Crystal Structure Of Material Research Articles

Prediction of crystal structure, phase group, and stability of 2D materials through data science coupled with DFT

Two-dimensional materials offer unique mechanical strength, electrical conductivity, and tunable electronic properties, driving advancements in electronics, energy storage, and catalysis. The crystal structure of the materials is fundamental to several properties. In this study, we employ solely the elemental features to construct a random forest classification model achieving an 82.56% accuracy in predicting the crystal structure of the compounds. Additionally, one vs rest binary classifiers are developed for each crystal structure within our 2D materials dataset, with accuracies ranging from 86% to 99%, enhancing their practical utility. Features based on stoichiometric norms have been found to play a major role in the prediction because of the fact that certain crystal structures are associated with more balanced compositions, leading to lower norm values, while others with imbalances have higher norm values. It has also been observed that material compositions with an overall higher amount of p valence electrons tend to show monoclinic, orthorhombic and triclinic crystal structures. Moreover, in compounds with a lower total electronegativity of the constituent elements, the occurrence of trigonal and tetragonal systems has been found to be more probable. In a similar fashion, hexagonal crystal systems have been more often found in compounds where the sum of Van Der Waals radius of the constituent atoms is lower. To validate our model, Crystal structure AnaLYsis by Particle Swarm Optimization (CALYPSO) method, and Density Functional Theory (DFT) are utilized to predict the crystal structure, phase group, and stability of a 2D material.

Encoding CO2 Adsorption in Sodium Zirconate by Neutron Diffraction.

Recent research into sodium zirconate as a high-temperature CO2 sorbent has been extensive, but detailed knowledge of the material's crystal structure during synthesis and carbon dioxide uptake remains limited. This study employs neutron diffraction (ND), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) to explore these aspects. An improved synthesis method, involving the pre-drying and ball milling of raw materials, produced pure samples with average crystal sizes of 37-48 nm in the monoclinic phase. However, using a slower heating rate (1 °C/min) decreased the purity. Despite this, the 1 °C/min rate resulted in the highest CO2 uptake capacity (4.32 mmol CO2/g Na2ZrO3) and CO2 sorption rate (0.0017 mmol CO2/g) after 5 min at 700 °C. This was attributed to a larger presence of microstructure defects that facilitate Na diffusion from the core to the shell of the particles. An ND analysis showed that the conversion of Na2ZrO3 was complete under the studied conditions and that CO2 concentration significantly impacts the rate of CO2 absorption. The TGA results indicated that the reaction rate during CO2 sorption remained steady until full conversion due to the absorptive nature of the chemisorption process. During the sorbent reforming step, ND revealed the disappearance of Na2O and ZrO2 as the zirconate phase reformed. However, trace amounts of Na2CO3 and ZrO2 remained after the cycles.

Facile in-Situ Straining Platform for Transmission Electron Microscopy with Quantification of Strains

This work aims to design and model an experimental platform to perform in-situ straining experiments in a transmission electron microscope (TEM), enabling structural characterization of materials under tensile strain. The ability to visualize changes in the crystal structure of materials under strain can provide important insights into failure modes and improve understanding of process-structure-property relationships. Existing methods of in-situ straining typical involve complex sample preparation and are not well-suited to the study of thin films or sensitive battery materials. In this work, thin films of materials are deposited on a conventional TEM grid adhered to a copper template. The template is mounted in a Gatan 654 single tilt straining holder and strained within the TEM. Electron diffraction patterns are taken from the specimens, and strain can be calculated based on shifts in the Bragg reflections.An essential component of in-situ straining experiments is the quantification of applied strains. For our facile straining platform, we calculate the expected values of strain on our specimen using a finite element model. The finite element strain simulation data was compared with experimental data collected during in-situ straining experiments. Experimental results on a variety of material systems, including those applicable to lithium-ion batteries, are within the bounds of our model. Overall, the ability to accurately simulate in-situ strains using the finite element model enables researchers to better explain observation in the TEM, improve the reproducibility of the experiments, and optimize straining geometries to be tested. Figure 1

Mechanics of surface deformations in rigid bodies

Studying surface deformations in solids is crucial for advancing science and technology, informing material development, structural design and process enhancement. The purpose of study is to review and analyse the mechanics of surface deformations in rigid bodies in order to identify their features and develop new methods for describing and predicting such deformations. The study analysed theoretical models and experimental approaches to study surface deformation; among the methods used, the analytical method, classification method and synthesis method should be noted. In the study, the following parameters and aspects related to surface deformation in rigid bodies were investigated: material response to plastic deformation, mechanical properties, surface deformation characteristics, extent of deformation and behaviour under small deformations. The study investigates the impact of plastic deformation on the crystal structure of materials, focusing on grain boundary structure, dislocation motion and stacking faults. The main results of the study are the identification of the relationship between mechanical stress and surface deformation in rigid bodies. It was found that high mechanical stress leads to a change in the crystal structure of the material on the surface, which, in turn, affects its mechanical properties. Also, the results of the study are the establishment of relationships between the parameters of materials and the amount of surface deformation, as well as the identification of physical laws governing this process.

