Complex Surface Research Articles

Effect of pyrolytic temperature on the adsorption of Pb(II) from synthetic wastewater onto bamboo chopstick biochar: a conventional vs. microwave-assisted pyrolysis approach

This study investigated the effects of different pyrolytic temperatures on Pb(II) adsorption from synthetic wastewater using waste bamboo chopsticks (BCs) produced via conventional and microwave-assisted pyrolysis. Eleven biochars were prepared and characterized using Brunauer‒Emmett‒Teller analysis, elemental analysis, scanning electron microscopy, and Fourier transform infrared spectroscopy. Thereafter, the selected biochars were further analyzed through batch adsorption studies. The influence of adsorbent dose, initial Pb(II) concentration, and contact time on the removal of Pb(II) from synthetic wastewater was studied. For the adsorbent dose, good removal efficiencies and adsorption capacities were observed at an adsorbent dose of 2 g L−1 and at an initial concentration of 50 mg L−1. For the initial Pb(II) concentration, high adsorption capacities and removal efficiencies were observed at 50 mg L−1 for concentrations ranging from 5 to 100 mg L−1. The contact time reached equilibrium within 24 h, where BC 450 W had the highest removal efficiency of 99.9%. Furthermore, the Langmuir isotherm model best represented the adsorption of Pb(II) onto biochar, with the highest qm of 81 mg g−1 at R2 = 0.978. Pseudo-second-order kinetics provided the best overall fit for the adsorption kinetics of the biochars, with R2 = 1.00 for BC 450 W and BC 700 °C. Among the many chemisorption processes identified in previous studies, surface complexation has been identified as a possible adsorption mechanism for Pb(II) on the biochars produced. BC biochar could be a sustainable means for remediating polluted mine water and managing waste.

Failure Modes and Fault Morphology

Abstract Fault failure modes determine the geometric characteristics of faults and fault zones during their formation and early development. These geometric properties, in turn, govern a wide range of fault processes and behaviors, such as reactivation potential, fault propagation, and growth, and the hydraulic properties of faults and fault zones. Here, we use field data and close-range digital photogrammetry to characterize, in detail, the surface morphology of three normal faults with cm-scale displacements in mechanically layered carbonates of the Cretaceous Glen Rose Formation at Canyon Lake Gorge, Comal County, Texas. Analyses demonstrate complex fault surface geometries, a broad spectrum of slip tendency (Ts) and dilation tendency (Td), and variable failure behavior. We show that (i) fault patches coated with coarse calcite cement tend to have moderate to high dips, low to high Ts, and high to very high Td; (ii) slickensided fault patches exhibit low to moderate dips, moderate to very high Ts, and moderate to high Td; and (iii) slickolite patches exhibit low dips, moderate Ts, and low to moderate Td. Calcite-coated patches are interpreted to record hybrid extension-shear failure, whereas slickensided and slickolite patches record shear and compactional shear failure, respectively. Substantial variability in both Ts and Td across the exposed fault surfaces reflects complex fault morphology that is not easily measured using traditional field techniques but is captured by our photogrammetry data. We document complex fault geometries, with kinematic (displacement) compatibility indicating the various failure modes were active coevally during fault slip. This finding is in direct contrast with the often-assumed concept of faults forming by shear failure on surfaces oriented 30° to σ1. Distinct failure behaviors are consistent with patchworks of volume neutral, volume gain, and volume loss zones along the fault surfaces, indicating that the characterized faults likely represent dual conduit-seal systems for fluid flow.

Synaptic Gα12/13 signaling establishes hippocampal PV inhibitory circuits

Combinatorial networks of cell adhesion molecules and cell surface receptors drive fundamental aspects of neural circuit establishment and function. However, the intracellular signals orchestrated by these cell surface complexes remain less understood. Here, we report that the Gα12/13 pathway lies downstream of several GPCRs with critical synaptic functions. Impairment of the Gα12/13 pathway in postnatal hippocampal neurons diminishes inhibitory inputs without altering neuronal morphology or excitatory transmission. Gα12/13 signaling in hippocampal CA1 neurons in vivo selectively regulates PV interneuron synaptic connectivity, supporting an inhibitory synapse subtype-specific function of this pathway. Our studies establish Gα12/13 as a signaling node that shapes inhibitory hippocampal circuitry.

