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Chen, Qian

Publications and source records attributed to Chen, Qian.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward High-Voltage Cathodes for Zinc-Ion Batteries: Discovery Pipeline and Material Design Rules

Efficient energy storage systems are crucial to address the intermittency of renewable energy sources. As multivalent batteries, Zn-ion batteries (ZIBs), while inherently low voltage, offer a promising low-cost alternative to Li-ion batteries due to the viable use of zinc as the anode. However, to maximize the potential impact of ZIBs, rechargeable cathodes with improved Zn diffusion are needed. To better understand the chemical and structural factors influencing Zn-ion mobility within battery electrode materials, we employ a high-throughput computational screening approach to systematically evaluate candidate intercalation hosts for ZIB cathodes, expanding the chemical search space on empty intercalation hosts that do not contain Zn. We leverage a high-throughput screening funnel to identify promising cathodes in ZIBs, integrating screening criteria with density functional theory (DFT)-based calculations of Zn2+ intercalation and diffusion inside the host materials. Using these data, we identify the design principles that favor Zn-ion mobility in candidate cathode materials. Building on previous work on divalent-ion cathodes, this study broadens the chemical space for next-generation multivalent energy storage systems.

electrodes↗
DOE OSTI2025

The role of soil chemical properties and microbial communities on Dendrocalamus brandisii bamboo shoot quality, Yunnan Province, China

Objective To explore the effects of soil nutrients and microbial communities on the quality of Dendrocalamus brandisii shoots in different regions, providing a scientific basis for their development and utilization. Methods Using seven different geographic sources of D. brandisii from Yunnan Province as research subjects, this study employs chemical analysis and high-throughput sequencing to reveal the relationship between soil nutrients, microbial functional groups, and the nutritional quality of bamboo shoots. Results The results indicate that there are significant differences in soil nutrient content among the regions ( p < 0.05), with bamboo shoots from Baoshan Changning (CN) exhibiting the best overall nutritional quality. The key factors influencing bacterial community changes include pH, available phosphorus (AP), and available potassium (AK). In contrast, the main factors affecting fungal community changes are pH, soil organic matter (SOM), available potassium (AK), and total nitrogen (TN). This version maintains clarity and logical flow, making it easier for readers to understand the different factors influencing bacterial and fungal community changes. The diversity indices of soil microbial communities among different sources of Dendrocalamus brandisii show significant differences ( p < 0.05). The dominant groups in the seven regions include Proteobacteria, Acidobacteriota, Actinobacteriota, Chloroflexi, Ascomycota, and Basidiomycota. The soil microbial community in Baoshan Changning (CN) shows significant structural differences compared to the other six regions, with the highest relative abundances of Chloroflexi and Acidobacteriota. In contrast, the highest relative abundance of Proteobacteria is found in Honghe Shiping (SP), while Actinobacteriota has the highest relative abundance in Yuxi Xinping (XP). RDA analysis indicates that soil nutrients (SOM, pH, AP, TN) affect the water content, soluble sugar, and crude fat of bamboo shoots. Additionally, the bacterial communities including Actinobacteriota, Chloroflexi, Patescibacteria, GAL15, and Cyanobacteria influence the water content, soluble sugar, ash content, protein, and lignin of bamboo shoots. Discussion In the fungal community, Basidiomycota, Kickxellomycota, Mucoromycota, unclassified-k-Fungi, and Glomeromycota affect the water content and tannin levels in bamboo shoots. In summary, soil nutrients and soil microorganisms are interconnected and work together to influence the quality of bamboo shoots.

Chen, Qian↗
DOE OSTI2024

Unveiling Structural Heterogeneity and Imbalance of Gold Decahedral Nanoparticles using Four-dimensional Scanning Transmission Electron Microscopy

Multi-twinned structures have been observed in technologically important crystal systems, for example diamond cubic and face-centered cubic (FCC) lattices, that include materials such as diamond, silicon, a wide range of noble metals, and their nanoscale counterparts. Beyond atomic building blocks, the special arrangements also occur in the self-assembly of nanoparticles (NP) and μm-sized colloidal particles and occupy parts of their phase diagrams. Spanning a wide range of length scales, the universality of the structures arises when the systems attempt to achieve multitwinned structures by overcoming geometric misfits during minimizing surface energies with entirely {111} or close-packing facets. While it is fundamental to understand how strain is sustained upon twinned structures and symmetry breaking, the knowledge will be paramount in practical aspects such as guiding and controlling the thin film growth, anisotropic NP growth, and self-assembly of NPs. Au decahedral (Dh) NP, as the most prevalent multi-twinned model system, fits five tetrahedral motifs into a circle by sharing an axis resulting in a geometric misfit angle of 7.35°, or a disclination with power of -7.35°. Postulating how Au FCC lattice adopts the misfit, theoretical models have been developed to address the underlying lattice symmetry and inhomogeneous strain distribution separately. Yet, experimental reports regarding the former have been limited due to the relatively large X-ray beam sizes that do not fit the sizes of NPs. On the other hand, though the latter has been widely adapted in the thermodynamics of small (<10 nm) multi-twinned nanoparticles, previous literature has shown that, at edge length of 17 nm, the theory’s is invalidated by shear strain that is observed in a defect-free Au Dh NP by high-resolution transmission electron microscopy (HR-TEM) imaging. Though the advancement of aberrationcorrected scanning transmission electron microscopy (AC-STEM) imaging and ab initio calculation techniques brings new opportunities, along with challenges in complicated image analysis and limitation in particle size (usually below 10 nm), the gap between nanoscale and mesoscale has never been extended to gain insight from atomic system with straightforward interaction potentials.

