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DOE OSTI2015

Photodissociation of the carbon monoxide dication in the {sup 3}Σ{sup −} manifold: Quantum control simulation towards the C{sup 2+} + O channel

The photodissociation and laser assisted dissociation of the carbon monoxide dication X{sup 3}Π CO{sup 2+} into the {sup 3}Σ{sup −} states are investigated. Ab initio electronic structure calculations of the adiabatic potential energy curves, radial nonadiabatic couplings, and dipole moments for the X {sup 3}Π state are performed for 13 excited {sup 3}Σ{sup −} states of CO{sup 2+}. The photodissociation cross section, calculated by time-dependent methods, shows that the C{sup +} + O{sup +} channels dominate the process in the studied energy range. The carbon monoxide dication CO{sup 2+} is an interesting candidate for control because it can be produced in a single, long lived, v = 0 vibrational state due to the instability of all the other excited vibrational states of the ground {sup 3}Π electronic state. In a spectral range of about 25 eV, perpendicular transition dipoles couple this {sup 3}Π state to a manifold of {sup 3}Σ{sup −} excited states leading to numerous C{sup +} + O{sup +} channels and a single C{sup 2+} + O channel. This unique channel is used as target for control calculations using local control theory. We illustrate the efficiency of this method in order to find a tailored electric field driving the photodissociation in a manifold of strongly interacting electronic states. The selected local pulses are then concatenated in a sequence inspired by the “laser distillation” strategy. Finally, the local pulse is compared with optimal control theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Reconciling tensor and scalar observables in G-inflation

The simple m 2Φ2 potential as an inflationary model is coming under increasing tension with limits on the tensor-to-scalar ratio r and measurements of the scalar spectral index n s . Cubic Galileon interactions in the context of the Horndeski action can potentially reconcile the observables. However, we show that this cannot be achieved with only a constant Galileon mass scale because the interactions turn off too slowly, leading also to gradient instabilities after inflation ends. Furthermore, allowing for a more rapid transition can reconcile the observables but moderately breaks the slow-roll approximation leading to a relatively large and negative running of the tilt αs that can be of order n s -1. We show that the observables on CMB and large scale structure scales can be predicted accurately using the optimized slow-roll approach instead of the traditional slow-roll expansion. Upper limits on |αs| place a lower bound of r ≳ 0.005 and, conversely, a given r places a lower bound on |α s |, both of which are potentially observable with next generation CMB and large scale structure surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

DOE OSTI2019

Global Optimization of Adsorbate Covered Supported Cluster Catalysts: The Case of Pt 7 H 10 CH 3 on α-Al 2 O 3

Determining structures of supported sub-nanometer catalytic clusters is important for finding binding sites, active sites, and reaction mechanisms. In realistic conditions, the cluster may be covered with adsorbed reactants and intermediates, which strongly affect the structure of the cluster compared to the low coverage regime. The global optimization of supported adsorbate-covered clusters is not possible with existing methods. In this paper, we present a customized Basin Hopping (BH) approach, with a core (metal cluster) – shell (adsorbates) separation scheme, and perform first applications to the search of low-energy isomers of Pt 7 /α-Al 2 O 3 at high hydrogen coverage (10H). The presence of adsorbates significantly alters the low-energy isomers compared to bare Pt 7 /α-Al 2 O 3 . Molecular dynamics simulations additionally show the different time-scales associated with the mobility of H and Pt atoms. The revised BH method with core-shell separation presents key advantages for the structural exploration of adsorbate-covered supported catalysts, relevant to realistic catalytic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Optimization design of helium circulator diffuser in HTR-PM - 18488

