A Study on Yield Criteria Influence on Anisotropic Behavior and Fracture Prediction in Deep Drawing SECC Steel Cylindrical Cups.

The deep drawing process, a pivotal technique in sheet metal forming, frequently encounters challenges such as anisotropy-induced defects. This study comprehensively investigates the influence of various yield criteria on the anisotropic behavior and fracture prediction in SECC steel cylindrical cups. It integrates Hill'48R, Hill'48S, and von Mises yield criteria in conjunction with Swift's hardening law to evaluate material behavior under complex stress states. Experimental and numerical simulations assess the anisotropy effects across multiple orientations (0°, 45°, and 90°), revealing intricate relationships between stress criteria and material response. The findings indicate significant discrepancies between isotropic and anisotropic models in predicting fracture heights, emphasizing the importance of selecting appropriate yield criteria. Notably, the von Mises criterion results in lower fracture heights, suggesting higher susceptibility to fractures, while the Hill'48R model aligns closely with experimental data, validated through variations in punch corner radius and blank holder force parameters, with a maximum deviation of 3.23%. Hill'48S displays moderate plastic deformation characteristics.

Improving Micro-EDM Machining Efficiency for Titanium Alloy Fabrication with Advanced Coated Electrodes.

Enhancing the operational efficacy of electrical discharge machining (EDM) is crucial for achieving optimal results in various engineering materials. This study introduces an innovative solution-the use of coated electrodes-representing a significant advancement over current limitations. The choice of coating material is critical for micro-EDM performance, necessitating a thorough investigation of its impact. This research explores the application of different coating materials (AlCrN, TiN, and Carbon) on WC electrodes in micro-EDM processes specifically designed for Ti-6Al-4V. A comprehensive assessment was conducted, focusing on key quality indicators such as depth of cut (Z), tool wear rate (TWR), overcut (OVC), and post-machining surface quality. Through rigorous experimental methods, the study demonstrates substantial improvements in these quality parameters with coated electrodes. The results show significant enhancements, including increased Z, reduced TWR and OVC, and improved surface quality. This evidence underscores the effectiveness of coated electrodes in enhancing micro-EDM performance, marking a notable advancement in the precision and quality of Ti-6Al-4V machining processes. Among the evaluated coatings, AlCrN-coated electrodes exhibited the greatest increase in Z, the most significant reduction in TWR, and the best OVC performance compared to other coatings and the uncoated counterpart.

Base- and sulfur-promoted oxidative lactonization of chalcone-acetate Michael adducts: access to pyran-2-ones.

A cost-effective, practical, straightforward and scalable synthesis of α-pyrones via base- and sulfur-promoted annulation of phenylacetates and chalcones is reported. Generated in situ from the starting components by using dbu as a base catalyst, the Michael adducts underwent a smooth oxidative cyclization into 3,4,6-triaryl-2-pyranones upon heating with DABCO and sulfur in DMSO. Extension to malonate in place of phenylacetates led to 4,6-diaryl-2-pyranone-2-carboxylates.

Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows.

This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices.

Enhancing/Improving Forming Limit Curve and Fracture Height Predictions in the Single-Point Incremental Forming of Al1050 Sheet Material.

Single-point incremental forming (SPIF) has emerged as a cost-effective and rapid manufacturing method, especially suitable for small-batch production due to its minimal reliance on molds, swift production, and affordability. Nonetheless, SPIF's effectiveness is closely tied to the specific characteristics of the employed sheet materials and the intricacies of the desired shapes. Immediate experimentation with SPIF often leads to numerous product defects. Therefore, the pre-emptive use of numerical simulations to predict these defects is of paramount importance. In this study, we focus on the critical role of the forming limit curve (FLC) in SPIF simulations, specifically in anticipating product fractures. To facilitate this, we first construct the forming limit curve for Al1050 sheet material, leveraging the modified maximum force criterion (MMFC). This criterion, well-established in the field, derives FLCs based on the theory of hardening laws in sheet metal yield curves. In conjunction with the MMFC, we introduce a graphical approach that simplifies the prediction of forming limit curves at fracture (FLCF). Within the context of the SPIF method, FLCF is established through both uniaxial tensile deformation (U.T) and simultaneous uniform tensile deformation in bi-axial tensile (B.T). Subsequently, the FLCF predictions are applied in simulations and experiments focused on forming truncated cone parts. Notably, a substantial deviation in fracture height, amounting to 15.97%, is observed between simulated and experimental samples. To enhance FLCF prediction accuracy in SPIF, we propose a novel method based on simulations of truncated cone parts with variable tool radii. A FLCF is then constructed by determining major/minor strains in simulated samples. To ascertain the validity of this enhanced FLCF model, our study includes simulations and tests of truncated cone samples with varying wall angles, revealing a substantial alignment in fracture height between corresponding samples. This research contributes to the advancement of SPIF by enhancing our ability to predict and mitigate product defects, ultimately expanding the applicability of SPIF in diverse industrial contexts.