Estimation of full-coverage surface ozone using sentinel-5P data and a GAN-LGBM model in the YRDUA, China

ABSTRACT Recent years have seen increasing academic attention to surface ozone pollution due to its significant impacts on air quality and human health. To overcome the spatial coverage limitation of surface ozone ground monitoring, we proposed a novel approach that integrated the Generative Adversarial Network (GAN) with the Light Gradient Boosting Machine (LGBM) for full-coverage surface ozone estimation in the Yangtze River Delta Urban Agglomeration (YRDUA), using ground monitoring data and Sentinel-5P satellite data. We assessed the performance of the GAN-LGBM model against other decision-tree-based models (XGBoost, LGBM) using three cross-validation (CV) methods: sample-based, space-based, and time-based. The results demonstrated that the GAN-LGBM model consistently outperformed other models across all evaluation metrics and validation scenarios, achieving the highest correlation coefficient (R 2) of 0.94 in sample-based CV. Spatiotemporal evaluations further showed the robustness of the GAN-LGBM model and its ability to capture complex surface ozone concentration patterns. This study introduces a promising method for full-coverage surface ozone estimation and explores the potential of incorporating unsupervised learning methods into regression models to address complex correlations in environmental datasets.

Bridging the Gap between Molecular Simulations and Surface Complexation Modeling for Heterogeneous Surfaces: A Case Study with Uranium and Arsenic Adsorption on Clay Minerals.

Among all natural submicrosized phases, clay minerals are ubiquitous in soils and sedimentary rocks in nature as well as in engineered environments, and while clay minerals' adsorption properties have been studied extensively, their unique level of surface reactivity heterogeneities necessitates further investigation at the molecular level to understand and predict the influence of these heterogeneities on their macroscopic properties. In this study, we investigated the surface structures and desorption-free energies of U(VI) species (UO22+) and As(V) species (H2AsO4- and HAsO42-) complexed at different edge surface reactive sites of a cis-vacant montmorillonite layer using first-principles molecular dynamics (FPMD). We show that U(VI) forms bidentate and tridentate complexes on montmorillonite edge surfaces, whereas As(V) monodentate complexes are the most stable. Then, we constrained a state-of-the-art surface complexation model (SCM) with surface acid-base chemistry and surface complexation properties obtained from the molecular-level simulation results. While our results highlighted the complexity of the interfacial chemistry controlling the complexation of inorganic contaminants on clay mineral surfaces, they also evidenced the reliability of an integrated workflow using modern multiscale simulation techniques to address the challenge of predicting heterogeneities in mineral surface reactivity.

Advancing cellular transfer printing: achieving bioadhesion-free deposition via vibration microstreaming.

Cell transfer printing plays an essential role in biomedical research and clinical diagnostics. Traditional bioadhesion-based methods often necessitate complex surface modifications and offer limited control over the quantity of transferred cells. There is a critical need for a modification-free, non-labeling, and high-throughput cell transfer printing technique. In this study, an adhesion-free cellular transfer printing method based on vibration-induced microstreaming is introduced. By adjusting the volume of the microcavity, the number of cells transferred per microtiter well can be realized to the level of a single cell. Additionally, it allows for precise control of large-scale cellular spatial distribution, leading to the formation of biomimetic patterns. Moreover, the demonstrated biocompatibility and high throughput of this cell transfer printing method highlight its potential utility. The correspondence of the transferred cell amount to the vibration and frequencies allows the system to exhibit excellent tunability of the transferred cell amount and pattern. This bioadhesion-free cell transfer printing method holds promise for advancing cell manipulation in biomedical research and analysis.

Travel time calculation of seismic waves on complex surfaces using the group marching method

Travel time calculation of seismic waves on complex surfaces using the group marching method

On compact complex surfaces with finite homotopy rank-sum

A topological space (not necessarily simply connected) is said to have finite homotopy rank-sum if the sum of the ranks of all higher homotopy groups (from the second homotopy group onward) is finite. In this article, we characterize the smooth compact complex Kähler surfaces having finite homotopy rank-sum. We also prove the Steinness of the universal cover of these surfaces assuming holomorphic convexity of the universal cover.

Artificial Intelligence-Based Feature Analysis of Pulmonary Vein Morphology on Computed Tomography Scans and Risk of Atrial Fibrillation Recurrence After Catheter Ablation: A Multi-Site Study.