Synergistic structure and oxygen-vacancies engineering of lithium vanadate for kinetically accelerated and pseudocapacitance-dominated lithium storage

The high reversibility, capacity, and safety make lithium vanadate (LVO) an attractive anode to Li-ion batteries, yet they still suffer from the low intrinsic electrical conductivity and ion diffusion rate. Modulating the electronic and crystal structure of materials by vacancies engineering could significantly affect the lithium storage performance. Herein, high concentration of oxygen-vacancies incorporated Li3VO4 nanowires (HLVO) were prepared to make up conductivity and ion diffusion kinetics of LVO as a competitive fast-charging anode. The oxygen-vacancies were derived from the controllable oxidation of local V4+ ions via the thermal treatment, enabling the redistribution of electrons and optimized charge‐transport properties of LVO on the basis of the experimental results and theoretical calculations. The reduced reaction energy barriers, enhanced Li-ion diffusion, improved electrical conductivity, and additional active sites induced by oxygen-vacancies drastically accelerate the redox kinetics, enhancing the capacitive behavior. Thus, the HLVO anode delivers superior electrochemical performance with large specific capacities of 553.8 mA h g−1, exceptional rate capacity of 312.2 mA h g−1 even at 4.0 A g−1 and excellent cycling stability. This finding provides the credence to the prospect of vacancy engineering contributing to develop the matter-of-fact transition metal oxides as high-performance anodes for Li-ion batteries.

One-pot synthesis of high-efficiency one-dimensional perovskite phosphor for warm white LEDs

A simple one-pot method was used to synthesize one-dimensional perovskite phosphor, which was characterized using X-ray diffraction, scanning electron microscopy, and photoluminescence spectroscopy. The material demonstrates excellent photoluminescence properties and can emit warm white light with a color temperature of 4710 K and a color rendering index of 84.6. The simple one-pot method makes it easy to synthesize the perovskite phosphor, positioning it as a promising candidate for the production of warm white LEDs. This work provides a detailed analysis of the material's crystal structure and photoluminescence properties.

Understanding the Insight Mechanism of Chemical-Mechanical Degradation of Layered Co-Free Ni-Rich Cathode Materials: A Review.

Layered Cobalt (Co)-free Nickel (Ni)-rich cathode materials have attracted much attention due to their high energy density and low cost. Still, their further development is hampered by material instability caused by the chemical/mechanical degradation of the material. Although there are numerous doping and modification approaches to improve the stability of layered cathode materials, these approaches are still in the laboratory stage and require further research before commercial application. To fully exploit the potential of layered cathode materials, a more comprehensive theoretical understanding of the underlying issues is necessary, along with active exploration of previously unrevealed mechanisms. This paper presents the phase transition mechanism of Co-free Ni-rich cathode materials, the existing problems, and the state-of-the-art characterization tools employed to study the phase transition. The causes of crystal structure degradation, interfacial instability, and mechanical degradation are elaborated, from the material's crystal structure to its phase transition and atomic orbital splitting. By organizing and summarizing these mechanisms, this paper aims to establish connections among common research problems and to identify future research priorities, thereby facilitating the rapid development of Co-free Ni-rich materials.

Origin of improved average power factor and mechanical properties of SnTe with high-dose Bi2Te3 alloying

Chemical bond and defect engineering have profound impact on energy band and crystal structure of materials, which can adjust physicochemical and mechanical properties of materials. BiSn and VSn are simultaneously designed in SnTe material system via the (SnTe)x(Bi2Te3) alloying form, which was realized by vacuum melting and spark plasma sintering technology. Both point defects increase band gap and decrease ΔEL−Σ, which improves obviously Seebeck coefficient of SnTe. The high-efficiency improvement in the middle temperature zone makes average power factor of (SnTe)24(Bi2Te3) achieves 1656 μWm-1K−2(323K–773K). BiSn induces strong coupling hybridization between Te-5s and Te-5p, and forms the lower bonding state. The lower bonding state and the larger -IpCOHP increase bond strengthen, which result in the smaller thermal expansion coefficient and the higher hardness. Bonding evolution makes thermal expansion coefficient of SnTe reduce by 27%, and Vickers hardness increase by 44%. Higher average power factor, lower thermal expansion coefficient and higher hardness can improve output power density and service life, which provides strategies for exploiting high-power thermoelectric devices with suitable mechanical properties.

