arXiv subjects

Hai-Feng Li

Publications and source records attributed to Hai-Feng Li.

At least 19 recordsLinked to original sources

arXiv2026

Synergistic Interface Stability and High Room-Temperature Ionic Conductivity for Wide-Temperature All-Solid-State Batteries Based on Li6+xSixSb1-xS5I Electrolytes

Solid-state lithium-ion batteries (LIBs) are increasingly recognized for their exceptional energy density and safety. However, their widespread adoption is challenged by persistent issues such as thermal and electrochemical instability, dendrite formation, and limited compatibility with high-voltage cathodes. Sulfide-based solid electrolytes (SEs), particularly iodide argyrodites, offer outstanding ionic conductivity and stability; however, their practical application is constrained by the formation of space-charge layers, slow ion transport, and susceptibility to dendrite penetration. To address these challenges, we synthesized a novel Li6.6Si0.6Sb0.4S5I argyrodite electrolyte via ball milling and heat treatment, achieving a remarkable room-temperature ionic conductivity of 9.9 mS cm^-1. The electrolyte was integrated with a LiNbO3-coated LiNi0.7Co0.1Mn0.2O2 cathode to form an all-solid-state battery, which demonstrated an initial discharge capacity of 171.2 mAh g^-1, retained 84.2% of its capacity after 200 cycles at 0.5C, and maintained stable cycling across a broad temperature range from -20 degrees C to 60 degrees C. Our study shows that tailored electrolyte composition and a composite cathode configuration significantly enhance cycling stability and improve interfacial protection. These findings highlight the potential of Si-doped antimony-type iodide argyrodites for next-generation high-performance all-solid-state batteries, offering durable operation under diverse thermal conditions.

cond-mat.mtrl-sci↗

arXiv2026

Chemical tuning of magnetic ordering and cryogenic magnetocaloric response in zircon-type Gd1-xErxVO4

Chemical substitution offers an effective route to tune magnetic ordering and magnetocaloric performance in rare-earth oxides for cryogenic refrigeration. Here we investigate the structural evo lution, magnetic properties, and magnetocaloric effect of polycrystalline zircon-type Gd1-xErxVO4 (x=0, 0.1, 0.25, 0.5, and 0.75). Powder X-ray diffraction confirms that all samples crystallize in the tetragonal zircon structure without detectable impurity phases. Substitution of Gd3+ by the smaller Er3+ ion produces a systematic lattice contraction and modifies the magnetic behavior of the rare-earth sublattice. In particular, the magnetic ordering temperature is suppressed from 3.65(2) K in GdVO4 to 2.76(2) K in Gd0.9Er0.1VO4 , accompanied by a weakening of the spin-flop-like field-induced anomaly observed in the parent compound. A low Er concentration correspondingly improves the low-temperature magnetocaloric performance, with Gd0.9Er0.1VO4 exhibiting a max imum magnetic entropy change of 45.1 J kg-1 K-1 for mu_0 Delta H=7T. These results demonstrate that weak Er substitution effectively tunes the competition among exchange interactions, dipolar coupling, and magnetic anisotropy, optimizing the balance between magnetic ordering and available spin entropy in zircon-type rare-earth vanadates, which is crucial for developing efficient cryogenic refrigeration materials.

cond-mat.mtrl-sci↗

arXiv2026

Entropy engineering of BF-BT-based high-entropy ceramics for ultra-high energy storage performance

Dielectric capacitors are promising for pulsed power applications, but the energy storage performance of lead-free bulk ceramics is often limited by low breakdown strength and large ferroelectric hysteresis. Herein, a high entropy perovskite oxide BaTi0.2Zr0.2Sn0.2Hf0.2Nb0.1Sc0.1O3 was introduced into the BF-BT matrix to develop lead free high entropy ferroelectric ceramics. Multicomponent B-site substitution induces lattice distortion, enhanced pseudocubic characteristics, relaxor behavior, and grain refinement. These effects suppress polarization hysteresis and electrical conduction, resulting in a significant increase in breakdown strength. A maximum breakdown strength of 840 kV/cm1 and a recoverable energy density of 10.55 J/cm3 were achieved. Entropy-induced microstructural heterogeneity promotes a more uniform electric-field distribution and delays dielectric breakdown. This work demonstrates entropy engineering as an effective route to achieving high breakdown strength and superior energy-storage performance in lead-free ferroelectric ceramics.