Novel model predictive control-based motion cueing algorithm for compensating centrifugal acceleration in KUKA robocoaster-based driving simulators.

The washout motion cueing algorithm (MCA) is a critical element in driving simulators, designed to faithfully reproduce precise motion cues while minimizing false cues during simulation processes, particularly deceptive translational and rotational cues. To enhance motion sensation accuracy and optimize the use of available workspace, model predictive control (MPC) has been employed to develop innovative motion cueing algorithms. While most MCAs have been tailored for the Steward motion platform, there has been a recent adoption of the motion platform based on KUKA Robocoaster as an economical option for driving simulators. However, leveraging the full potential of the KUKA Robocoaster requires trajectory conversion of the motion base. Thus, this research proposes a novel MCA specifically designed for the KUKA Robocoaster-based motion platform, utilizing large planar circular motion to simulate lateral movement for drivers. Nonetheless, circular motion introduces disruptive centrifugal forces, which can be mitigated through proper pitch-tilted angles. The novel MPC generates simulated motion that accurately follows the lateral specific force target and effectively maintains the roll angular velocity below its threshold value. Additionally, it compensates for disturbing centrifugal acceleration by implementing pitch rotational motion, ensuring the pitch angular velocity remains below its threshold. Simulation tasks conducted on the motion platform, focusing solely on lateral acceleration, demonstrate the successful elimination of false motion cues in both the roll/sway and pitch/surge channels. The proposed innovative MPC solution offers an original approach to motion cueing algorithms in KUKA Robocoaster-based driving simulators. It enables the exploitation of the KUKA Robocoaster platform's capabilities while delivering accurate and immersive motion cues to drivers during simulation experiences.

Case Study: Improving the Quality of Dairy Cow Reconstruction with a Deep Learning-Based Framework.

Three-dimensional point cloud generation systems from scanning data of a moving camera provide extra information about an object in addition to color. They give access to various prospective study fields for researchers. With applications in animal husbandry, we can analyze the characteristics of the body parts of a dairy cow to improve its fertility and milk production efficiency. However, in the depth image generation from stereo data, previous solutions using traditional stereo matching algorithms have several drawbacks, such as poor-quality depth images and missing information in overexposed regions. Additionally, the use of one camera to reconstruct a comprehensive 3D point cloud of the dairy cow has several challenges. One of these issues is point cloud misalignment when combining two adjacent point clouds with the small overlapping area between them. In addition, another drawback is the difficulty of point cloud generation from objects which have little motion. Therefore, we proposed an integrated system using two cameras to overcome the above disadvantages. Specifically, our framework includes two main parts: data recording part applies state-of-the-art convolutional neural networks to improve the depth image quality, and dairy cow 3D reconstruction part utilizes the simultaneous localization and calibration framework in order to reduce drift and provide a better-quality reconstruction. The experimental results showed that our approach improved the quality of the generated point cloud to some extent. This work provides the input data for dairy cow characteristics analysis with a deep learning approach.

Auto-Tuning parameters of motion cueing algorithms for high performance driving simulator based on Kuka Robocoaster.