Correlation analysis with measurement conditions and peak structures in XPS spectral round-robin tests on MnO powder sample

Spectral measurements provide valuable information on the electronic states and crystal structures of materials. In particular, X-ray photoelectron spectroscopy (XPS) can facilitate the analysis of the chemical-bond states of the surfaces of materials. In the analysis of XPS spectra, the spectrum to be measured is typically compared to a reference spectrum measured from a known single-phase sample. Therefore, establishing a reference spectral database is imperative. In this study, round-robin tests (RRT) of XPS spectra are performed to obtain recommended XPS reference spectra and develop appropriate measurement conditions, including preprocessing procedures. Determining the variations in peak structures between equipment- and sample-derived spectral shapes and quantitatively discussing them through RRT of XPS spectra are challenging. Therefore, an analysis method that automatically determines the above-mentioned variations and extracts the sample-derived common spectral structures is developed in this study. This paper presents a new approach to the quantitative analysis of round-robin XPS spectral tests. The required common peak structure, a new definition of the XPS reference spectrum, is obtained. Further, a correlation between the variability of deviations in the spectral data of the RRT and the measurement condition and XPS measurement equipment used is determined. Such a framework is essential for standardizing XPS spectra and expanding the XPS reference spectral database.

Band gap prediction of perovskite materials based on transfer learning

<sec>The band gap is a key physical quantity in material design. First-principles calculations based on density functional theory can approximately predict the band gap, which often requires significant computational resources and time. Deep learning models have the advantages of good fitting capability and automatic feature extraction from the data, and are gradually used to predict the band gap. In this paper, aiming at the problem of quickly obtaining the band gap value of perovskite material, a feature fusion neural network model, named CGCrabNet, is established, and the transfer learning strategy is used to predict the band gap of perovskite material. The CGCrabNet extracts features from both chemical equation and crystal structure of materials, and fits the mapping between feature and band gap. It is an end-to-end neural network model. Based on the pre-training data obtained from the Open Quantum Materials Database (OQMD dataset), the CGCrabNet parameters can be fine-tuned by using only 175 perovskite material data to improve the robustness of the model.</sec><sec>The numerical and experimental results show that the prediction error of the CGCrabNet model for band gap prediciton based on the OQMD dataset is 0.014 eV, which is lower than that obtained from the prediction based on compositionally restricted attention-based network (CrabNet). The mean absolute error of the model developed in this paper for predicting perovskite materials is 0.374 eV, which is 0.304 eV, 0.441 eV and 0.194 eV lower than that obtained from random forest regression, support vector machine regression and gradient boosting regression, respectively. The mean absolute error of the test set of CGCrabNet trained only by using perovskite data is 0.536 eV, and the mean absolute error of the pre-trained CGCrabNet decreases by 0.162 eV, which indicates that the transfer learning strategy plays a significant role in improving the prediction accuracy of small data sets (perovskite material data sets). The difference between the predicted band gap of some perovskite materials such as SrHfO<sub>3</sub> and RbPaO<sub>3</sub> by the model and the band gap calculated by first-principles is less than 0.05 eV, which indicates that the CGCrabNet can quickly and accurately predict the properties of new materials and accelerate the development process of new materials.</sec>

Atomic structure generation from reconstructing structural fingerprints

Data-driven machine learning methods have the potential to dramatically accelerate the rate of materials design over conventional human-guided approaches. These methods would help identify or, in the case of generative models, even create novel crystal structures of materials with a set of specified functional properties to then be synthesized or isolated in the laboratory. For crystal structure generation, a key bottleneck lies in developing suitable atomic structure fingerprints or representations for the machine learning model, analogous to the graph-based or SMILES representations used in molecular generation. However, finding data-efficient representations that are invariant to translations, rotations, and permutations, while remaining invertible to the Cartesian atomic coordinates remains an ongoing challenge. Here, we propose an alternative approach to this problem by taking existing non-invertible representations with the desired invariances and developing an algorithm to reconstruct the atomic coordinates through gradient-based optimization using automatic differentiation. This can then be coupled to a generative machine learning model which generates new materials within the representation space, rather than in the data-inefficient Cartesian space. In this work, we implement this end-to-end structure generation approach using atom-centered symmetry functions as the representation and conditional variational autoencoders as the generative model. We are able to successfully generate novel and valid atomic structures of sub-nanometer Pt nanoparticles as a proof of concept. Furthermore, this method can be readily extended to any suitable structural representation, thereby providing a powerful, generalizable framework towards structure-based generation.