Circulator is very important in HTR-PM. It needs to supply enough pressure rise to circulate cooled helium in the primary loop of HTR-PM to bring heat out. Its pressure rise requirement is the highest among the worldwide circulators. Diffuser is one main component to produce pressure rise for circulator. And the most particular for HTR-PM is that the helium must flow out from two round tubes after flowing through the diffuser, which is very different from other circulators. This special export structure increases flow loss and decreases diffuser efficiency. So it is necessary to optimize diffuser to satisfy high pressure rise requirement of HTR-PM circulator with the special export structure. Four geometrical variables of diffuser have been studied and optimized. Based on the flow and performance analysis, the optimum structure was chosen. Then the detailed simulation was done by combining it with impeller to obtain performance characteristics of the whole circulator. Finally, the simulation results were compared with experimental results. It was obtained that simulation pressure rise was 201 kPa and experimental result was 210 kPa, which verified that optimization design of diffuser was effective. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

An error-in-constitutive equations strategy for topology optimization for frequency-domain dynamics

This paper presents a topology optimization formulation for frequency-domain dynamics to reduce solution dependence upon initial guess and considered loading conditions. Due to resonance phenomena in undamped steady-state dynamics, objectives measuring dynamic response possess many local minima that may represent poor solutions to a design problem, an issue exacerbated for design with respect to multiple frequencies. In this work, we propose an extension of the modified error-in-constitutive-equations (MECE) method, used previously in material identification inverse problems, as a new approach for frequency-domain dynamics topology optimization to mitigate these issues. The main idea of the proposed framework is to incorporate an additional penalty-like term in the objective function that measures the discrepancy in the constitutive relations between stresses and strains and between inertial forces and displacements. Then, the design problem is cast within a PDE-constrained optimization formulation in which we seek displacements, stresses, inertial forces, and a density-field solution that minimize our new objective subject to conservation of linear momentum plus some additional constraints. We show that this approach yields superior designs to conventional gradient-based optimization approaches that solely use a functional of displacements as the objective, while strictly enforcing the constitutive equations. The MECE strategy integrates into a density-based topology optimization scheme for void–solid or two-phase material structural design. We highlight the merits of our approach in a variety of scenarios for direct frequency response design, considering multiple frequency load cases and structural objectives.

42 ENGINEERING↗

DOE OSTI2018

Subdiffraction-resolution live-cell imaging for visualizing thylakoid membranes

© 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd The chloroplast is the chlorophyll-containing organelle that produces energy through photosynthesis. Within the chloroplast is an intricate network of thylakoid membranes containing photosynthetic membrane proteins that mediate electron transport and generate chemical energy. Historically, electron microscopy (EM) has been a powerful tool for visualizing the macromolecular structure and organization of thylakoid membranes. However, an understanding of thylakoid membrane dynamics remains elusive because EM requires fixation and sectioning. To improve our knowledge of thylakoid membrane dynamics we need to consider at least two issues: (i) the live-cell imaging conditions needed to visualize active processes in vivo; and (ii) the spatial resolution required to differentiate the characteristics of thylakoid membranes. Here, we utilize three-dimensional structured illumination microscopy (3D-SIM) to explore the optimal imaging conditions for investigating the dynamics of thylakoid membranes in living plant and algal cells. We show that 3D-SIM is capable of examining broad characteristics of thylakoid structures in chloroplasts of the vascular plant Arabidopsis thaliana and distinguishing the structural differences between wild-type and mutant strains. Using 3D-SIM, we also visualize thylakoid organization in whole cells of the green alga Chlamydomonas reinhardtii. These data reveal that high light intensity changes thylakoid membrane structure in C. reinhardtii. Moreover, we observed the green alga Chromochloris zofingiensis and the moss Physcomitrella patens to show the applicability of 3D-SIM. This study demonstrates that 3D-SIM is a promising approach for studying the dynamics of thylakoid membranes in photoautotrophic organisms during photoacclimation processes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