4D-STEM↗
DOE OSTI2024

Shape-persistent ladder molecules exhibit nanogap-independent conductance in single-molecule junctions

Molecular electronic devices require precise control over the flow of current in single molecules. However, the electron transport properties of single molecules critically depend on dynamic molecular conformations in nanoscale junctions. Here, in this work, we report a unique strategy for controlling molecular conductance using shape-persistent molecules. Chemically diverse, charged ladder molecules, synthesized via a one-pot multicomponent ladderization strategy, show a molecular conductance (d[log( G/G 0 )]/d x ≈ -0.1 nm -1 ) that is nearly independent of junction displacement, in stark contrast to the nanogap-dependent conductance (d[log( G/G 0 )]/d x ≈ -7 nm -1 ) observed for non-ladder analogues. Ladder molecules show an unusually narrow distribution of molecular conductance during dynamic junction displacement, which is attributed to the shape-persistent backbone and restricted rotation of terminal anchor groups. These principles are further extended to a butterfly-like molecule, thereby demonstrating the strategy's generality for achieving gap-independent conductance. Overall, our work provides important avenues for controlling molecular conductance using shape-persistent molecules. Achieving robust and controllable conductance in single-molecule junctions is challenging due to the dynamic nature of molecular conformations that fluctuate over operational timescales. A strategy using shape-persistent molecules has now been developed that demonstrates nearly junction-displacement-independent conductance, providing a stable solution for single-molecule electronic properties.

molecular electronics↗
DOE OSTI2024

Nanocrystal Assemblies: Current Advances and Open Problems

Here we explore the potential of nanocrystals (a term used equivalently to nanoparticles) as building blocks for nanomaterials, and the current advances and open challenges for fundamental science developments and applications. Nanocrystal assemblies are inherently multiscale, and the generation of revolutionary material properties requires a precise understanding of the relationship between structure and function, the former being determined by classical effects and the latter often by quantum effects. With an emphasis on theory and computation, we discuss challenges that hamper current assembly strategies and to what extent nanocrystal assemblies represent thermodynamic equilibrium or kinetically trapped metastable states. We also examine dynamic effects and optimization of assembly protocols. Finally, we discuss promising material functions and examples of their realization with nanocrystal assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Alkali‐Ion‐Assisted Activation of ε‐VOPO 4 as a Cathode Material for Mg‐Ion Batteries

Abstract Rechargeable multivalent‐ion batteries are attractive alternatives to Li‐ion batteries to mitigate their issues with metal resources and metal anodes. However, many challenges remain before they can be practically used due to the low solid‐state mobility of multivalent ions. In this study, a promising material identified by high‐throughput computational screening is investigated, ε‐VOPO 4 , as a Mg cathode. The experimental and computational evaluation of ε‐VOPO 4 suggests that it may provide an energy density of >200 Wh kg −1 based on the average voltage of a complete cycle, significantly more than that of well‐known Chevrel compounds. Furthermore, this study finds that Mg‐ion diffusion can be enhanced by co‐intercalation of Li or Na, pointing at interesting correlation dynamics of slow and fast ions.