Atrial fibrillation (AF) recurrence (AF+) is common after catheter ablation. Pulmonary vein (PV) isolation is the cornerstone of AF ablation, but PV remodeling has been associated with the risk of AF+. We aimed to evaluate whether artificial intelligence-based morphological features of primary and secondary PV branches on computed tomography images are associated with AF+ post-ablation. Two artificial intelligence models were trained for the segmentation of computed tomography images, enabling the isolation of PV branches. Patients from Cleveland Clinic (n=135) and Vanderbilt University (n=594) were combined and divided into 2 sets for training and cross-validation (D1, n=218) and internal testing (D2, n=511). An independent validation set (D3, n=80) was obtained from University Hospitals of Cleveland. We extracted 48 fractal-based and 12 shape-based radiomic features from primary and secondary PV branches of patients with AF+ and without recurrence after catheter ablation of AF. To predict AF+, 3 Gradient Boosting classification models based on significant features from primary branch PV model (Mp), secondary branch PV model (Ms), and combined primary and secondary branch PV model (Mc) were built. Features relating to primary PVs were found to be associated with AF+. The Mp classifier achieved area under the curve values of 0.73, 0.71, and 0.70 across the 3 datasets. AF+ cases exhibited greater surface complexity in their primary PV area, as evidenced by higher fractal dimension values compared with AF nonrecurrence cases. The Ms classifier results revealed a weaker association with AF+, suggesting higher relevance to AF+ post-ablation from primary PV branch morphology. This largest multi-institutional study to date revealed associations between artificial intelligence-extracted morphological features of the primary PV branches with AF+ in 809 patients from 3 sites. Future work will focus on enhancing the predictive ability of the classifier by integrating clinical, structural, and morphological features, including left atrial appendage and left atrium-related characteristics.

Phosphoric acid-modified bentonite-chitosan composite beads: a novel and cost-effective adsorbent for multi-metal wastewater treatment.

This study introduces a novel, cost-effective adsorbent made from phosphoric acid-modified bentonite-chitosan composite beads, designed to remove Cu2⁺, Ni2⁺, and Zn2⁺ from aqueous solutions. Characterization of the composite revealed a mesoporous structure and the presence of functional groups that enhance its adsorption properties. Using response surface methodology, the adsorption capacities were determined as 362.24mg/g for Cu2⁺, 279.51mg/g for Ni2⁺, and 210.54mg/g for Zn2⁺ under optimal conditions. A pH study further improved the adsorption capacities to 381.29mg/g for Cu2⁺, 305.98mg/g for Ni2⁺, and 225.04mg/g for Zn2⁺. The adsorption process followed pseudo-second-order kinetics and was best described by the Langmuir isotherm model, suggesting that the adsorption occurred on a single layer of the adsorbent surface via chemical bonds. In competitive adsorption scenarios, Cu2⁺ was removed more efficiently than Zn2⁺ and Ni2⁺. The removal efficiencies achieved were 88.59% for Cu2⁺, 72.30% for Ni2⁺, and 62.07% for Zn2⁺ using 1g/l adsorbent within 30min for treating industrial effluent. Thermodynamic analysis confirmed that the adsorption process was spontaneous and endothermic. The adsorbent maintained good performance over 10 regeneration cycles, demonstrating its reusability. The primary adsorption mechanisms include electrostatic attraction, surface complexation, and ion exchange. The developed adsorbent proved to be an efficient, sustainable, and environmentally friendly solution for removing heavy metals from wastewater. This cost-effective material can be readily implemented in industrial wastewater treatment plants to tackle heavy metal contamination.

Micro-scale modeling and analysis on material removal mechanisms for flexible ball-end tool polishing incorporating the curvature effect