BH-DFTB/DFT calculations for iron clusters

We present a study on the structural, electronic, and magnetic properties of Fe{sub n}(n = 2 − 20) clusters by performing density functional tight binding (DFTB) calculations within a basin hopping (BH) global optimization search followed by density functional theory (DFT) investigations. The structures, total energies and total spin magnetic moments are calculated and compared with previously reported theoretical and experimental results. Two basis sets SDD with ECP and 6-31G** are employed in the DFT calculations together with BLYP GGA exchange-correlation functional. The results indicate that the offered BH-DFTB/DFT strategy collects all the global minima of which different minima have been reported in the previous studies by different groups. Small Fe clusters have three kinds of packing; icosahedral (Fe{sub 9−13}), centered hexagonal antiprism (Fe{sub 14−17}, Fe{sub 20}), and truncated decahedral (Fe{sub 17(2)}, Fe{sub 18−19}). It is obtained in a qualitative agreement with the time of flight mass spectra that the magic numbers for the small Fe clusters are 7, 13, 15, and 19 and with the collision induced dissociation experiments that the sizes 6, 7, 13, 15, and 19 are thermodynamically more stable than their neighboring sizes. The spin magnetic moment per atom of Fe{sub n}(n = 2 − 20) clusters is between 2.4 and 3.6 μ{sub B} for the most of the sizes. The antiferromagnetic coupling between the central and the surface atoms of the Fe{sub 13} icosahedron, which have already been reported by experimental and theoretical studies, is verified by our calculations as well. The quantitative disagreements between the calculations and measurements of the magnetic moments of the individual sizes are still to be resolved.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Optimizing HVAC Operations in Multi-unit Buildings for Grid Demand Response

The thermal inertia of buildings, along with the flexibility associated with thermostatically controlled loads (TCL) allows heating ventilation and cooling (HVAC) systems to be used for grid demand response (DR). In this work, we consider an HVAC system that serves multiple units in a residential building to meet their space heating requirements. We aim to determine the optimal power flow to each unit that minimizes the power costs incurred by the building's occupants while keeping in consideration their thermal comfort. The DR program is assumed to allow the building temperatures to deviate from the set-points up to a maximum limit. Despite the complex, non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using quadratic programming. Since HVAC systems can run on either electricity or natural gas, we study the efficacy of the DR regime for both hourly electricity prices and flat gas prices over the course of 24 hours. Finally, we run simulations to determine the optimal thermal power and the evolution of unit temperatures for various energy pricing schemes.

Naqvi, Syed A.↗

DOE OSTI2022

Shell-Based Support Structure for the 45 GHz ECR Ion Source MARS-D

Superconducting electron cyclotron resonance ion sources (ECRISs) using NbTi coils and optimized for 28 GHz resonant heating have been successfully operated for almost two decades. Moving to higher heating frequencies requires increased magnetic fields, but traditional racetrack-and-solenoid ECRIS structures are at their limit using NbTi. Rather than moving to a superconductor untested in this field, we report the Mixed Axial and Radial field System (MARS) being developed at Lawrence Berkeley National Laboratory employs a novel closed-loop-coil design that more efficiently utilizes conductor fields and will allow the use of NbTi in a next-generation, 45 GHz ECRIS. This article presents the design of the shell-based support structure central to the MARS-D magnet design, as well as structural analysis of its components and optimization of pre-load parameters that will guarantee its successful operation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Influence of functional groups on low-temperature combustion chemistry of biofuels

Ongoing progress in synthetic biology, metabolic engineering, and catalysis continues to produce a diverse array of advanced biofuels with complex molecular structure and functional groups. In order to integrate biofuels into existing combustion systems, and to optimize the design of next-generation combustion systems, understanding connections between molecular structure and ignition at low-temperature conditions (< 1000 K) remains a priority that is addressed in part using chemical kinetics modeling. The development of predictive models relies on detailed information, derived from experimental and theoretical studies, on molecular structure and chemical reactivity, both of which influence the balance of chain reactions that occur during combustion – propagation, termination, and branching. In broad context, three main categories of reactions affect ignition behavior: (i) initiation reactions that generate a distribution of organic radicals, ; (ii) competing unimolecular decomposition of and bimolecular reaction of with O2; (iii) decomposition mechanisms of peroxy radical adducts (RO), including isomerization via RO ⇌ OOH. Furthermore, all three categories are influenced by functional groups in different ways, which causes a shift in the balance of chain reactions that unfold over complex temperature- and pressure-dependent mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