Driving simulators have been utilized to test and evaluate products and services for a long time. Their complexity and price range from extremely simple low-cost simulators with a fixed base to very complex high-end and pricey six-degree-of-freedom simulators with the XY table. The recent novel technique that uses an industrial robot - KUKA Robocoaster - as an interactive motion simulator platform, allowing for a highly flexible workspace as well as significantly lower prices due to mass production of the fundamental mechanics. In the constrained workspace of driving simulators, motion cueing algorithms (MCAs) are commonly employed to merge the tilt gravity and translational acceleration components for simulating the linear acceleration in the real vehicle. However, there is a few MCAs developed for the motion platform, almost MCAs were implemented for the standard six-degree-of-freedom simulators in the Cartesian coordinate. The classical MCA in the cylindrical coordinate (ClCy) MCA was first developed for the novel motion platform to take advantage of enormous rotational motion to simulate lateral acceleration while compensating for the bothersome longitudinal acceleration (due to centrifugal acceleration appearing in the rotational motion) with a proper pitch tilted angle. The process of tuning MCAs for the novel motion platform is time-consuming due to both trial and error method and the disturbing motion cues generated by rotational motion, thus it needs the involvement of experts. Although there are several auto-tuning approaches for classical, optimal, and model-predictive control MCA based on fuzzy control theory or genetic optimization method, the methods were purely applied for Cartersian coordinate without taking the bothersome longitudinal acceleration into account. Therefore, this paper firstly presents the process of integrating MCAs in the novel motion platform utilizing rotational motion for simulating lateral acceleration. For the case, besides the ClCy algorithm, the classical algorithm developed for the standart six-degree-of-freedom simulators was a sample implementation due to its popular and familiar characteristics. Secondly, the proposal of the use of the mean-variance mapping optimization (MVMO) for auto-tuning parameters of the two algorithms for reducing both rotational false cues in roll and pitch channel, and longitudinal acceleration as well as washout effect. The simulation results prove that 1) The classical and other MCAs can be applied in the novel motion platform with the proposed motion conversion; 2) both algorithms with auto-tuned parameters have high performance in exploiting effectively the workspace of the motion platform, producing no false cues of angular velocity, conpensating the disturbed longitudinal acceleration, and pulling the motion platform to the initial position after the simulation task; 3) The auto-tuning method is so transparent that can manipulates the specific simulated quantities according to the tuning goals.

Preparation and Photocatalytic Characterization of Modified Nano TiO2/Nd/Rice Husk Ash Material for Rifampicin Removal in Aqueous Solution.

Antibiotics like rifampicin are often persistent in the environment. When entering the water, it causes antimicrobial resistance that affects the ecosystem and accumulates in the aquatic organisms and affects human health through the food chain. In this study, titanium dioxide was doped with neodymium (0.01 to 0.8%) using the sol-gel hydrothermal method. TiO2/Nd was then coated on rice husk ash to produce a modified TiO2/Nd/rice husk ash material containing 0.36% (w/w) Nd. The structural characteristics and photocatalytic properties of the materials were analyzed by X-ray diffraction, energy dispersive X-ray, transmission electron microscopy, scanning electron microscopy, forbidden zone energy, and specific surface area. The TiO2/Nd material exhibited a higher photocatalytic decomposition capacity than TiO2 and depended on the Nd content. The rifampicin removal efficiency of TiO2/Nd materials with 0.36 to 0.80% Nd contents was approximately 40% higher than that of TiO2/Nd containing 0.01 to 0.28% Nd. A new photocatalytic TiO2/Nd/rice husk ash material was developed to decompose rifampicin. The rifampicin-degrading efficiency of TiO2/Nd and TiO2/Nd/rice husk ash material reached approximately 86 and 75%, respectively, within 90 min under sunlight. Although a lower efficiency was obtained, the TiO2/Nd/rice husk ash material was selected to degrade rifampicin residue in water via the photocatalytic process (under sunlight) because of its advantages such as requirement of a small amount and easy recovery. In the rifampicin removal process, k values were found to match the zero- and first-order kinetics. In particular, for TiO2/Nd and TiO2/Nd/rice husk ash under solar irradiation, R 2 values reached approximately 0.98. These results have been previously published as a preprint.

False cue influence on motion cue quality for 10 motion cueing algorithms.