cond-mat.mtrl-sci↗

arXiv2025

Synergistic effects of rare-earth doping on the magnetic properties of orthochromates: A machine learning approach

Multiferroic materials, particularly rare-earth orthochromates (RECrO$_3$), have garnered significant interest due to their unique magnetic and electric-polar properties, making them promising candidates for multifunctional devices. Although extensive research has been conducted on their antiferromagnetic (AFM) transition temperature (N$\acute{\textrm{e}}$el temperature, $T_\textrm{N}$), ferroelectricity, and piezoelectricity, the effects of doping and substitution of rare-earth (RE) elements on these properties remain insufficiently explored. In this study, convolutional neural networks (CNNs) were employed to predict and analyze the physical properties of RECrO$_3$ compounds under various doping scenarios. Experimental and literature data were integrated to train machine learning models, enabling accurate predictions of $T_\textrm{N}$, besides remanent polarization ($P_\textrm{r}$) and piezoelectric coefficients ($d_{33}$). The results indicate that doping with specific RE elements significantly impacts $T_\textrm{N}$, with optimal doping levels identified for enhanced performance. Furthermore, high-entropy RECrO$_3$ compounds were systematically analyzed, demonstrating how the inclusion of multiple RE elements influences magnetic properties. This work establishes a robust framework for predicting and optimizing the properties of RECrO$_3$ materials, offering valuable insights into their potential applications in energy storage and sensor technologies.

cond-mat.mtrl-sci↗

arXiv2025

Integrating Machine Learning with Triboelectric Nanogenerators: Optimizing Electrode Materials and Doping Strategies for Intelligent Energy Harves

The integration of machine learning techniques with triboelectric nanogenerators (TENGs) offers a transformative pathway for optimizing energy harvesting technologies. In this study, we propose a comprehensive framework that utilizes graph neural networks to predict and enhance the performance of TENG electrode materials and doping strategies. By leveraging an extensive dataset of experimental and computational results, the model effectively classifies electrode materials, predicts optimal doping ratios, and establishes robust structure-property relationships. Key findings include a 65.7% increase in energy density for aluminum-doped PTFE and an 85.7% improvement for fluorine-doped PTFE, highlighting the critical influence of doping materials and their concentrations. The model further identifies PTFE as a highly effective negative electrode material, achieving a maximum energy density of 1.12 J/cm$^2$ with 7% silver (Ag) doping when copper (Cu) is used as the positive electrode. This data-driven approach not only accelerates material discovery but also significantly reduces experimental costs, providing novel insights into the fundamental factors influencing TENG performance. The proposed methodology establishes a robust platform for intelligent material design, advancing the development of sustainable energy technologies and self-powered systems.

cond-mat.mtrl-sci↗

arXiv2025

Insights into dendritic growth mechanisms in batteries: A combined machine learning and computational study

In recent years, researchers have increasingly sought batteries as an efficient and cost-effective solution for energy storage and supply, owing to their high energy density, low cost, and environmental resilience. However, the issue of dendrite growth has emerged as a significant obstacle in battery development. Excessive dendrite growth during charging and discharging processes can lead to battery short-circuiting, degradation of electrochemical performance, reduced cycle life, and abnormal exothermic events. Consequently, understanding the dendrite growth process has become a key challenge for researchers. In this study, we investigated dendrite growth mechanisms in batteries using a combined machine learning approach, specifically a two-dimensional artificial convolutional neural network (CNN) model, along with computational methods. We developed two distinct computer models to predict dendrite growth in batteries. The CNN-1 model employs standard convolutional neural network techniques for dendritic growth prediction, while CNN-2 integrates additional physical parameters to enhance model robustness. Our results demonstrate that CNN-2 significantly enhances prediction accuracy, offering deeper insights into the impact of physical factors on dendritic growth. This improved model effectively captures the dynamic nature of dendrite formation, exhibiting high accuracy and sensitivity. These findings contribute to the advancement of safer and more reliable energy storage systems.