SU-F-T-617: Remotely Pre-Planned Stereotactic Ablative Radiation Therapy: Validation of Treatment Plan Quality

Purpose: We propose a workflow to improve access to stereotactic ablative radiation therapy (SABR) for rural patients. When implemented, a separate trip to the central facility for simulation can be eliminated. Two elements are required: (1) Fabrication of custom immobilization devices to match positioning on prior diagnostic CT (dxCT). (2) Remote radiation pre-planning on dxCT, with transfer of contours/plan to simulation CT (simCT) and initiation of treatment same-day or next day. In this retrospective study, we validated part 2 of the workflow using patients already treated with SABR for upper lobe lung tumors. Methods: Target/normal structures were contoured on dxCT; a plan was created and approved by the physician. Structures were transferred to simCT using deformable image registration and the plan was re-optimized on simCT. Plan quality was evaluated through comparison to gold-standard structures contoured on simCT and a gold-standard plan based on these structures. Workflow-generated plan quality in this study represents a worst-case scenario as these patients were not treated using custom immobilization to match dxCT position as would be done when the workflow is implemented clinically. Results: 5/6 plans created through the pre-planning workflow were clinically acceptable. For all six plans, the gold-standard GTV received full prescription dose, along with median PTV V95%=95.2% and median PTV D95%=95.4%. Median GTV DSC=0.80, indicating high degree of similarity between the deformed and gold-standard GTV contours despite small GTV sizes (mean=3.0cc). One outlier (DSC=0.49) resulted in inadequate PTV coverage (V95%=62.9%) in the workflow plan; in clinical practice, this mismatch between deformed/gold-standard GTV would be revised by the physician after deformable registration. For all patients, normal tissue doses were comparable to the gold-standard plan and well within constraints. Conclusion: Pre-planning SABR cases on diagnostic imaging generated clinically acceptable plans. Coupled with rapid-prototyped custom immobilization, this workflow may improve treatment access for rural patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Discovery and structure-based design of 4,6-diaminonicotinamides as potent and selective IRAK4 inhibitors

The identification of small molecule inhibitors of IRAK4 for the treatment of autoimmune diseases has been an area of intense research. We discovered novel 4,6-diaminonicotinamides which potently inhibit IRAK4. Optimization efforts were aided by X-ray crystal structures of inhibitors bound to IRAK4. Structure activity relationship (SAR) studies led to the identification of compound 29 which exhibited sub-micromolar potency in a LTA stimulated cellular assay.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Salt Solutions in Carbon Nanotubes: The Role of Cation-π Interactions

Understanding the structure of aqueous electrolytes at interfaces is essential for predicting and optimizing device performance for a wide variety of emerging energy and environmental technologies. In this work, we investigate the structure of two com- mon salt solutions, NaCl and KCl, at a hydrophobic interface within narrow carbon nanotubes (CNTs). Using a combination of first-principles and classical molecular dynamics simulations in conjunction with molecular orbital analysis, we find that the solvation structure of the cations in the CNTs can deviate substantially from the conventional weakly interacting hydrophobic picture. Instead, interactions between solvated ions and π-orbitals of the CNTs are found to play a critically important role. Specifically, the ion solvation structure is ultimately determined by a complex interplay between cation- interactions and the intrinsic flexibility of the solvation shell. In the case of K + , these effects result in an unusually strong propensity to partially desolvate and reside closer to the carbon wall than both Na + and Cl - , in sharp contrast to the known ion ordering at the water-vapor interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Strikingly high amount of tricin-lignin observed from vanilla (Vanilla planifolia) aerial roots