Optical freeform surfaces (OFS) have been extensively employed as core components in advanced optical systems for their excellent performances. However, the surface complexity and the high surface accuracy do impose challenges to the processing of OFS, especially the surface form maintaining or control during polishing. As one of the promising ultra-precision machining technologies to fabricate OFS, the flexible ball-end tool (FBET) polishing becomes available due to its attractive technical advantages. Nevertheless, there are still lack of more comprehensive insights on material removal mechanisms for FBET polishing incorporating the curvature effect, particularly from a microscopic scale, which is of great significance to determine the surface quality and form control in ultra-precision polishing process. In this paper, different from those published macro-scale Preston law-based models, a micro-scale material removal model is developed based on the mutual interaction of the slurry, polishing pad and curved workpiece among the FBET polishing interfaces with micro-contact theory and tribology theory, wherein various parameters embodied in FBET polishing are formulated quantitatively, such as slurry characteristics, pad properties, tool features, processing conditions, as well as workpiece curvature effect. The FBET is designed and adopted to conduct the spot polishing experiments within the concave curvature radius range from 75 mm to 225 mm, wherein the curvature radius range from 225 mm to 800 mm is theoretically chosen as an extension of this research. The predicted results agree well with the experimentally measured section profiles of polishing spots, thereby demonstrating the correctness and effectiveness of the proposed model. Furthermore, the effective relative velocity U together with the separation gap d between reference plane and workpiece surface are known as the two key parameters to account for the material removal mechanisms, and the latter is figured out to be the sensitive one to the curvature effect rather than the former. Through the analysis of key parameters, the established model is capable of helping to strengthen the understanding of material removal mechanisms for FBET polishing with the consideration of curvature effect, addressing those cannot be interpreted by the classical Preston equation previously, which is meaningful for precision control of material removal during polishing of OFS.

An improved goal-oriented adaptive finite-element method for 3-D direct current resistivity anisotropic forward modeling using nested tetrahedra

We developed a novel adaptive finite element method (FEM) to address the problem of 3-D direct current (DC) resistivity forward modeling with complex surface topography and arbitrary conductivity anisotropy. The tetrahedra-based FEM and secondary virtual potential algorithm are first used to handle arbitrary complex geo-models. Then, to ensure the accuracy of the simulation solution, an improved goal-oriented adaptive mesh refinement (AMR) algorithm is proposed to realize an optimized mesh density distribution. To avoid the drawback of the traditional goal-oriented AMR algorithm for the DC forward modeling problem, we incorporate a volume-based weighting factor into the posterior error estimation procedure to further optimize the density distribution of the forward modeling grid. In addition, instead of traditional open source mesh generation software, we propose using the longest-edge bisection (LEB) algorithm to perform the mesh refinement process, which can preserve the topological structure between different-level meshes. Finally, the comprehensive test using a two-layered model and two complex 3-D models demonstrate the capability of our newly developed code to obtain highly accurate solutions even on relatively coarse initial grids. By incorporating the volume factor, our novel AMR algorithm achieves a more uniform and reasonable mesh density distribution during these experiments. The LEB refinement technique can generate a series of nested tetrahedral elements and provide fewer tetrahedral elements compared to the traditional Delaunay-based AMR method. The proposed 3-D DC forward modeling method has been implemented into an open source C++ code, which will contribute to the advancement of the 3-D DC resistivity imaging field.

A slime-inspired phycocyanin/κ-carrageenan-based hydrogel bandage with ultra-stretchability, self-healing, antioxidative, and antibacterial activity for wound healing.

Hydrogels have attracted extensive attention as wound dressing owing to their excellent multifunctionality, flexibility, and biocompatibility. Due to the frequent movement and stretching of skin as well as complex surface of wound, traditional wound dressings have difficulty to adapt to motion and irregular wounds. Furthermore, excessive reactive oxygen species (ROS) and bacterial infection can induce delayed wound healing. To this end, we developed a set of versatile phycocyanin-based dual network hydrogels (PPC hydrogels) with polyvinyl alcohol (PVA) and κ-carrageenan (CRG) as substrate via forming of borate ester bonds, hydrogen bonds, and electrostatic interaction. The PPC hydrogels not only possessed adaptivity, ultra-stretchability (7036.12 %), efficient self-healing and injectability, but also possessed antioxidative and antibacterial capacities conferred by C-phycocyanin (PC) and rhein. Moreover, the hydrogels also exhibited excellent hemostatic ability and high biocompatibility. More remarkably, the PPC-I hydrogel could accelerate wound healing by effect of anti-inflammation (downregulating TNF-α and IL-6) and promoting collagen deposition and angiogenesis (upregulating CD31), which may be utilized as hydrogel bandages and applied to motion and irregular wounds, thereby promising the application prospect of the hydrogels as wound dressing.