TiN–LiAlSiO4 powders for hydrogen production under simulated solar light and their relationship between photocatalytic activity and the coefficient of thermal expansion

In the present work, it is reported the synergy effect from TiN with LiAlSiO4 powders for hydrogen production under simulated solar light. TiN–LiAlSiO4 composites were synthesized by solid-state reaction. XRD results showed that conditions of the preparation of the composite did not cause any variation on the crystal structure of materials. By SEM analysis, composites presented a homogeneous distribution of the TiN and LiAlSiO4 particles with similar morphology to TiN or LiAlSiO4, depending on their content in the mixture. Energy band-gap values are within the interval of 2.0 and 3.5 eV, where the presence of TiN in a proportion greater than 30% caused that composite showed Eg values lower than 3.0 eV, which could be favorable for their potential application in photocatalysis under solar light. All samples showed specific surface area close to 2.0 m2/g. TiN–LiAlSiO4 composites presented higher photocatalytic activity than TiN and LiAlSiO4, which is occasioned by synergy effect from, n-type, and p-type semiconductors, respectively. The photocatalytic activity is greater in composites with a major proportion of TiN than those where TiN is less than 50%. TiN–LiAlSiO4 (T60:L40) showed the highest activity, around 306 μmol H2, after 3 h. This activity was corroborated by PL analysis where composite with more than 50% of TiN, presented less intensity in the spectra, indicating that a reduction electron-hole pair recombination rate is occurring during the irradiation. Furthermore, it was found that there is a relation between the coefficient of thermal expansion (CTE) and photocatalytic hydrogen production. Composites with positive thermal expansion (PTE) showed a higher amount of H2 than composites with negative thermal expansion (NTE). Coincidentally, T60:L40 shows the highest activity, but also it is the one that presents the CTE value closest to zero.

Comprehensive Review on Thermoelectric Electrodeposits: Enhancing Thermoelectric Performance Through Nanoengineering.

Thermoelectric devices based power generation and cooling systemsystem have lot of advantages over conventional refrigerator and power generators, becausebecause of solid-state devicesdevices, compact size, good scalability, nono-emissions and low maintenance requirement with long operating lifetime. However, the applications of thermoelectric devices have been limited owingowing to their low energy conversion efficiency. It has drawn tremendous attention in the field of thermoelectric materials and devices in the 21st century because of the need of sustainable energy harvesting technology and the ability to develop higher performance thermoelectric materials through nanoscale science and defect engineering. Among various fabrication methods, electrodeposition is one of the most promising synthesis methods to fabricate devices because of its ability to control morphology, composition, crystallinity, and crystal structure of materials through controlling electrodeposition parameters. Additionally, it is an additive manufacturing technique with minimum waste materials that operates at near room temperature. Furthermore, its growth rate is significantly higher (i.e., a few hundred microns per hour) than the vacuum processes, which allows device fabrication in cost effective matter. In this paper, the latest development of various electrodeposited thermoelectric materials (i.e., Te, PbTe, Bi2Te3 and their derivatives, BiSe, BiS, Sb2Te3) in different forms including thin films, nanowires, and nanocomposites were comprehensively reviewed. Additionally, their thermoelectric properties are correlated to the composition, morphology, and crystal structure.

Anisotropic Nodal‐Line‐Derived Large Anomalous Hall Conductivity in ZrMnP and HfMnP (Adv. Mater. 48/2021)

Topological Nodal Line States A mirror helps light rays to make an image of an object; the mirror planes in a material's crystal structure similarly guide electrons and enhance the properties. In article number 2104126, Chandra Shekhar and co-workers demonstrate that the abundance of such mirror planes is primarily responsible for topological nodal line states at the Fermi energy in some ferromagnetic metals, leading to a large anomalous Hall conductivity.