physics.comp-ph↗

arXiv2024

Ultrasonic-assisted liquid phase exfoliation for high-yield monolayer graphene with enhanced crystallinity

Graphene stands as a promising material with vast potential across energy storage, electronics, etc. Here, we present a novel mechanical approach utilizing ultrasonic high-energy intercalation exfoliation to extract monolayer graphene from graphite, offering a simple yet efficient alternative to conventional methods. Through a comprehensive series of characterizations involving atomic force microscopy, scanning electron microscopy, Raman spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy, the resulting graphene nanosheets demonstrate superior crystallinity compared to those obtained via the conventional method. The high-crystalline freestanding graphene nanosheets derived from this method not only facilitate easier separation but also significantly enhance the physical performance of the original materials. This method showcases the potential for scalable production of layered materials with increased yield and crystallinity, paving the way for their utilization in various applications.

cond-mat.mtrl-sci↗

arXiv2024

Unraveling the magnetic and electronic complexity of intermetallic ErPd$_2$Si$_2$: Anisotropic thermal expansion, phase transitions, and twofold magnetotransport behavior

We present a comprehensive investigation into the physical properties of intermetallic ErPd$_2$Si$_2$, a compound renowned for its intriguing magnetic and electronic characteristics. We confirm the tetragonal crystal structure of ErPd$_2$Si$_2$ within the $I4/mmm$ space group. Notably, we observed anisotropic thermal expansion, with the lattice constant $a$ expanding and $c$ contracting between 15 K and 300 K. This behavior is attributed to lattice vibrations and electronic contributions. Heat capacity measurements revealed three distinct temperature regimes: $T_1 \sim 3.0$ K, $T_\textrm{N} \sim 4.20$ K, and $T_2 \sim 15.31$ K. These correspond to the disappearance of spin-density waves, the onset of an incommensurate antiferromagnetic (AFM) structure, and the crystal-field splitting and/or the presence of short-range spin fluctuations, respectively. Remarkably, the AFM phase transition anomaly was observed exclusively in low-field magnetization data (120 Oe) at $T_\textrm{N}$. A high magnetic field ($B =$ 3 T) effectively suppressed this anomaly, likely due to spin-flop and spin-flip transitions. Furthermore, the extracted effective PM moments closely matched the expected theoretical value, suggesting a dominant magnetic contribution from localized 4$f$ spins of Er. Additionally, significant differences in resistance ($R$) values at low temperatures under applied $B$ indicated a magnetoresistance (MR) effect with a minimum value of -4.36\%. Notably, the measured MR effect exhibited anisotropic behavior, where changes in the strength or direction of the applied $B$ induced variations in the MR effect. A twofold symmetry of $R$ was discerned at 3 T and 9 T, originating from the orientation of spin moments relative to the applied $B$. Intriguingly, above $T_\textrm{N}$, short-range spin fluctuations also displayed a preferred orientation along the $c$-axis due to single-ion anisotropy.

cond-mat.str-el↗

arXiv2024

Investigating Material Interface Diffusion Phenomena through Graph Neural Networks in Applied Materials

Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, and catalysis. In this study, we propose a novel approach utilizing Graph Neural Networks (GNNs) to investigate and model material interface diffusion. We begin by collecting experimental and simulated data on diffusion coefficients, concentration gradients, and other relevant parameters from diverse material systems. The data are preprocessed, and key features influencing interface diffusion are extracted. Subsequently, we construct a GNN model tailored to the diffusion problem, with a graph representation capturing the atomic structure of materials. The model architecture includes multiple graph convolutional layers for feature aggregation and update, as well as optional graph attention layers to capture complex relationships between atoms. We train and validate the GNN model using the preprocessed data, achieving accurate predictions of diffusion coefficients, diffusion rates, concentration profiles, and potential diffusion pathways. Our approach offers insights into the underlying mechanisms of interface diffusion and provides a valuable tool for optimizing material design and engineering. Additionally, our method offers possible strategies to solve the longstanding problems related to materials interface diffusion.

cond-mat.mtrl-sci↗

arXiv2024

Deep learning-driven evaluation and prediction of ion-doped NASICON materials for enhanced solid-state battery performance