Motion simulators are becoming increasingly popular for many applications in which human sensation is important to replicate and optimize target motions. For the emulation of the perceived human acceleration, motion cueing algorithms (MCAs) have been proposed in the literature that mimics the motion sensation by a combination of actual acceleration and tilted gravity effects, termed g-force or specific force. However, their relative performance has not yet been analyzed. This paper reviews existing families of MCAs and compares their performance for a simple offline S-shaped planar test trajectory featuring only lateral acceleration. The comparison is carried out both numerically using two previously published objective measures, the "performance indicator" of Pouliot, Gosselin, and Nahon, and the "good criterion" of Schmidt, as well as subjectively by a preliminary passenger rating on a real motion platform-Robocoaster testbed. The results show that (a) the novel optimizing MCA group exploits more effectively the workspace of the motion platform than the traditional MCA group for reducing false cue with small scale error and shape errors, (b) path-dependent tuning of MCA parameters may improve motion sensation, (c) average subjective ratings can be made to correlate well with the "good criterion" when expanded with a penalty for false angular velocity cues, and (d) the scale error of specific force seems to play the most important role to the evaluation of test subject on the motion cue quality. However, still a strong variance in subjective ratings was observed, making further research necessary.

Optical Properties of Doxorubicin Hydrochloride Load and Release on Silica Nanoparticle Platform.

Silica nanoparticles (SiO2 NPs) synthesized by the Stober method were used as drug delivery vehicles. Doxorubicin hydrochloride (DOX·HCl) is a chemo-drug absorbed onto the SiO2 NPs surfaces. The DOX·HCl loading onto and release from the SiO2 NPs was monitored via UV-VIS and fluorescence spectra. Alternatively, the zeta potential was also used to monitor and evaluate the DOX·HCl loading process. The results showed that nearly 98% of DOX·HCl was effectively loaded onto the SiO2 NPs' surfaces by electrostatic interaction. The pH-dependence of the process wherein DOX·HCl release out of DOX·HCl-SiO2 NPs was investigated as well. For comparison, both the free DOX·HCl molecules and DOX·HCl-SiO2 NPs were used as the labels for cultured cancer cells. Confocal laser scanning microscopy images showed that the DOX·HCl-SiO2 NPs were better delivered to cancer cells which are more acidic than healthy cells. We propose that engineered DOX·HCl-SiO2 systems are good candidates for drug delivery and clinical applications.

Role of Nanoimprint Lithography for Strongly Miniaturized Optical Spectrometers.

Optical spectrometers and sensors have gained enormous importance in metrology and information technology, frequently involving the question of size, resolution, sensitivity, spectral range, efficiency, reliability, and cost. Nanomaterials and nanotechnological fabrication technologies have huge potential to enable an optimization between these demands, which in some cases are counteracting each other. This paper focuses on the visible and near infrared spectral range and on five types of optical sensors (optical spectrometers): classical grating-based miniaturized spectrometers, arrayed waveguide grating devices, static Fabry-Pérot (FP) filter arrays on sensor arrays, tunable microelectromechanical systems (MEMS) FP filter arrays, and MEMS tunable photonic crystal filters. The comparison between this selection of concepts concentrates on (i) linewidth and resolution, (ii) required space for a selected spectral range, (iii) efficiency in using available light, and (iv) potential of nanoimprint for cost reduction and yield increase. The main part of this review deals with our own results in the field of static FP filter arrays and MEMS tunable FP filter arrays. In addition, technology for efficiency boosting to get more of the available light is demonstrated.

Restoration of Polyamine Metabolic Patterns in In Vivo and In Vitro Model of Ischemic Stroke following Human Mesenchymal Stem Cell Treatment.

We investigated changes in PA levels by the treatment of human bone-marrow-derived mesenchymal stem cells (hBM-MSCs) in ischemic stroke in rat brain model and in cultured neuronal SH-SY5Y cells exposed to oxygen-glucose deprivation (OGD). In ischemic rat model, transient middle cerebral artery occlusion (MCAo) was performed for 2 h, followed by intravenous transplantation of hBM-MSCs or phosphate-buffered saline (PBS) the day following MCAo. Metabolic profiling analysis of PAs was examined in brains from three groups: control rats, PBS-treated MCAo rats (MCAo), and hBM-MSCs-treated MCAo rats (MCAo + hBM-MSCs). In ischemic cell model, SH-SY5Y cells were exposed to OGD for 24 h, treated with hBM-MSCs (OGD + hBM-MSCs) prior to continued aerobic incubation, and then samples were collected after coculture for 72 h. In the in vivo MCAo ischemic model, levels of some PAs in brain samples of the MCAo and MCAo + hBM-MSCs groups were significantly different from those of the control group. In particular, putrescine, cadaverine, and spermidine in brain tissues of the MCAo + hBM-MSCs group were significantly reduced in comparison to those in the MCAo group. In the in vitro OGD system, N (1)-acetylspermidine, spermidine, N (1)-acetylspermine, and spermine in cells of the OGD + hBM-MSCs group were significantly reduced compared to those of OGD group.