Biomass‐Derived Phosphorus‐Doped Porous Hard Carbon Anode for Stable and High‐Rate Sodium Ion Batteries

Biomass‐derived hard carbon, despite being promising for anode material of sodium‐ion batteries, usually suffer from low initial coulombic efficiency (ICE), poor rate capacity, and limited cycling stability caused by complex surface defects and low intrinsic conductivity. Herein, phosphorus‐doped porous hard carbon (HC@PC‐P) were synthesized by the thermal polymerization of soy lecithin on the surfaces of hard carbon derived from olive kernels. The incorporation of heteroatom phosphorus in the porous hard carbon framework expands the carbon lattice spacing, optimizes the graphitization degree, and increases electrical conductivity, guaranteeing ensuring rapid electron and ion transfer. These coupling effects enable HC@PC‐P anode to achieve a high reversible capacity of 350 mAh g‐1 at 0.1 A g‐1, an impressive initial coulombic efficiency of 89.6%, and remarkable long‐term cycling stability at 1 A g‐1 over 1000 cycles with negligible capacity fade. The mechanisms behind sodium storage and enhanced electrochemical performance were elucidated by ex‐situ Raman spectroscopy and kinetic analysis. Additionally, the assembled HC@PC‐P//Na3V2(PO4)3 full cell demonstrated a high energy density of 257.9 Wh kg‐1. This work provides a rational guide for designing advanced hard carbon anode materials for high‐energy sodium‐ion batteries.

Surface Reconstruction From Point Clouds: A Survey and a Benchmark.

Reconstruction of a continuous surface of two-dimensional manifold from its raw, discrete point cloud observation is a long-standing problem in computer vision and graphics research. The problem is technically ill-posed, and becomes more difficult considering that various sensing imperfections would appear in the point clouds obtained by practical depth scanning. In literature, a rich set of methods has been proposed, and reviews of existing methods are also provided. However, existing reviews are short of thorough investigations on a common benchmark. The present paper aims to review and benchmark existing methods in the new era of deep learning surface reconstruction. To this end, we contribute a large-scale benchmarking dataset consisting of both synthetic and real-scanned data; the benchmark includes object- and scene-level surfaces and takes into account various sensing imperfections that are commonly encountered in practical depth scanning. We conduct thorough empirical studies by comparing existing methods on the constructed benchmark, and pay special attention on robustness of existing methods against various scanning imperfections; we also study how different methods generalize in terms of reconstructing complex surface shapes. Our studies help identity the best conditions under which different methods work, and suggest some empirical findings. For example, while deep learning methods are increasingly popular in the research community, our systematic studies suggest that, surprisingly, a few classical methods perform even better in terms of both robustness and generalization; our studies also suggest that the practical challenges of misalignment of point sets from multi-view scanning, missing of surface points, and point outliers remain unsolved by all the existing surface reconstruction methods. We expect that the benchmark and our studies would be valuable both for practitioners and as a guidance for new innovations in future research.

Growth mechanism of Pb0.9Cd0.1Te: Pb thin films prepared by PVD technique

Abstract The complex surface morphology, defect subsystem and an ab initio model study of Pb1-xCdxTe thin films deposited on mica-muscovite substrates by PVD technology are presented in this paper. The thickness, growth mechanisms and uniformity of condensates dependence on deposition regimes were studied by scanning electron microscopy and energy-dispersive x-ray spectroscopy. The deposited films have a granular structure and sizes of crystallites depend on thickness and difference between substrate and condensate crystallographic parameters. The dominance of film growth by the Vollmer-Weber mechanism is demonstrate. Studies of film growth mechanisms allowed us to predict that the formation of grains and the dynamics of their size changes during film growth are caused by complex defects that are associated with Cd atoms in nodes and vacancies of chalcogens.

Characterization and performance of novel carbon-doped aluminum-modified bentonite for cost-effective fluoride removal

Elevated fluoride levels in water pose a critical global health issue, necessitating advanced remediation strategies. This study introduces a novel, cost-effective approach using clay minerals, specifically bentonite, enhanced with carbon-doped aluminum. The resulting composite, carbon-doped aluminum-bentonite (CCDAB), exhibits exceptional fluoride adsorption performance. Detailed structural analyses by SEM, FTIR, BET, and X-ray diffraction reveal successful carbon-doped aluminum integration, which markedly improves fluoride uptake. Adsorption kinetics adhere to pseudo-second-order models, signifying predominant chemical interactions, while the Langmuir isotherm model indicates monolayer coverage. CCDAB achieves a fluoride adsorption capacity of 85.51 mg/g and a removal efficiency of 95.3 %, demonstrating robust performance even in the presence of competing ions. Its efficacy over a broad pH range (3−7) is attributed to its high point of zero charge (pHpzc), which enhances electrostatic interactions. Carbon doping introduces additional active sites, synergistically enhancing fluoride removal alongside aluminum oxide. Thermodynamic analysis confirms that the process is both spontaneous and endothermic. The mechanisms of fluoride removal encompass electrostatic attraction, ion exchange, and surface complexation. This study highlights CCDAB’s promise as a highly effective and economical solution for fluoride contamination in water.