We developed a convolutional neural network (CNN) model capable of predicting the performance of various ion-doped NASICON compounds by leveraging extensive datasets from prior experimental investigation.The model demonstrated high accuracy and efficiency in predicting ionic conductivity and electrochemical properties. Key findings include the successful synthesis and validation of three NASICON materials predicted by the model, with experimental results closely matching the model predictions. This research not only enhances the understanding of ion-doping effects in NASICON materials but also establishes a robust framework for material design and practical applications. It bridges the gap between theoretical predictions and experimental validations.

cond-mat.mtrl-sci↗

arXiv2024

Predicting doping strategies for ternary nickel-cobalt-manganese cathode materials to enhance battery performance using graph neural networks

The exceptional electrochemical performance of lithium-ion batteries has spurred considerable interest in advanced battery technologies, particularly those utilizing ternary nickel-cobalt-manganese (NCM) cathode materials, which are renowned for their robust electrochemical performance and structural stability. Building upon this research, investigators have explored doping additional elements into NCM cathode materials to further enhance their electrochemical performance and structural integrity. However, the multitude of doping strategies available for NCM battery systems presents a challenge in determining the most effective approach. In this study, we elucidate the potential of ternary NCM systems as cathode materials for lithium-ion batteries. We compile a comprehensive database of lithium-ion batteries employing NCM systems from various sources of prior research and develop a corresponding data-driven model utilizing graph neural networks to predict optimal doping strategies. Our aim is to provide insights into the NCM-based battery systems for both fundamental understanding and practical applications.

cond-mat.mtrl-sci↗

arXiv2024

High-performance magnesium/sodium hybrid ion battery based on sodium vanadate oxide for reversible storage of Na+ and Mg2+

Magnesium ion batteries (MIBs) are a potential field for the energy storage of the future but are restricted by insufficient rate capability and rapid capacity degradation. Magnesium-sodium hybrid ion batteries (MSHBs) are an effective way to address these problems. Here, we report a new type of MSHBs that use layered sodium vanadate ((Na, Mn)V8O20 5H2O, Mn-NVO) cathodes coupled with an organic 3,4,9,10-perylenetetracarboxylic diimide (PTCDI) anode in Mg2+/Na+ hybrid electrolytes. During electrochemical cycling, Mg2+ and Na+ co-participate in the cathode reactions, and the introduction of Na+ promotes the structural stability of the Mn-NVO cathode, as cleared by several ex-situ characterizations. Consequently, the Mn-NVO cathode presents great specific capacity (249.9 mAh g-1 at 300 mA g-1) and cycling (1500 cycles at 1500 mA g-1) in the Mg2+/Na+ hybrid electrolytes. Besides, full battery displays long lifespan with 10,000 cycles at 1000 mA g-1. The rate performance and cycling stability of MSHBs have been improved by an economical and scalable method, and the mechanism for these improvements was discussed.

cond-mat.mtrl-sci↗

arXiv2024

Crystal, ferromagnetism, and magnetoresistance with sign reversal in a EuAgP semiconductor

We synthesized the ferromagnetic EuAgP semiconductor and conducted a comprehensive study of its crystalline, magnetic, heat capacity, band gap, and magnetoresistance properties. Our investigation utilized a combination of X-ray diffraction, optical, and PPMS DynaCool measurements. EuAgP adopts a hexagonal structure with the $P6_3/mmc$ space group. As the temperature decreases, it undergoes a magnetic phase transition from high-temperature paramagnetism to low-temperature ferromagnetism. We determined the ferromagnetic transition temperature to be $T_{\textrm{C}} =$ 16.45(1) K by fitting the measured magnetic susceptibility using a Curie-Weiss law. Heat capacity analysis of EuAgP considered contributions from electrons, phonons, and magnons, revealing $η$ = 0.03 J/mol/$\textrm{K}^\textrm{2}$, indicative of semiconducting behavior. Additionally, we calculated a band gap of $\sim$ 1.324(4) eV based on absorption spectrum measurements. The resistivity versus temperature of EuAgP measured in the absence of an applied magnetic field shows a pronounced peak around $T_{\textrm{C}}$, which diminishes rapidly with increasing applied magnetic fields, ranging from 1 to 14 T. An intriguing phenomenon emerges in the form of a distinct magnetoresistance transition, shifting from positive (e.g., 1.95\% at 300 K and 14 T) to negative (e.g., -30.73\% at 14.25 K and 14 T) as the temperature decreases. This behavior could be attributed to spin-disordered scattering.

