NC System Research Articles

Disclosing the influence mechanism of facet-dependent pyrite photo-activation and photo-dissolution processes on the reduction of Cr(VI)

The photo-activation and photo-dissolution processes of pyrite (FeS2) can affect the environmental behavior of the co-existing hexavalent chromium (Cr(VI)). But the photochemical performance of FeS2 is intimately dependent on its exposed facets. Herein, FeS2 nanosheets (FeS2 NS) and FeS2 nanocubes (FeS2 NC) with the dominant exposed facets of (001) and (210)/(100) respectively are prepared. The more Fe3+, Fe2+, and SO42− are released in the FeS2 NS system than the other system due to its more excellent generation ability of photogenerated electrons and reactive oxygen species. The higher surface energy on (001) facet leads to the faster dissolution rate of FeS2 NS. Due to the optimal production ability of photogenerated electrons and Fe2+ of (001) facet, the much higher Cr(VI) elimination efficiency in the FeS2 NS system is observed than that in the FeS2 NC (72.8%) system within 120 min. This work could help to unveil the influence of FeS2 on the fate of Cr(VI) in surface environment, and offer a theoretical support to clarify the influence of heavy metal ions on the iron sulfide minerals.

Determination of GaN nanosensor for scavenging of toxic heavy metal ions (Mn2+, Zn2+, Ag+, Au3+, Al3+, Sn2+) from water: Application of green sustainable materials by molecular modeling approach

Gallium nitride nanocage (GaN_NC) can select toxic heavy metals from water. Therefore, it has been found a selective competition for metal cations in the GaN_NC. The electromagnetic and thermodynamic attributes of heavy metals cations-trapped gallium nitride nanocage (GaN_NC) was depicted by material modeling. The data display that heavy metals cations-trapped in the GaN_NC system are resistant materials, with the firm adsorption zone in the center of the cage. Furthermore, charge transfer from GaN_NC to the heavy metals cations demonstrates clear n-type adsorbing manner. The encapsulation of heavy metals cations occurs via chemisorption. In this article, the behavior of trapping of heavy metal ions of Mn2+, Zn2+, Ag+, Au3+, Al3+ and Sn2+ by gallium nitride nanocone for sensing the water metal cations was observed. The nature of covalent features for these complexes has represented the analogous energy amount and vision of the PDOS for the p states of N and d states of heavy metal cations of Mn2+, Zn2+, Ag+, Au3+, Al3+ and Sn2+ through water treatment. The partial density of states (PDOS) can also evaluate an appointed charge group between Mn2+, Zn2+, Ag+, Au3+, Al3+, Sn2+ and GaN_NC which indicate the most stable complex of metallic visage and a certain degree of covalent specifications between heavy metals cations and gallium nitride nanocage. Furthermore, the NMR analysis indicated the notable peaks surrounding metal elements of Mn2+, Zn2+, Ag+, Au3+, Al3+ and Sn2+ through the trapping in the GaN_NC during ion detection and removal from water; however, it can be seen some fluctuations in the chemical shielding treatment of isotropic and anisotropy tensors. Based on the results in this research, the selectivity of metal ion adsorption by gallium nitride nanocage (ion sensor) has been approved as: Ag+ ˃ Au3+ ˃ Mn2+ ≫ Zn2+ ˃ Sn2+ ˃ Al3+. Using quantum theory of atoms in molecules (QTAIMs) method, intermolecular interactions and corresponding parameters at critical bonding points were also investigated.