Quantitative measurement of organic acids in tissues from gastric cancer patients indicates increased glucose metabolism in gastric cancer.

The levels of organic acids representing metabolic pathway end products are important indicators of physiological status, and may be associated with metabolic changes in cancer. The aim of this study is to investigate the levels of organic acids in cancerous and normal tissues from gastric cancer patients and to confirm the role of metabolic alterations in gastric carcinogenesis. Organic acids in normal and cancerous tissues from forty-five patients with gastric adenocarcinoma were investigated by gas chromatography-mass spectrometry in selected ion monitoring mode as methoxime/tert-butyldimethylsilyl derivatives. We analysed the significant differences in the levels of organic acids in normal and cancer tissues and investigated the correlation of these levels in cancer tissues with clinicopathological features. The levels of Krebs cycle components, including α-ketoglutaric acid, succinic acid, fumaric acid, malic acid and oxaloacetic acid, were significantly increased in cancer tissues compared to normal tissues. In addition, the levels of glycolytic products, including pyruvic acid and lactic acid, as well as the levels of ketone bodies, including 3-hydroxybutyric acid, were also significantly increased in cancer tissues compared to normal tissues. The levels of ketone bodies in cancer tissues with differentiated histology and in intestinal-type cancer tissues were significantly increased. The organic acid profiling analysis described here may be a generally useful clinical tool for understanding the complexity of metabolic events in gastric adenocarcinoma, and organic acids may have potential as metabolic markers for the future discovery of diagnostic and therapeutic modalities.

Correlation of daytime sleepiness with urine metabolites in patients with obstructive sleep apnea.

PURPOSE: The apnea-hypopnea index (AHI) is closely related with the severity of daytime sleepiness, but excessive daytime sleepiness (EDS) is not presented on all patients with obstructive sleep apnea (OSA). It is unclear why daytime sleepiness is not always present in OSA patients even if their sleep is disrupted from the perspective of polysomnographic findings. This study aimed to analyze the correlation between sleepiness and urine metabolites of neurotransmitters involved in the arousal system. METHODS: On the basis of AHI in polysomnography, 49 consecutive OSA patients were included. According to their Epworth sleepiness scale (ESS), 23 non-sleepy patients (ESS <11) and 26 sleepy patients (ESS ≥11) were included. Urine samples were collected before and after polysomnography and analyzed by gas chromatography-mass spectrometry with selective ion monitoring. Six metabolites of dopamine, norepinephrine and serotonin were analyzed. RESULTS: The dopamine metabolites, homovanillic acid (r = 0.366, P = 0.017) and 3,4-dihydroxyphenylacetic acid (DOPAC; r = 0.584, P < 0.0001), were significantly correlated with ESS after adjusting for age, sex, body mass index, AHI, sleep efficiency and total sleep time. A two-by-two table analysis revealed that the overnight increase in the urine DOPAC was more frequent in sleepy patients while its decrease was more frequent in non-sleepy patients (odds ratio = 3.54, P = 0.032). CONCLUSION: Urine dopamine metabolites may identify sleepy patients with OSA. In particular, the overnight change of urine DOPAC may indicate OSA patients with EDS.

Keto acid profiling analysis as ethoxime/tert-butyldimethylsilyl derivatives by gas chromatography-mass spectrometry.

Organic acids, including keto acids, are key intermediates of central pathways in cellular metabolism. In this study, a comprehensive and reliable method was developed and optimized for the simultaneous measurement of 17 keto acids in various biological samples. The keto acids were converted to solvent extractable forms by ethoximation followed by tert-butyldimethylsilylation for direct analysis by gas chromatography-mass spectrometry in selected ion monitoring mode. The proposed method was precise (0.05-8.3, % RSD) and accurate (-10.5 to 5.3, % RE) with low limit of detection (0.01-0.5ng/mL) and good linearity (r>0.995) in the range of 0.01-5.0µg/mL. This was suitable for profiling analysis of targeted keto acids in human plasma, urine and rat brain tissue.