cond-mat.str-el↗

arXiv2024

A new ferromagnetic semiconductor system of Eu$_{1-x}$Sr$_x$AgP $(x = 0.0-0.6)$ compounds: Crystallographic, magnetic, and magneto-resistive properties

Adjusting chemical pressure through doping is a highly effective method for customizing the chemical and physical properties of materials, along with their respective phase diagrams, thereby uncovering novel quantum phenomena. Here, we successfully synthesized Sr-doped Eu$_{1-x}$Sr$_x$AgP $(x = 0.0-0.6)$ and conducted a comprehensive investigation involving crystallography, magnetization, heat capacity, and magnetoresistance. Utilizing X-ray diffraction and PPMS DynaCool measurements, we studied Eu$_{1-x}$Sr$_x$AgP in detail. The hexagonal structure of parent EuAgP at room temperature, with the $P6_3/mmc$ space group, remains unaltered, while the lattice constants expand. The magnetic phase transition from paramagnetism to ferromagnetism, as temperature decreases, is suppressed through the gradual introduction of strontium doping. Heat capacity measurements reveal a shift from magnon-dominated to predominantly phonon and electron contributions near the ferromagnetic phase with increasing doping levels. The resistivity-temperature relationship displays distinct characteristics, emphasizing the impact of Sr doping on modifying charge transport. Magnetoresistance measurements uncover novel phenomena, illustrating the adjustability of magnetoresistance through Sr doping. Notably, Sr doping results in both positive magnetoresistance (up to 20\%) and negative magnetoresistance (approximately -60\%). The resistivity and magnetic phase diagram were established for the first time, revealing the pronounced feasibility of Sr doping in modulating EuAgP's resistivity. This study has provided valuable insights into the intricate interplay between structural modifications and diverse physical properties. The potential for technological advancements and the exploration of novel quantum states make Sr-doped Eu$_{1-x}$Sr$_x$AgP a compelling subject for continued research in the field of applied physics.

cond-mat.mtrl-sci↗

arXiv2024

Zincophilic armor: Phytate ammonium as a multifunctional additive for enhanced performance in aqueous zinc-ion batteries

Corrosion and the formation of by-products resulting from parasitic side reactions, as well as random dendrite growth, pose significant challenges for aqueous zinc-ion batteries (AZIBs). In this study, phytate ammonium is introduced into the traditional dilute Zinc sulfate electrolyte as a multi-functional additive. Leveraging the inherent zincophilic nature of the phytic anion, a protective layer is formed on the surface of the zinc anode. This layer can effectively manipulate the deposition process, mitigate parasitic reactions, and reduce the accumulation of detrimental by-products. Additionally, the competitive deposition between dissociated ammonium ions and Zn2+ promotes uniform deposition, thereby alleviating dendrite growth. Consequently, the modified electrolyte with a lower volume addition exhibits superior performance. The zinc symmetric battery demonstrates much more reversible plating/stripping, sustaining over 2000 hours at 5 mA cm-2 and 1 mA h cm-2. A high average deposition/stripping efficiency of 99.83% is achieved, indicating the significant boosting effect and practical potential of our strategy for high-performance aqueous zinc-ion batteries.

physics.app-ph↗

arXiv2024

Structure and magnetic properties of a La$_{0.75}$Sr$_{0.25}$Cr$_{0.90}$O$_{3-δ}$ single crystal