Sprayable biogenic Ag-collagen nanocomposites with potent antibacterial and antibiofilm activity for Acinetobacter baumannii infected wound healing under hyperglycemic condition

Owing to their susceptibility to infection by drug-resistant bacteria, refractory wounds pose a formidable risk to the well-being of patients with diabetes and other immune-compromised conditions, and their management poses significant economic distress to the healthcare system, particularly in low and middle-income countries. Therefore, deployable interventions for rapid and effective management of such wounds are needed. In the present study, we report the processing of sprayable biogenic Ag-collagen nanocomposites (Ag-Col NCs) with cogent antibacterial and healing activity in Acinetobacter baumannii infected wounds under hyperglycemic conditions. Silver nanoparticles (Ag NPs) has been synthesized by using the plant extract of Urginea indica (U. indica), which was further used for the processing of Ag-Col NCs. Synthesized NCs were found to have notable broad spectrum antibacterial activity against clinically significant strains (Acinetobacter baumannii, Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus) and appreciable biocompatibility towards RAW 264.7 and 3 T3 mouse fibroblast cell lines. The sprayable NC system was found to promote the wound healing activity in mouse model (Balb/c) not only in normal but also in hyperglycemic conditions. Our experimental findings suggest the potential of the Ag-Col NC spray in chronic wound management and an exploitable option in both clinical and personalized settings.

Acceleration and deceleration control algorithm of CNC system based on deep neural network reinforcement learning and MCU

Acceleration and deceleration control, as one of the key technologies in high-speed CNC system, directly affects the machining efficiency, the stability of machining process and the error of machining follow. Therefore, it is necessary to study and explore new acceleration and deceleration control methods in high-speed CNC system to ensure the smooth feed and improve the machining accuracy. Therefore, the acceleration and deceleration control algorithm of NC system based on deep reinforcement learning and single chip microcomputer is studied. The theoretical basis of deep reinforcement learning is analyzed, and the acceleration of acceleration and deceleration is calculated based on the linear acceleration and deceleration control. The whole integer operation of single chip microcomputer is used to estimate the value range of each step. The variation characteristics of trajectory motion are predicted so that acceleration and deceleration can be processed across program segments. The velocity of transfer point is calculated by the rate of change of feed velocity vector, and the speed of multi-program is smoothed by adjusting the allowable contour error. Based on the proximal strategy optimization algorithm in deep reinforcement learning, the acceleration and deceleration control model of CNC system is established to realize the acceleration and deceleration control. The experimental results show that the proposed algorithm has better control effect, shorter time and smaller interpolation error, which can ensure the NC system to feed smoothly at high speed.

Trapping of toxic heavy metals from water by GN–nanocage: Application of nanomaterials for contaminant removal technique

Gallium nitride nanocage (GaN_NC) can select toxic heavy metals from water. Therefore, it has been found a selective competition for metal cations in the GaN_NC. The electromagnetic and thermodynamic attributes of heavy metals cations trapped GaN_NC was depicted by material modeling. The data displays those heavy metals cations-trapped in the GaN_NC system are resistant materials, with the most firm adsorption zone in the center of the cage. Furthermore, charge transfer from GaN_NC to the heavy metals cations demonstrates clear n-type adsorbing manner. The encapsulation of heavy metals cations occurs via chemisorption. In this article, it was observed the behavior of trapping of main group cations of Cr3+, Co2+, Cu2+, Ni2+, Pb2+ and As3+ by GaN_NC for sensing the water metal cations. The nature of covalent features for these complexes has represented the analogous energy amount and vision of the partial density of states (PDOS) for the p states of N and d states of heavy metal cations of Cr3+, Co2+, Cu2+, Ni2+, Pb2+ and As3+ through water treatment. The PDOS can also evaluate an appointed charge group between Cr3+, Co2+, Cu2+, Ni2+, Pb2+, As3+ and GaN_NC which indicate the most stable complex of metallic visage and a certain degree of covalent specifications between heavy metals cations and GaN_NC. Furthermore, the nuclear magnetic resonance (NMR) analysis indicated the notable peaks surrounding metal elements of Cr3+, Co2+, Cu2+, Ni2+, Pb2+ and As3+ through the trapping in the GaN_NC during ion detection and removal from water; however, it can be seen some fluctuations in the chemical shielding treatment of isotropic and anisotropy tensors. Based on the results in this research, the selectivity of metal ion adsorption by GaN_NC (ion sensor) has been approved as: Ni2+˃˃˃ Cu2+ ˃Co2+˃ Cr3+˃˃ Pb2+ ˃ As3+.