Lignin has attracted tremendous interest as a renewable resource for biofuels, biomaterials, and chemicals especially in the era of bio-based refineries. The structural studies of lignin play an essential role in both understanding the nature and biosynthesis of these polymers and optimizing their valorization values. In this study, we have investigated the structures of lignin from different tissues—aerial roots, nodes, internodes, and seeds, from vanilla (Vanilla planifolia) by using gel permeation chromatography (GPC), heteronuclear single-quantum coherence (HSQC) nuclear magnetic resonance (NMR), and 31P NMR. An unusual tricin-lignin was observed in the aerial roots of vanilla with an strikingly high level of tricin unit, whereas the lignin from the nodes and internodes displayed traditional S/G type lignin with only 4–10% tricin abundance. The aerial roots lignin is primarily composed of β-O-4' alkyl-aryl ether substructures (96% of linkages) in comparison to 65 and 73% in the nodes and internodes lignin, respectively. Additionally, thioacidolysis quantification results showed that lignin from aerial roots has 29.1 mg g -1 tricin, about 3- to 5-fold higher than the lignins isolated from nodes (10.1 mg g -1 ) and internodes (6.9 mg g -1 ). This communication of a particularly high level of tricin-lignin in vanilla plant has important impacts including: (1) the presence of the high amount of tricin as part of lignin from aerial roots could play a vital role for the valorization of lignin, even tricin itself, as a feedstock for value-added chemicals and commodities; and (2) it could open new ways to scientists to design and engineer the structure of tricin-lignin, or lignin in general, to confer plants with new or improved properties due to the plasticity of lignification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Internal influences of hydrolysis conditions on rutile TiO2 pigment production via short sulfate process

Highlights: • A novel short sulfate process was proposed to produce rutile TiO{sub 2} pigment. • Effects and internal influences of hydrolysis conditions were investigated in detail. • Intrinsic relationship between hydrolysis conditions and pigment properties were revealed. - Abstract: Rutile TiO{sub 2} white pigment was prepared via short sulfate process by using the unenriched industrial TiOSO{sub 4} solution as titanium source through authigenic seed hydrolysis process. The effects and internal influences of hydrolysis conditions on the structure, particle size distribution and pigment properties for the as-synthesized samples were investigated, involving the inducing hydrolysis water volume ratio, ripening time and hydrolysis time after the second boiling point. These hydrolysis factors influenced the number and quality of the initial formed hydrolysis nuclei, the crystal growth and the particle aggregation velocity, eventually determined the pigment properties. And the conditions had internal mathematical regression correlation with crystal structure, particle polydispersity index and pigment properties. The optimal inducing hydrolysis water volume ratio is of 0.123, ripening time is of 29.05 min, and hydrolysis time is of 2.6 h.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗

DOE OSTI2025

Tailored Additive Design of Scaffold‐Free Porous Mg for Ultimate Hydrogen Storage

For hydrogen storage materials to become practically viable, comprehensive improvements in key properties—kinetics, thermodynamics, thermal transport, and durability—are crucial. Porous Mg structure has been proposed as a promising strategy due to its high storage capacity and ability to accommodate volume expansion. However, challenges such as sluggish kinetics and structural degradation resulting from instability due to vacant sites still remain. In this study, a tailored design of porous Mg structure with site-specific transition metal dual-doping and structure-reinforced carbon nanotube (CNT)-framework is presented for optimal hydrogen storage. Ti and Ni are strategically deposited on the surface to synergistically enhance hydrogen sorption kinetics by facilitating hydrogen dissociation and diffusion, while CNTs are interpenetrated into 3D Mg structure for improving thermal conductivity and maintaining the porous structure. The resulting composite demonstrates exceptional performance, achieving hydrogen absorption and desorption of 4.8 and 5.8 wt%, respectively, within 10 min with an impressively low activation energy for absorption of 46 kJ mol −1 H 2 . Even after 50 cycles, its capacity and porous structure are well preserved, showing excellent cyclability in comparison with previously reported materials. In conclusion, this delicate design strategy based on a comprehensive understanding of structural and chemical characteristics is key to maximizing the targeted performance.

CNT embedding↗