We have successfully grown large and good-quality single crystals of the La$_{0.75}$Sr$_{0.25}$Cr$_{0.90}$O$_{3-δ}$ compound using the floating-zone method with laser diodes. We investigated the crystal quality, crystallography, chemical composition, magnetic properties and the oxidation state of Cr in the grown single crystals by employing a combination of techniques, including X-ray Laue and powder diffraction, scanning electron microscopy, magnetization measurements, X-ray photoelectron spectroscopy and light absorption. The La$_{0.75}$Sr$_{0.25}$Cr$_{0.90}$O$_{3-δ}$ single crystal exhibits a single-phase composition, crystallizing in a trigonal structure with the space group $R\bar{3}c$ at room temperature. The chemical composition was determined as La$_{0.75}$Sr$_{0.25}$Cr$_{0.90}$O$_{3-δ}$, indicating a significant chromium deficiency. Upon warming, we observed five distinctive characteristic temperatures, namely $T_1 =$ 21.50(1) K, $T_2 =$ 34.98(1) K, $T_3 =$ 117.94(1) K, $T_4 =$ 155.01(1) K, and $T_{\textrm{N}} =$ 271.80(1) K, revealing five distinct magnetic anomalies. Our magnetization study allows us to explore the nature of these anomalies. Remarkably, the oxidation state of chromium in the single-crystal La$_{0.75}$Sr$_{0.25}$Cr$_{0.90}$O$_{3-δ}$, characterized by a band gap of 1.630(8) eV, is exclusively attributed to Cr$^{3+}$ ions, making a departure from the findings of previous studies on polycrystalline materials.

cond-mat.mtrl-sci↗

arXiv2023

MgF$_2$ as an effective additive for improving ionic conductivity of ceramic solid electrolytes

As typical solid-state electrolytes (SSEs), {Na}$_{1+x}${Zr}$_2${Si}$_{x}${P}$_{3-x}${O}$_{12}$ NASICONs provide an ideal platform for solid-state batteries (SSBs) that display higher safety and accommodate higher energy densities. The critical points for achieving SSBs with higher efficiencies are to improve essentially the ionic conductivity and to reduce largely the interfacial resistance between SSEs and cathode materials, which would necessitate extremely high level of craftsmanship and high-pressure equipment. An alternative to higher-performance and lower-cost SSBs is additive manufacturing. Here, we report on an effective additive, MgF$_2$, which was used in synthesizing NASICONs, resulting in SSEs with fewer defects and higher performance. With an addition of mere 1 wt$\%$ MgF$_2$ additive, the total room-temperature ionic conductivity of the NASICON electrolyte reaches up to 2.03 mS cm$^{-1}$, improved up to $\sim$ 181.3$\%$, with an activation energy of 0.277 eV. Meanwhile, the stability of the Na plating/stripping behavior in symmetric cells increases from 236 to 654 h. We tried to reveal the microscopic origins of the higher ionic conductivity of MgF$_2$-doped NASICONs by comprehensive in-house characterizations. Our study discovers a novel MgF$_2$ additive and provides an efficient way to prepare higher-performance SSEs, making it possible to fabricate lower-cost SSBs in industries.

physics.app-ph↗

arXiv2022

A comprehensive review on the ferroelectric orthochromates: Synthesis, property, and application

Multiferroics represent a class of advanced materials for promising applications and stand at the forefront of modern science for the special feature possessing both charge polar and magnetic order. Previous studies indicate that the family of RECrO3 (RE = rare earth) compounds is likely another rare candidate system holding both ferroelectricity and magnetism. However, many issues remain unsolved, casting hot disputes about whether RECrO3 is multiferroic or not. For example, an incompatibility exists between reported structural models and observed ferroelectric behaviors, and it is not easy to determine the spin canting degree. To address these questions, one key step is to grow single crystals because they can provide more reliable information than other forms of matter do. In this review, the parent and doped ferroelectric YCrO3 compounds are comprehensively reviewed based on scientific and patent literatures from 1954 to 2022. The materials syntheses with different methods, including poly-, nano-, and single-crystalline samples and thin films, are summarized. The structural, magnetic, ferroelectric and dielectric, optical, and chemical-pressure (on Y and Cr sites by doping) dependent chemical and physical properties and the corresponding phase diagrams, are discussed. Diverse (potential) applications, including anti-corrosion, magnetohydrodynamic electrode, catalyst, negative-temperature-coefficient thermistor, magnetic refrigeration, protective coating, and solid oxide fuel cell, are present. To conclude, we summarize general results, reached consensuses, and existing controversies of the past nearly 69 years of intensive studies and highlight future research opportunities and emerging challenges to address existing issues.

cond-mat.mtrl-sci↗