An adaptive singularity avoidance method for five-axis toolpath generation with invariant cutter-contact points and bounded tool orientation variation based on the reduction of Jacobian condition number

To enhance the five-axis machine-tool performance, it is significant to avoid the singular configuration where the kinematic and dynamic performances degrade dramatically. Most existing methods aim at solving this issue by avoiding the singularity posture in the geometric manner. Different from them, this paper aims at avoiding the singular phenomenon by reducing the Jacobian-matrix condition number, and proposes an adaptive singularity avoidance toolpath generation method. This method adds a damping diagonal matrix into the computation of the pseudo-inverse Jacobian matrix to reduce its ill-condition extent during axial path generation, thus solving the singularity phenomenon. However, the adding of damping matrix gives arise to the toolpath error. To ensure the accuracy meanwhile, an adaptive law for determination of the damping matrix is presented to balance the singularity-avoiding effect and the path error, under the constraints of condition number and tool-orientation error-tolerance thresholds, as well as invariant cutter-contact points. Simulation and experimental tests verify that the proposed method can not only realize the singular avoidance without preliminary adjustment of the original toolpath, thus can be realized in real-time NC system, but also has better singular-avoiding performance and lower toolpath error when comparing with typical methods.

The Impact of Longitudinal Data-Completeness of Electronic Health Record Data on the Prediction Performance of Clinical Risk Scores.

The impact of electronic health record (EHR) discontinuity (i.e., receiving care outside of a given EHR system) on EHR-based risk prediction is unknown. We aimed to assess the impact of EHR-continuity on the performance of clinical risk scores. The study cohort consisted of patients aged ≥ 65 years with ≥ 1 EHR encounter in the 2 networks in Massachusetts (MA; 2007/1/1-2017/12/31, internal training and validation dataset), and one network in North Carolina (NC; 2007/1/1-2016/12/31, external validation dataset) that were linked with Medicare claims data. Risk scores were calculated using EHR data alone vs. linked EHR-claims data (not subject to misclassification due to EHR-discontinuity): (i) combined comorbidity score (CCS), (ii) claim-based frailty score (CFI), (iii) CHAD2 DS2 -VASc, and (iv) Hypertension, Abnormal renal/liver function, Stroke, Bleeding, Labile, Elderly, and Drugs (HAS-BLED). We assessed the performance of CCS and CFI predicting death, CHAD2 DS2 -VASc predicting ischemic stroke, and HAS-BLED predicting bleeding by area under receiver operating characteristic curve (AUROC), stratified by quartiles of predicted EHR-continuity (Q1-4). There were 319,740 patients in the MA systems and 125,380 in the NC system. In the external validation dataset, AUROC for EHR-based CCS predicting 1-year risk of death was 0.583 in Q1 (lowest) EHR-continuity group, which increased to 0.739 in Q4 (highest) EHR-continuity group. The corresponding improvement in AUROC was 0.539 to 0.647 for CFI, 0.556 to 0.637 for CHAD2 DS2 -VASc, and 0.517 to 0.556 for HAS-BLED. The AUROC in Q4 EHR-continuity group based on EHR alone approximates that based on EHR-claims data. The prediction performance of four clinical risk scores was substantially worse in patients with lower vs. high EHR-continuity.

Milling Simulation of NC System Based on 3D Modeling

In order to avoid interference in NC milling process, a milling simulation design method of NC system based on 3D modeling technology is proposed. We use OpenGL technology and advanced object-oriented programming technology to perform a comprehensive object-oriented design of the NC milling simulation software system. On this basis, the tool motion parameters in the NC code are extracted and stored, the STL model is introduced as the data model of the machining object, and the interface mechanism between OpenGL and VC is provided. Finally, through the main interface of Visual C++ application program, the development of database and application system oriented to 3D end mill model is realized. The simulation results show that the method presented in this paper is more realistic for the establishment of the whole virtual milling machine profile, and it is suitable for general or more complex parts NC machining programming and simulation.