Study on microstructure evolution of grinding surface of bcc Fe-Ni maraging steel based on molecular dynamics

Research on microstructure of material removal process is the key to aerospace high-performance manufacturing because of the limitation of relative linear speed of tool and workpiece for small-size parts. The polycrystalline grinding model of Fe-Ni maraging steel was established by 3D molecular dynamics simulation method. The effects of parameter combinations on force, temperature, microstructure and dislocation were researched based on the simulation results. The grinding surface and subsurface were defined as the chips, subsurface damage (SSD) layer and intact layer of workpiece according to the damage degree of the microstructure, and the evolution mechanism of microstructure of different regions was studied emphatically. The results indicate that most energy of micro-nano grinding is consumed for the influence on the crystal structure of material. The main factors of the damage of microstructure is the cutting depth of single grit, and the increase of linear velocity gradually decreases its influence on the microstructure with a cutting depth larger than 1.8 nm. The shallower cutting depth and higher grinding speed are the better parameter combinations, which result in the reduction of SSD thickness, and the surface BCC structure, dislocation density and grinding efficiency are maintained with a slight increase in force and temperature.

Supercapacitor properties of V10O14(OH)2 and reduced graphene oxide hybrids: Experimental and theoretical insights

In this work, V10O14(OH)2 nanostructure and its hybrid with reduced graphene oxide (rGO/V10O14(OH)2) have been synthesized by a simple hydrothermal process, and the supercapacitance property has been explored. The material's crystal structure, surface morphology, elemental compositions, and oxidation state of metal atoms are properly characterized. The structure and electronic properties of V10O14(OH)2 and rGO/V10O14(OH)2 are presented using Density Functional Theory (DFT) investigations. Using the cyclic voltammetry (CV) technique, the capacitance of the rGO/V10O14(OH)2 hybrid was found to be 558 Fg−1 at a scan rate of 1 mV/s, which is 2.9 times greater than the capacitance of the V10O14(OH)2 material. The hybrid material provides 94% operational stability over 5000 cycles. From the Trassatti plot, the capacitance contribution of rGO/V10O14(OH)2 and V10O14(OH)2 are estimated, and found that the maximum capacitance contribution is due to diffusion-controlled pseudocapacitance phenomena, i.e., 87.5% and 95.9%, respectively. Enhanced electronic states near Fermi level and improved quantum capacitance for the hybrid structure justify the superior charge storage performance of the integrated structure (rGO/ V10O14(OH)2) as observed in the experiment. Also, the mobility of the electrolyte ions increases in the hybrid structure due to lower diffusion energy barrier leading to better charge transfer kinetics.

A Review of Potential Ferrous Metal Lathe Waste as A Raw Material of LiFePO<sub>4</sub>

Lathe waste is one of the wastes products of metal processing in the metal-turning industry. The most content of lathe waste is a ferrous (Fe) metal, which, if disposed of into the environment, can cause environmental pollution. Fe metal from lathe waste can be used as a Fe precursor in LiFePO4 synthesis. The extraction of Fe from the lathe waste can be done by the leaching method using acid as the leaching agent. The recovered compounds have great potential to be used as Fe precursors for the LiFePO4 synthesis. The selection of leaching agent was based on considerations of the price, the effectiveness of Fe extraction, and the advanced recovery process from Fe extraction. The LiFePO4 synthesis process can be carried out using co-precipitation, hydrothermal, and sol-gel. LiFePO4 material characterization was carried out to test the yield of the material produced. Synthesized materials were done to test the characteristics by Scanning Electron Microscopy (SEM) and X-Ray Diffractometer (XRD) analysis. SEM analysis aims to describe the shape and particle size of the material in three dimensions. Meanwhile, XRD analysis aims to characterize the material's crystal structure and crystal size by using the Lattice Parameter value. The electrochemical test aims to test electrochemistry to test the capacity of charge/discharge, efficiency, and lithium-ion batteries' stability. The resulting battery capacity from the three methods is close to the theoretical capacity of LiFePO4, which is 170 mAh/g.

Ultrafast Control of Material Optical Properties via the Infrared Resonant Raman Effect

The Raman effect -- inelastic scattering of light by lattice vibrations (phonons) -- produces an optical response closely tied to a material's crystal structure. Here we show that resonant optical excitation of IR and Raman phonons gives rise to a Raman scattering effect that can induce giant shifts to the refractive index and induce new optical constants that are forbidden in the equilibrium crystal structure. We complete the description of light-matter interactions mediated by coupled IR and Raman phonons in crystalline insulators -- currently the focus of numerous experiments aiming to dynamically control material properties -- by including a forgotten pathway through the nonlinear lattice polarizability. Our work expands the toolset for control and development of new optical technologies by revealing that the absorption of light within the terahertz gap can enable control of optical properties of materials over a broad frequency range.