25 ENERGY STORAGE↗
DOE OSTI2024

Nanoparticle self-assemblies with modern complexity

Thanks to decades of tireless efforts, nanoparticle assemblies have reached at an extremely high level of controllability, sophistication, and complexity, with new insights provided by integration with graph theory, cutting-edge characterization, and machine learning (ML)-based computation and modeling, as well as with ever-diversifying applications in energy, catalysis, biomedicine, optics, electronics, magnetics, organic biosynthesis, and quantum technology. Nanoparticle assemblies can be crystalline, known as superlattices or supracrystals. Their assembly entails a transition from disorder—dispersed nanoparticles—to order, which can be achieved through classical nucleation pathways or nonclassical pathways via prenucleation precursors or particle aggregation. Further, the periodic lattices allow facile manipulations of electrons, phonons, photons, and even spins, leading to advanced device components and metamaterials. Meanwhile, aperiodic assemblies out of nanoparticles, such as gels, networks, and amorphous solids, also start to attract attentions. Despite the loss of periodicity, symmetry-lowering or symmetry-breaking three-dimensional (3D) structures emerge with unique properties, such as chiroptical activity, topological mechanical strength, and quantum entanglement. Real-space imaging such as electron microscopy and X-ray based tomography methods are utilized to characterize these complex structures, while mathematical tools such as graph theories are in need to describe such complex structures. This issue aims to provide a timely review of the efforts in this greatly broadened materials design space including experiment, simulation, theory, and applications. Nine top experts (and their teams) from four countries deliver six review papers, summarizing fundamental mechanistic understandings of nanoparticle assemblies, highlighted with the developments of state-of-the-art in situ characterization tools and ML-assisted reverse engineering, and newly emergent applications of nanoarchitectures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

4D-STEM Mapping of Nanocrystal Reaction Dynamics and Heterogeneity in a Graphene Liquid Cell

Chemical reaction kinetics at the nanoscale are intertwined with heterogeneity in structure and composition. However, mapping such heterogeneity in a liquid environment is extremely challenging. Here, in this work, we integrate graphene liquid cell (GLC) transmission electron microscopy and four-dimensional scanning transmission electron microscopy to image the etching dynamics of gold nanorods in the reaction media. Critical to our experiment is the small liquid thickness in a GLC that allows the collection of high-quality electron diffraction patterns at low dose conditions. Machine learning-based data-mining of the diffraction patterns maps the three-dimensional nanocrystal orientation, groups spatial domains of various species in the GLC, and identifies newly generated nanocrystallites during reaction, offering a comprehensive understanding on the reaction mechanism inside a nanoenvironment. This work opens opportunities in probing the interplay of structural properties such as phase and strain with solution-phase reaction dynamics, which is important for applications in catalysis, energy storage, and self-assembly.

four-dimensional scanning transmission electron mi↗
DOE OSTI2024

Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates

Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Novel Structural Motif To Promote Mg-Ion Mobility: Investigating ABO 4 Zircons as Magnesium Intercalation Cathodes

There is an increasing need for sustainable energy storage solutions as fossil fuels are replaced by renewable energy sources. Multivalent batteries, specifically Mg batteries, are one energy storage technology that researchers continue to develop with hopes to surpass the performance of Li-ion batteries. However, the limited energy density and transport properties of Mg cathodes remain critical challenges preventing the realization of high-performance multivalent batteries. In this work, ABO 4 zircon materials (A = Y, Eu and B = V, Cr) are computationally and experimentally evaluated as Mg intercalation cathodes. Remarkably good Mg-ion transport properties were predicted and Mg-ion intercalation was experimentally verified in sol-gel synthesized zircon YVO 4 , EuVO 4 , and EuCrO 4 . Among them, EuVO 4 exhibited the best electrochemical performance and demonstrated repeated reversible cycling. While we believe that the one-dimensional diffusion channels and redox-active species tetragonal coordination limit the value of many zircons as high-performance cathodes, their unique structural motif of overlapping polyhedra along the diffusion pathway appears instrumental for promoting good Mg-ion mobility. The motif results in a favorable "6-5-4" change in coordination that avoids unfavorable sites with lower coordination along the diffusion pathway and a structural design metric for future Mg cathode development.

25 ENERGY STORAGE↗
DOE OSTI2023

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗
DOE OSTI2023

Unravelling crystal growth of nanoparticles

Crystal growth from nanoscale constituents is a ubiquitous phenomenon in biology, geology and materials science. Numerous studies have focused on understanding the onset of nucleation and on producing high-quality crystals by empirically sampling constituents with different attributes and varying the growth conditions. However, the kinetics of post-nucleation growth processes, an important determinant of crystal morphology and properties, have remained underexplored due to experimental challenges associated with real-space imaging at the nanoscale. Here we report the imaging of the crystal growth of nanoparticles of different shapes using liquid-phase transmission electron microscopy, resolving both lateral and perpendicular growth of crystal layers by tracking individual nanoparticles. We observe that these nanoscale systems exhibit layer-by-layer growth, typical of atomic crystallization, as well as rough growth prevalent in colloidal systems. Surprisingly, the lateral and perpendicular growth modes can be independently controlled, resulting in two mixed crystallization modes that, until now, have received only scant attention. Combining analytical considerations with molecular dynamics and kinetic Monte Carlo simulations, we develop a comprehensive framework for our observations, which are fundamentally determined by the size and shape of the building blocks. Furthermore, these insights unify the understanding of crystal growth across four orders of magnitude in particle size and suggest novel pathways to crystal engineering.

Imaging techniques↗
DOE OSTI2023

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