressibility of the fluid has motivated support for both primitive (pressure- and temperature-based) and conservative (internal energy- and specific volume-based) flow variables in the module. Thermodynamic relations are used to convert between these two formulations, as needed. The module serves a dual purpose of providing fluid properties for direct use in flow simulations and facilitating the implementation of user-specific fluid properties. Contributions of new properties for existing fluids or new fluids are strongly encouraged.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Life cycle assessment of novel heat exchanger for dry cooling of power plants based on encapsulated phase change materials

Cooling systems in power plants account for approximately 40% of total freshwater withdrawals in the U.S. Due to dwindling access to freshwater resources worldwide, continued operation of wet cooling systems poses a significant engineering challenge. To reduce water consumption, a novel air-cooled heat exchanger has been developed using encapsulated phase change material (EPCM) for dry cooling of power plants. Compared to traditional finned-tube air-cooled condensers, this novel EPCM heat exchanger improves the heat transfer coefficient and power plant efficiency while reducing the pressure drop and cooling system cost. Life cycle assessment (LCA) and techno-economic analysis (TEA) are used to evaluate the environmental and economic performance of EPCM heat exchangers from cradle-to-grave and to compare them to wet cooling and traditional air-cooled condensers. A thermodynamic model is developed to predict the EPCM heat exchanger performance for plant-scale operations. Equipment and construction costs for heat exchangers are estimated based on design parameters obtained from the thermodynamic model. Both process-LCA and economic-input–output LCA are used to simulate and test the sensitivity of EPCM alternatives with commercial wet and dry cooling technologies. We investigate options for EPCM end-of-life management upon retiring the heat exchanger and construct a process-based LCA model to estimate a greenhouse gas (GHG) emissions credit for recycling the EPCM. The life cycle GHG emission of the novel dry cooling technology is 1.16 kg CO 2 eq. /MWh compared with the 1.1–4.3 kg CO 2 eq. /MWh reported for commercial dry cooling technologies and consumes 9.5 L/MWh e of water for cradle-to-gate life cycle, which is significantly lower than that of wet cooling systems. The TEA shows many advantages of EPCM cooling technology over the state-of-art dry cooling solutions. Overall, the EPCM heat exchanger provides a better alternative compared to existing dry cooling and wet cooling technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A continuum framework for coupled solid deformation–fluid flow through anisotropic elastoplastic porous media

We present a continuum framework for coupled solid deformation–fluid flow in anisotropic elastoplastic porous media. A thermodynamic formulation of the coupled processes gives rise to an anisotropic Biot tensor that is a function of drained elastic tangent moduli tensor of the solid skeleton and the intrinsic bulk modulus of the solid constituent. Two effective stress measures emerge from the formulation, namely, σ', which is energy-conjugate to the elastic strain, and σ'', which is energy-conjugate to the plastic strain. For the special case of transverse isotropy that is commonly encountered in natural rocks, the Biot tensor can be expressed in terms of its normal and tangential components to the bedding plane, along with a microstructure tensor. Apart from its thermodynamic consistency, an advantage of this new formulation is that standard mixed finite element formulation can be employed to discretize the domain and solve initial boundary-value problems. We conduct plane strain simulations of coupled solid deformation–fluid flow in a transversely isotropic porous medium to demonstrate the impacts of material anisotropy, stress history, and the Biot tensor on the system response.

42 ENGINEERING↗

Unusual Temperature Dependence of Water Sorption in Semicrystalline Hydrogels

Abstract Water vapor sorption is a ubiquitous phenomenon in nature and plays an important role in various applications, including humidity regulation, energy storage, thermal management, and water harvesting. In particular, capturing moisture at elevated temperatures is highly desirable to prevent dehydration and to enlarge the tunability of water uptake. However, owing to the thermodynamic limit of conventional materials, sorbents inevitably tend to capture less water vapor at higher temperatures, impeding their broad applications. Here, an inverse temperature dependence of water sorption in poly(ethylene glycol) (PEG) hydrogels, where their water uptake can be doubled with increasing temperature from 25 to 50 °C, is reported. With mechanistic modeling of water–polymer interactions, this unusual water sorption is attributed to the first‐order phase transformation of PEG structures, and the key parameters for a more generalized strategy in materials development are identified. This work elucidates a new regime of water sorption with an unusual temperature dependence, enabling a promising engineering space for harnessing moisture and heat.

36 MATERIALS SCIENCE↗

Metal hydride composition-derived parameters as machine learning features for material design and H 2 storage

Though hydrogen is a promising energy carrier for a green future, many challenges persist. One is the difficulty in engineering storage solutions, with metal hydrides being a leading contender among solid-state strategies. To facilitate efficient searching of candidate materials, ridge regression, simple decision trees, random forest ensembles, and gradient boosting ensembles were employed to predict the energy of formation, with the random forest ensemble resulting in the lowest test set error. First, two public databases, Materials Project and HydPark, were searched for metal hydrides. Feature engineering was performed before the models were developed, resulting in electronegativity, density, atomic density, d-character, f-character, band gap, hydrogen weight fraction, magnetization, temperature, and pressure being retained. The models were then benchmarked by the lowest test error before a random forest ensemble was used to populate entries missing energy of formation. Furthermore, all were then scored by hydrogen storage capacity and energy of formation suitability. Readily available features including several derived from only the chemical formula which were found to be highly predictive. and so are promising for high-throughput screening of arbitrary novel hydride formulations and blends for thermodynamic feasibility.

25 ENERGY STORAGE↗

Material analysis of metal hydrides for bulk hydrogen storage

The United States Department of Energy (DOE) Hydrogen Storage Engineering Center of Excellence (HSECoE), 2009–2014, was established to evaluate the viability of material-based hydrogen storage for light duty vehicles. The HSECoE concluded that there were no metal hydrides that simultaneously met the DOE targets for gravimetric and volumetric capacity, and rate of onboard refueling. However, it was noted by the DOE that potential applications existed for stationary hydrogen storage systems. An application of particular interest is using a metal-hydride to store a hydrogen supply for fuel cell backup power to a 5 MWe data center. A generalized numerical model that coupled mass and energy conservation, chemical kinetics and thermodynamics was developed to simulate the discharge process for a given metal-hydride. The model was applied to an interstitial and a complex metal-hydride. In conclusion, it was found that the interstitial metal-hydride, which is discharged by a pressure swing is preferrable in a practical sense to the complex metal-hydride, which requires a temperature swing discharge process.

08 HYDROGEN↗

Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