Hydrogen underground storage potential in sandstone formation: A thorough study utilizing surface complexation modelling

This research focuses on the geochemical aspects of hydrogen underground storage, with particular emphasis on surface complexation modelling and its impact on surface potential and surface charge. The primary objective is to develop the first comprehensive surface complexation model specifically tailored for sandstone rocks, emphasizing key minerals such as quartz, kaolinite, and calcite, which are suitable for hydrogen underground storage applications. This model is intended to serve as a benchmark for more research in this field, providing a solid foundation for investigating and improving predictions related to wettability alteration. Additionally, the model has been integrated with hydrogen solubility to accurately capture changes in surface charge. The study identified six brine compositions with various minerals to examine the effect of monovalent and divalent ions. The results showed an increase in solubility with an overall reduction in salinity, and a decrease in divalent ions. The homogeneous surface complexation model demonstrated a neutral surface potential, attributed to an increased mole fraction of positively charged >SiOH+and a decreased in negatively charged >SiO-. Similar trends were observed in kaolinite and calcite minerals. The influence of pH was also explored, revealing a significant impact on the homogeneous quartz case, where an increase in pH shifted the surface potential from neutral to more negative. The heterogeneous cases exhibited less negative behavior as the quartz content increased per case, mainly due the increasing presence of positively charged species such as >SiOH+ and >AlOH+, and the reduction of the negatively charged >AlO-. Increasing the salinity of the solution resulted in less negative surface potential, attributed to the abundance of positive divalent and monovalent ions boosted by increasing salinity, thus the formation of positive surface complexes.

Effects of particle size and aging on heavy metal adsorption by polypropylene and polystyrene microplastics under varying environmental conditions

Microplastics have become a major environmental issue because of their widespread presence and tendency to adsorb heavy metals, which can have harmful effects on aquatic ecosystems and human health. The present study investigates the adsorption mechanisms of Pb2+ and Cu2+ ions on both pristine and artificially aged microplastics (MPs) made of polystyrene (PS) and polypropylene (PP). Furthermore, the influence of MP size on the adsorption capacity under different environmental conditions was evaluated. According to the characterization of MPs, aging leads to physical damage and an increase in the number of oxygen-containing functional groups on their surface. The experimental results highlight the significantly higher adsorption ability of smaller and aged MPs compared with that of pristine MPs for both the heavy metal ions. The pseudo-second-order equation provided a better fit for the adsorption kinetics study (R2 = 0.95), suggesting that chemisorption governs the rate-limiting phase in the adsorption mechanism on the MP surfaces. The concordance between the adsorption isotherm model and Freundlich model (R2 > 0.95) indicated a predominance of multilayer adsorption. The environmental factors such as pH, humic acid, temperature, and SO42- concentration significantly affected the adsorption of Pb2⁺ and Cu2⁺ onto PP and PS MPs. These variables play a crucial role in determining the nature of the interactions between heavy metal ions and the microplastic particles under diverse environmental conditions. Electrostatic interactions, surface complexation and van der Waals forces were identified as two factors that could either improve or diminish the metal ion adsorption capacity of MPs.

A crawling robot with temperature-controlled variable stiffness feet: strong surface adaptability

Abstract Existing soft robots have not shown the same level of adaptability on diverse terrains when compared to natural animals that possess variable stiffness characteristics. In this paper, utilizing the mutual transformation between the glassy and molten states of rosin materials, temperature-controlled variable stiffness feet (TVSF) are achieved by filling the rosin into an array of soft cavity villi. A single motor is utilized as the vibration-driven actuator of the robot. It is found that the feet stiffness can be changed ranging from 0.6227 N/mm to 0.9611 N/mm, which has a significant impact on the robot’s velocity and follows a nonlinear relationship. A smooth motion surface requires a high-stiffness foot to provide support and stability for the robot, while a rough motion surface necessitates a low-stiffness foot to reduce friction and resistance allowing for quick movement for the driving voltage of 1.6 V. Furthermore, the TVSF enable stable operation on complex surfaces, including a 30°slope, pipes, and pothole surfaces. This research provides a new technological approach to designing and manufacturing variable stiffness robots with enhanced surface adaptability.