High-field Mobility Research Articles

Application and performance enhancement of FAIMS spectral data for deep learning analysis using generative adversarial network reinforcement

When using High-field asymmetric ion mobility spectrometry (FAIMS) to process complex mixtures for deep learning analysis, there is a problem of poor recognition performance due to the lack of high-quality data and low sample diversity. In this paper, a Generative Adversarial Network (GAN) method is introduced to simulate and generate highly realistic and diverse spectral for expanding the dataset using real mixture spectral data of 15 classes collected by FAIMS. The mixed datasets were put into VGG and ResNeXt for testing respectively, and the experimental results proved that the best recognition effect was achieved when the ratio of real data to generated data was 1:4: where accuracy improved by 24.19 % and 6.43 %; precision improved by 23.71 % and 6.97 %; recall improved by 21.08 % and 7.09 %; and F1-score improved by 24.50 % and 8.23 %. The above results strongly demonstrate that GAN can effectively expand the data volume and increase the sample diversity without increasing the additional experimental cost, which significantly enhances the experimental effect of FAIMS spectral for the analysis of complex mixtures.

Theoretical and experimental study on the effect of scanning speed on FAIMS peaks

High-Field Asymmetric Ion Mobility Spectrometry (FAIMS) is a technique for ion separation and detection based on ion mobility variation under high electronic field. While compensation voltage scanning speed is a fundamental parameter in FAIMS, its impact on spectra remains unclear. In this work, a function referred to as F-EMG is introduced to describe the impact of compensation voltage scanning speed on FAIMS spectra, and the properties of the function are studied. Theoretical analysis emphasizes the impact of the scanning speed on peak height, position, and symmetry, as well as the capability of the F-EMG function to progressively approach Gaussian function at lower scanning speeds. Furthermore, the function indicates that spectra obtained in positive and negative scanning modes exhibits symmetry. An experimental validation, conducted with a custom FAIMS setup and analyzing hydrogen sulfide, ethylbenzene, toluene, styrene, benzene and ammonia, confirms the model's influence on peak features, fitting accuracy, and exhibits a closer alignment with the Gaussian function at lower scanning speeds. Additionally, the experimental data indicate that the spectra show symmetry in positive and negative scanning models. This work not only improves understanding of FAIMS spectral analysis but also introduces a robust method for enhancing data accuracy across varying scanning speeds.

Differentiating enantiomers by directional rotation of ions in a mass spectrometer

Conventional mass spectrometry does not distinguish between enantiomers, or mirror-image isomers. Here we report a technique to break the chiral symmetry and to differentiate enantiomers by inducing directional rotation of chiral gas-phase ions. Dual alternating current excitations were applied to manipulate the motions of trapped ions, including the rotation around the center of mass and macro movement around the center of the trap. Differences in collision cross section were induced, which could be measured by ion cloud profiling at high resolutions above 10,000. High-field ion mobility and tandem mass spectrometry analyses of the enantiomers were combined and implemented by using a miniature ion trap mass spectrometer. The effectiveness of the developed method was demonstrated with a variety of organic compounds including amino acids, sugars, and several drug molecules, as well as a proof-of-principle ligand optimization study for asymmetric hydrogenation.

A broad-spectrum peptide screening method using an optimized solid-phase extraction and liquid chromatography-high-field asymmetric ion mobility spectrometry-mass spectrometry for doping control in equine urine.

The abuse of prohibited peptide-based drugs with a broad spectrum of chemical characteristics poses a significant concern for the horseracing industry. Recently, there has been a notable increase in positive cases of small-peptide drugs reported in equine and canine sports. In addition to small peptides, large peptides (over 2 kDa) with structural diversity have also entered the market in increasing numbers as drugs for humans and livestock. However, the simultaneous analysis of both small- and large-peptide-based drugs is still challenging. In this study, a screening method was developed to cover 74 analytes, including peptides, their catabolites, and/or their mimetics, with molecular weights ranging from 0.3 kDa to greater than 5 kDa. The simultaneous extraction of both small and large peptides was achieved using a weak cation-exchange solid-phase extraction cartridge with a mixture of different pore sizes (suitable for large peptides), followed by analysis using liquid chromatography high-field asymmetric ion mobility spectrometry tandem mass spectrometry (LC-FAIMS-MS/MS). For method validation, the limits of detection (LoDs), reproducibility, recovery, matrix effect, selectivity, and carryover were evaluated. Remarkably, the LoDs of ∼80% of the analytes were less than or equal to 50 pg ml-1, with the lowest LoD (1 pg ml-1) being observed for selected peptides in horse urine. These results indicate a substantial advancement in achieving comprehensive coverage for both small and large peptides with high sensitivity for the purpose of doping control in horseracing and equestrian sports.