Thermodynamic Analysis of the Chromium Reduction Process Using the Cr-C-O System During Metallization of Chromium Ores

The aim of the work is to determine the optimal temperature regime for firing chromium ore and the consumption of solid carbon, which ensures the recovery of chromium. The process of chromium reduction was investigated on a model elementary system by reducing chromium from ore with solid carbon. The areas of redox conditions in the Cr-C-O system were identified, the boundaries of the reduction, transition and oxidative regions were revealed. The temperature required for the recovery process was determined by calculating the equilibrium compositions of the Cr2O3 + nC system in the temperature range 1100-1900 K at n = 1, 2, 3, 4 and 5 moles.

Harvesting Plasmonic Near-Infrared Photons by Hot Hole Transfer in Nonstoichiometric-Semiconductor Plasmonic Heterojunctions

Infrared light is an untapped energy source that accounts for half of solar energy. Thus, harvesting near-infrared photons for different applications needs further development for efficient utilization of the whole solar spectrum. Herein, we report harvesting infrared photons by hot hole transfer from a nonstoichiometric plasmonic semiconductor (Cu2–xSe) to an adjacent semiconductor (CdSe) in the heterostructure (HNCs). We found a decrease in transient signal intensity and hole–phonon scattering time in Cu2–xSe/CdSe HNCs compared to the pure Cu2–xSe nanocrystals, attributed to plasmon-induced hot hole transfer. A similar kind of TA kinetics has been observed for 800 and 930 nm laser pulse excitation for Cu2–xSe/CdSe HNCs. The spectroscopic results reveal anomalous carrier populations and slow carrier recovery dynamics at the 1P state of the CdSe phase in Cu2–xSe/CdSe HNCs, further establishing the plasmonic hot hole transfer mechanism. The estimated plasmon-induced hot hole transfer time from the nonstoichiometric semiconductor Cu2–xSe NC system is determined and found to be ∼177 fs. Fabricated plasmonic thin-film devices exhibit an excellent conductivity (0.15 A at 2 V) and photoconductivity (0.2 A at 2 V) under near-infrared light illustration (λlight = 1200 nm) in a plasmonic HNC system. These results reveal a novel approach for harvesting light photons from the visible to near-infrared region of the solar spectrum and provide a new avenue for developing hot carrier-based device applications of plasmonic semiconductor-based nanomaterials.

Cu/Au nanoclusters with peroxidase-like activity for chemiluminescence detection of α-amylase.

Herein, a novel chemiluminescence method was developed for efficient and sensitive detection of α-amylase activity. α-Amylase is closely related to our life, and α-amylase concentration is a marker for the diagnosis of acute pancreatitis. In this paper, Cu/Au nanoclusters with peroxidase-like activity were prepared using starch as a stabilizer. Cu/Au nanoclusters can catalyze H2O2 to generate reactive oxygen species and increase the CL signal. The addition of α-amylase makes the starch decompose and causes the nanoclusters to aggregate. The aggregation of the nanoclusters caused them to increase in size and decrease in the peroxidase-like activity, resulting in a decrease in the CL signal. α-Amylase was detected by the CL method of signal changes caused by dispersion-aggregation in the range of 0.05-8 U mL-1 with a low detection limit of 0.006 U mL-1. The chemiluminescence scheme based on the luminol-H2O2-Cu/Au NC system is of great significance for the sensitive and selective determination of α-amylase in real samples, and the detection time is short. This work provides new ideas for the detection of α-amylase based on the chemiluminescence method and the signal lasts for a long time, which can realize timely detection.