Techniques for studying materials under extreme states of high energy density compression

The properties of materials under extreme conditions of pressure and density are of key interest to a number of fields, including planetary geophysics, materials science, and inertial confinement fusion. In geophysics, the equations of state of planetary materials, such as hydrogen and iron, under ultrahigh pressure and density provide a better understanding of their formation and interior structure [Celliers et al., “Insulator-metal transition in dense fluid deuterium,” Science 361, 677–682 (2018) and Smith et al., “Equation of state of iron under core conditions of large rocky exoplanets,” Nat. Astron. 2, 591–682 (2018)]. The processes of interest in these fields occur under conditions of high pressure (100 GPa–100 TPa), high temperature (>3000 K), and sometimes at high strain rates (>103 s−1) depending on the process. With the advent of high energy density (HED) facilities, such as the National Ignition Facility (NIF), Linear Coherent Light Source, Omega Laser Facility, and Z, these conditions are reachable and numerous experimental platforms have been developed. To measure compression under ultrahigh pressure, stepped targets are ramp-compressed and the sound velocity, measured by the velocity interferometer system for any reflector diagnostic technique, from which the stress-density of relevant materials is deduced at pulsed power [M. D. Knudson and M. P. Desjarlais, “High-precision shock wave measurements of deuterium: Evaluation of exchange-correlation functionals at the molecular-to-atomic transition,” Phys. Rev. Lett. 118, 035501 (2017)] and laser [Smith et al., “Equation of state of iron under core conditions of large rocky exoplanets,” Nat. Astron. 2, 591–682 (2018)] facilities. To measure strength under high pressure and strain rates, experimenters measure the growth of Rayleigh–Taylor instabilities using face-on radiography [Park et al., “Grain-size-independent plastic flow at ultrahigh pressures and strain rates,” Phys. Rev. Lett. 114, 065502 (2015)]. The crystal structure of materials under high compression is measured by dynamic x-ray diffraction [Rygg et al., “X-ray diffraction at the national ignition facility,” Rev. Sci. Instrum. 91, 043902 (2020) and McBride et al., “Phase transition lowering in dynamically compressed silicon,” Nat. Phys. 15, 89–94 (2019)]. Medium range material temperatures (a few thousand degrees) can be measured by extended x-ray absorption fine structure techniques, Yaakobi et al., “Extended x-ray absorption fine structure measurements of laser-shocked V and Ti and crystal phase transformation in Ti,” Phys. Rev. Lett. 92, 095504 (2004) and Ping et al., “Solid iron compressed up to 560 GPa,” Phys. Rev. Lett. 111, 065501 (2013), whereas more extreme temperatures are measured using x-ray Thomson scattering or pyrometry. This manuscript will review the scientific motivations, experimental techniques, and the regimes that can be probed for the study of materials under extreme HED conditions.

Study on the effect of Ag nanoparticles density on ZnO/Ag nanostructure to enhance raman signals of SERS substrate on abamectin

This study investigated the effect of changing the density of Ag nanoparticles on the ZnO/Ag nanorod structure on the SERS substrate signal amplification ability. First, ZnO nanorods were fabricated by the sol - gel method combining with the chemical bath deposition method. Next, the Ag nanoparticles were decorated on ZnO nanorods by the DC magnetron sputtering method. The density and size of the modified Ag nanoparticles on the ZnO nanorods were changed by adjusting the sputtering times to 5, 10, 15 and 20s respectively. The optical properties of the material are characterized by UV - Vis and PL measurements. The surface morphology of ZnO nanorods and Ag nanoparticles were investigated by scanning electron microscope (SEM). X-ray diffraction measurement (XRD) is used to examine the crystal structures of materials. The composition and distribution of the chemical elements inside the material were investigated by Energy-dispersive X-ray spectroscopy (EDX). The ability of SERS substrates to amplify Raman signals was evaluated by measuring the R6G solution and investigating application for abamectin with a laser excitation wavelength of 532 nm. The results showed that SERS ZnO/Ag substrates with sputtering time of 15s gave the best ability to amplify SERS with the detection of R6G solution at 10􀀀9 M and abamectin at 50 ppm.