Application and integration of deep learning in FAIMS for identifying acetone concentration

In practical applications, analytical instruments are used for both qualitative and quantitative analysis. However, for high-field asymmetric-waveform ion mobility spectrometry (FAIMS), most studies to date have been focused on the qualitative analysis of substances, with limited research on quantitative analysis. Explored here is the feasibility of using deep learning in FAIMS for quantitative analysis, aided by redesigning the FAIMS upper computer. Integrating spectrum creation and deep learning analysis into the FAIMS upper computer boosts the processing and analysis of FAIMS data, laying a foundation for applying FAIMS practically. For analysis using image processing, multiple FAIMS spectral lines obtained under different conditions are converted into a three-dimensional thermodynamic map known as a FAIMS spectrum, and multiple FAIMS spectrum are preprocessed to obtain the data set of this experiment. The principles of partial-least-squares regression and the XGBoost and ResNeXt models are introduced in detail, and the data are analyzed using these models, while exploring the effects of different model parameters and determining their optimal values. The experimental results show that the pre-trained ResNeXt deep learning model performs the best on the test set, with a root mean square error of 0.86 mg/mL, indicating the potential of deep learning in realizing quantitative analysis of substances in FAIMS.

7.86 kV GaN-on-GaN PN power diode with BaTiO3 for electrical field management

Devices based on gallium nitride (GaN) have great potential for high power switching applications due to the high breakdown field and high electron mobility. In this work, we present a vertical GaN-on-GaN PN power diode using high dielectric constant material, BaTiO3, for electrical field management and high breakdown voltages, in together with an optimized guard-ring and field plate design. Numerical simulation shows that with high-k dielectrics implemented, the peak electrical field at the PN interface is mitigated from 3.5 to 3.1 MV/cm under a reverse bias of −9.05 kV. The device design with BaTiO3 shows a breakdown voltage of 9.65 kV or about 600 V improvement. The fabricated diodes with a 57 μm thick drift layer demonstrate a breakdown voltage of 7.86 kV on a bulk GaN substrate. The device has an on-resistance of 2.8 mΩ cm2 and a Baliga figure of merit of 22 GW/cm2.

Rapid method for accurate peak position extraction in high-field asymmetric ion mobility spectrometry

Rapid method for accurate peak position extraction in high-field asymmetric ion mobility spectrometry

Molecular Dynamics-Based Modeling of Ion-Neutral Collisions in an Open Ion Trajectory Simulation Framework.

Ion mobility spectrometry (IMS) and ion mobility mass spectrometry (IMS-MS) methods have become increasingly popular and are important analytical techniques to determine information about the structural parameters of gas-phase analytes. The accurate description of the interaction between molecular ions and neutral background gas particles is an essential part of high-quality simulations of such modern mass- and ion-mobility-spectrometric systems. Established ion-neutral collision models (Hard-sphere collision modeling and statistical diffusion simulations) in common ion-trajectory simulation systems like SIMION use strongly simplified assumptions and are thus limited in their predictive ability. In contrast, collision cross-section (CCS) modeling programs (e.g., MOBCAL, IMoS, and Colloidoscope) allow high-quality ion mobility predictions for low-field equilibrium conditions using explicit scattering processes with a molecular dynamics-based trajectory method but cannot be used for nonequilibrium collision modeling in an ion trajectory simulation. This work presents an extension to the open-source Ion Dynamics Simulation Framework (IDSimF), which allows the simulation of ion dynamics under arbitrary and even nonequilibrium conditions. It was extended by an advanced collision model employing the molecular dynamics trajectory method for a detailed microscopic description of ion-neutral collisions within ion-trajectory simulations. We used drift tube ion mobility spectrometry (DT-IMS) to validate the predictive abilities of the model and to estimate the runtime requirements for productive simulations. Simulated high-field ion mobilities for small ion systems in a drift tube IMS are compared to experimental values from the literature and an implementation of a hard-sphere model in IDSimF for helium and argon as background gas particles. Significant improvements in ion mobility predictions using the molecular dynamics trajectory approach are obtained with deviations of only a few percent from experimental values. Therefore, the established and publicly available MD collision model will serve as foundation for nonequilibrium ion dynamics simulations and the development of improved ion dynamics modeling methods.

3D Lumerical simulation of silicon photodiodes with microholes for high-speed short-reach intra-datacenter interconnects.

3D simulations are conducted using Lumerical software to study the performance of surface illuminated silicon positive-intrinsic-negative photodiodes with microholes. Drift-diffusion equations are solved including the effects of carrier lifetime due to Shockley-Read-Hall and Auger recombination mechanisms, as well as high field mobility. Lumerical's FDTD tool is used to determine the light absorption in the device. The generation profile is imported to Lumerical's CHARGE tool to determine the transient-limited impulse response. An equivalent circuit of the photodiode with microholes is developed for the simulation of an end-to-end high-speed system. Simulation results show an open eye diagram at 50 Gbps for 20µm×20µm devices.