Application of programmable logic control in the nonlinear machine automation control using numerical control technology

Abstract To explore the application of programmable logic control (PLC) in the automatic control of nonlinear machine tools, the application of PLC in the nonlinear electronic system control is studied. First, the author takes PLC technology in the numerical control machine tool electrical control application as the research equipment, PLC technology in the numerical control machine tool electrical control application is divided into four types. Then, according to the need of management number, the overall structure of PLC is designed and developed, and the concept of operation modularization is adopted to realize the decentralized development of PLC. There are three functional modules: repair, compile, and simulate. Finally, the machining performance of the nc system is evaluated experimentally. The processing time difference of two kinds of machine tools is compared. The average processing time of the original (Numerically controlled) NC system is 3.06 s, and the average processing time of the embedded soft PLC system is 2.01 s, with a gap of 1.04 s between the two systems. The Computer Numerical Control (CNC) machining improvement of 1 s is significant in the processing efficiency of CNC machine tools. The numerical control system embedded in the PLC system is more stable in the machining time, so it can be concluded that the numerical control-embedded soft PLC system has carried on some improvements and upgrades to the operation of machine tools. PLC has relatively strong reliability, stability, and flexibility and is widely used in industrial control systems. In the production process of CNC machine tools, the application of PLC can improve the automatic control level of machine tools. The application of PLC can improve the automatic control level of machine tools and realize the effective control of each link in the production process of CNC machine tools, such as the start-stop program, the automatic replacement of cutting tools in the production process, the automatic diagnosis, and treatment of various faults in the production process, which can be realized through the application of PLC technology.

Study on Model and Experimental of Laser Scribing Parameter of Maskant in Chemical Milling for Aerospace Applications

In order to solve the problems of multiple process parameters, difficult control and high process requirements in laser first/second scribing of aerospace chemical milling thin-wall parts, a laser scribing depth model based on thermal energy balance was established, and the relationship between laser power and speed was established with scribing depth as a target. Using AC850 laser scribing maskant as coating material, the effects of laser power, scribing speed, laser frequency, forward angle and side slope angle on the scribing depth were studied by single factor experiment. Experimental results show that the theoretical model is in good agreement with experimental data. The laser scribing depth is positively proportional to the laser power and inversely proportional to the laser speed and has little relationship with the laser frequency. The predicted accuracy of the mathematical equations regarding the laser power density and scribing depth, calculated by the laser power, speed and scribing depths experimental data, are 88.53% and 90.79%. The laser scribing depth at a forward angle of 6° and a side slope angle of 7° is deeper compared with the vertical incident scribing depth, and the angle is also the recommended angle of laser scribing. Based on the simplified regression model, the laser scribing depth model can be directly used in the laser NC system to realize the adaptive adjustment and accurate control of laser energy according to the actual laser speed.

Effect of NC System Functions on Profile Contouring of Machining Center

Effect of NC System Functions on Profile Contouring of Machining Center

A design of machine tool for switchable multi-NC systems test

A machine tool with 4 kinds of NC systems have been designed. The systems can control the same transmission mechanism and switch freely. The machine tool mainly used for the test of NC system function and performance. At present, the machine tool has been tested. The results show that the functions and performances of different NC systems can be compared and tested under the same condition of transmission mechanism.

An attempt to relate dynamic tracking error to occurring situation based on additional rectilinear motion for five-axis machine tools

During five-axis CNC machining, the dynamic tracking error of the five-axis machine tool caused by imperfect servo dynamic performance is the major factor affecting the accuracy during high-speed and high-precision manufacturing. Rotation tool center point (RTCP) test has become a typical kinematic test for the dynamic tracking error of five-axis machine tools. According to the mechanism and characteristics of dynamic tracking error, during the RTCP test, relating the measured dynamic tracking error to corresponding occurring situation is helpful for the research of calibration or reduction of dynamic tracking error. In this paper, a new method to relate dynamic tracking error to occurring situation based on additional rectilinear motion is attempted. During this method, rectilinear motions are added into the RTCP test process, and the dynamic tracking error and corresponding occurring position can be calculated from the scale of rectilinear motion. By six tests with rectilinear motions in and against X, Y and Z directions, the additional error and uncertainty of the test process can be offset by calculation. This method can be implemented without any addition or modification to the instrument or NC system.