Acidic metabolite profiling analysis of catecholamine and serotonin as O-ethoxycarbonyl/tert-butyldimethylsilyl derivatives by gas chromatography-mass spectrometry.

A novel derivatization method was developed for the simultaneous determination of six acidic metabolites of catecholamine and serotonin by gas chromatography-mass spectrometry (GC-MS). The metabolites were converted to O-ethoxycarbonyl/tert-butyldimethylsilyl (EOC/TBDMS) derivatives for the direct GC-MS analysis in selected ion monitoring mode. Their mass spectral pattern as EOC/TBDMS derivatives showed characteristic fragment ions of [M - 15](+) and [M - 57](+), which permitted rapid and accurate structural confirmation of acidic metabolites. The present method was linear (r ≥ 0.998), reproducible (percentage relative standard deviation = 1.0-10.0) and accurate (% relative error = -9.7-9.8) with detection limits of 0.001-4.7 ng/mL. When applied to human urine samples, the method allowed simultaneous determination of six acidic metabolites of catecholamine and serotonin.

Analysis of changes in gene expression and metabolic profiles induced by silica-coated magnetic nanoparticles.

Magnetic nanoparticles (MNPs) have proven themselves to be useful in biomedical research; however, previous reports were insufficient to address the potential dangers of nanoparticles. Here, we investigated gene expression and metabolic changes based on the microarray and gas chromatography-mass spectrometry with human embryo kidney 293 cells treated with MNPs@SiO(2)(RITC), a silica-coated MNP containing Rhodamine B isothiocyanate (RITC). In addition, measurement of reactive oxygen species (ROS) and ATP analysis were performed to evaluate the effect of MNPs@SiO(2)(RITC) on mitochondrial function. Compared to the nontreated control, glutamic acid was increased by more than 2.0-fold, and expression of genes related to the glutamic acid metabolic pathway was also disturbed in 1.0 µg/µL of MNPs@SiO(2)(RITC)-treated cells. Furthermore, increases in ROS concentration and mitochondrial damage were observed in this MNPs@SiO(2)(RITC) concentration. The organic acids related to the Krebs cycle were also disturbed, and the capacity of ATP synthesis was decreased in cell treated with an overdose of MNPs@SiO(2)(RITC). Collectively, these results suggest that overdose (1.0 µg/µL) of MNPs caused transcriptomic and metabolic disturbance. In addition, we suggest that a combination of gene expression and metabolic profiles will provide more detailed and sensitive toxicological evaluation for nanoparticles.

Chiral separation of N-methyl-DL-aspartic acid in rat brain tissue as N-ethoxycarbonylated (S)-(+)-2-octyl ester derivatives by GC-MS.

A selective and sensitive analytical method was developed for enantiomeric separation and determination of N-methyl-DL-aspartic acid (NMA). The method involved the conversion of each enantiomer into N-ethoxycarbonylated (S)-(+)-2-octyl ester derivative for the direct separation by gas chromatography-mass spectrometry (GC-MS). The diastereomeric derivatives showed characteristic mass spectral properties for analysis by selected ion monitoring mode (SIM) and enabling enantioseparation on an achiral capillary column. Two enantiomers were baseline separated, and the detection limits for N-methyl-L-aspartic acid (NMLA) and N-methyl-D-aspartic acid (NMDA) were 0.07 and 0.03 ng/g, respectively. When applied to rat brain tissues for absolute configuration of NMA, only NMDA was determined, while NMLA was monitored as lower than the limit of detection.

N-Menthoxycarbonylation combined with trimethylsilylation for enantioseparation of beta-blockers by achiral dual-column gas chromatography.

Solvent extractive two-phase menthoxycarbonyl (MnOC) derivatization was combined with trimethylsilyl (TMS) reaction for enantioseparation of beta-blockers by gas chromatography employing achiral DB-5 and DB-17 dual-columns of different polarity. beta-Blockers in alkaline solution were vortex-mixed with menthyl chloroformate present in dichloromethane to be extracted as diastereomeric N-MnOC derivatives. The subsequent O(N)-TMS reaction allowed complete enantioseparations of two beta-blockers and partial separations of five as N-MnOC/O(N)-TMS derivatives in a single analysis. The temperature-programmed retention index sets were characteristic of each derivative, facilitating chiral discrimination of each enantiomer.