An adaptive real-time NURBS curve interpolation for 4-axis polishing machine tool

The non-uniform rational B-spine (NURBS) curve interpolation is a key technology of the advanced computer numerical control (CNC) system. NURBS curve interpolation can realize a high-speed and high-precision machining, and it can also avoid some inevitable deficiencies of the linear and circular interpolation functions which are generally used in traditional NC system. Before the interpolation, some calculation tasks are finished, which will decrease the amount of calculation during interpolation and increase the interpolation efficiency. Further, an adaptive NURBS curve interpolation with real-time and flexible S-shaped curve acceleration/deceleration (ACC/DEC) control method is added to the interpolation algorithms. The NC machining simulation conducted with the MATLAB software and the NURBS curve interpolation experiments performed on the 4-axis polishing machine tool demonstrate the validity and correctness of the adaptive real-time NURBS curve interpolation algorithm in the CNC system.

Interface Design Technology and Verification of Intelligent Manufacturing Oriented CNC System

Objective With the proposal of German Industry 4.0, intelligent manufacturing has become the main direction of manufacturing technology development. In recent years, CNC technology industry for intelligent manufacturing has developed rapidly in China, and it has been widely used in various fields of manufacturing industry. Among them, the design of man-machine interface for system appearance is closely related to the operation mechanism of internal functions with high specialization and complexity, which has attracted more and more attention from the industry and designers. Therefore, the design method and key points of the human-machine interface of NC system will be discussed for intelligent manufacturing, and the technical verification will be made. Method The interface design requirements of intelligent manufacturing oriented CNC system were systematically analyzed, and the corresponding design techniques and key points were given. The specific design scheme and verification of Huazhong 9 interface design of Huazhong CNC were discussed based on a specific design case. Conclusion It is hoped that the design of man-machine interaction interface of intelligent manufacturing CNC system can be optimized and improved, and that a little contribution can be made to the CNC technology industry in China.

Path planning of manipulator based on acceleration and deceleration control of two-phase adaptive path

In this paper, the key technology in NC system, acceleration and deceleration control, is applied to path planning of manipulator. A two-phase adaptive path acceleration and deceleration control method is proposed, which reduces the requirement of S-shaped curve acceleration and deceleration control method on the shortest path length, and improves the smoothness of trapezoidal acceleration and deceleration control. On the whole, it improves the rapidity of accurately reaching the target position and the smoothness of manipulator’s movement.

External Validation of an Algorithm to Identify Patients with High Data-Completeness in Electronic Health Records for Comparative Effectiveness Research.

ObjectiveElectronic health records (EHR) data-discontinuity, i.e. receiving care outside of a particular EHR system, may cause misclassification of study variables. We aimed to validate an algorithm to identify patients with high EHR data-continuity to reduce such bias.Materials and MethodsWe analyzed data from two EHR systems linked with Medicare claims data from 2007 through 2014, one in Massachusetts (MA, n=80,588) and the other in North Carolina (NC, n=33,207). We quantified EHR data-continuity by Mean Proportion of Encounters Captured (MPEC) by the EHR system when compared to complete recording in claims data. The prediction model for MPEC was developed in MA and validated in NC. Stratified by predicted EHR data-continuity, we quantified misclassification of 40 key variables by Mean Standardized Differences (MSD) between the proportions of these variables based on EHR alone vs the linked claims-EHR data.ResultsThe mean MPEC was 27% in the MA and 26% in the NC system. The predicted and observed EHR data-continuity was highly correlated (Spearman correlation=0.78 and 0.73, respectively). The misclassification (MSD) of 40 variables in patients of the predicted EHR data-continuity cohort was significantly smaller (44%, 95% CI: 40–48%) than that in the remaining population.DiscussionThe comorbidity profiles were similar in patients with high vs low EHR data-continuity. Therefore, restricting an analysis to patients with high EHR data-continuity may reduce information bias while preserving the representativeness of the study cohort.ConclusionWe have successfully validated an algorithm that can identify a high EHR data-continuity cohort representative of the source population.