Research progress of optoelectronic devices based on diamond materials

Diamond has a variety of unique characteristics, including integrates mechanics, electricity, heat, optics and other excellent properties, so that it is widely focus on the field of high and new technology, especially in the optoelectronic technology. Because diamond has the characteristics of high thermal conductivity, high breakdown field (10 mV/cm), high electron and hole mobility, it has a wide application prospect in high temperature, high power and high frequency photoelectric equipment. The wide bandgap (5.47 eV) makes diamond an ideal material in ultraviolet detectors (UV). Its high carrier mobility and breakdown field strength make it an ideal choice for field emission materials, which are expected to be used in high-power electronic devices in the next few years. At the same time, in addition to high hardness, it also has various of excellent physical properties, such as low coefficient of thermal expansion, low coefficient of friction, high acoustic propagation speed and high optical transmittance, so that it has broad application prospects in many fields such as machining, microelectronic devices, optical windows and surface coatings. In addition, diamond also has a high exciton binding energy (80 meV), which plays an important development in deep ultraviolet and high-energy particle detectors. In this article, the latest progress in the application of diamond-based optoelectronic devices is reviewed. A variety of advanced devices and physical phenomena are considered, for example, sensors, transistors, memory, Light-emitting diode (LEDs), ultraviolet detectors and field emission. This review will provide a new idea to promote the development of photoelectric applications based on diamond structure.

Influence of metal capping thin film transistor with different Si concentration in ZnSnO

An amorphous metal-oxide semiconductor is emerging as a representative next-generation semiconductor material due to its high electric field mobility, excellent uniformity, and high transmittance in the visible region. The a-SZTO material shows high performance despite its In-free composition. In addition, Si acts as an excellent oxygen vacancy inhibitor to control its electrical properties and stability. Since Si has high binding energy with oxygen, the concentration of oxygen vacancies decreases as the composition of Si increases. As the Si composition increased due to the reduced oxygen vacancies, the mobility, which is an electrical characteristic, decreased from 27.90 cm2/Vs to 17.37 cm2/Vs, and the on current decreased from 7.0 × 10-4 A to 3.9 × 10-4 A, respectively. Amorphous metal-oxide limits improving its electrical properties due to oxygen vacancies by doping. According to the Si concentrations, a metal capping structure was applied to the a-SZTO thin-film transistor. In the metal capping structure, an additional metal rod is inserted between the source and drain electrodes which helps to improve the device characteristics with simple processing techniques. A systematic change was observed in the device by varying the length of the metal capping. The mobility from conventional to MC structures (40 μm) is improved from 27.90 to 86.25 cm2/Vs and 17.36 to 52.91 cm2/Vs for 0 and 1 wt% of Si concentrations, respectively. As for the stability characteristics for NBTS (Negative Bias Thermal Stress), it was confirmed that as the Si concentrations increased, the threshold voltage (Vth) shift decreased from 0.85 V to 0.71 V, and the stability characteristics improved. It has been confirmed that the stability characteristics of these unique channel characteristics (with different Si concentrations) are maintained even when MC TFT is applied. When an inverter logic circuit was manufactured, an excellent voltage gain of 7.47 was obtained using MC.

Investigation of Zero-/High-Field Ion Mobility Orthogonal Separation Using a Hyphenated DMA–FAIMS System and Validation of the Two-Temperature Theory at Arbitrary Field for Tetraalkylammonium Salts in Nitrogen

Toward greater separation techniques for ions, a differential mobility analyzer (DMA) has been coupled with field asymmetric waveform ion mobility spectrometry (FAIMS) to take advantage of two mobility-related but different methods of separation. The filtering effect of the DMA allows ions to be selected individually based on low-field mobility and studied in FAIMS at variable electric field, yielding mobility separations in two dimensions. Because spectra fully describe ion mobility at variable field strength, results are then compared with a two-temperature theory-predicted mobility up to the fourth-order approximation. The comparison yields excellent results up to at least 100 Td, beyond which the theory deviates from experiments. This is attributed to two effects, the enlargement of the structure due to ion heating and the inelasticity of the collisions with the nitrogen bath gas. The corrected mobility can then be used to predict the dispersion plot through a newly developed implicit equation that circumvents the possible issues related to the more elaborate Buryakov equation. Our results simultaneously show that the DMA-FAIMS coupling yields complete information on ion mobility versus the field-strength to gas-density ratio and works toward predicting such spectra from ion structures and gas properties.

Advanced mass spectrometry workflows for accurate quantification of trace-level host cell proteins in drug products: Benefits of FAIMS separation and gas-phase fractionation DIA.

Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level.

High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing.

Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.

Expanding the Epitranscriptomic RNA Sequencing and Modification Mapping Mass Spectrometry Toolbox with Field Asymmetric Waveform Ion Mobility and Electrochemical Elution Liquid Chromatography.

Post-transcriptional modifications of RNA strongly influence the RNA structure and function. Recent advances in RNA sequencing and mass spectrometry (MS) methods have identified over 140 of these modifications on a wide variety of RNA species. Most next-generation sequencing approaches can only map one RNA modification at a time, and while MS can assign multiple modifications simultaneously in an unbiased manner, MS cannot accurately catalog and assign RNA modifications in complex biological samples due to limitations in the fragment length and coverage depth. Thus, a facile method to identify novel RNA modifications while simultaneously locating them in the context of their RNA sequences is still lacking. We combined two orthogonal modes of RNA ion separation before MS identification: high-field asymmetric ion mobility separation (FAIMS) and electrochemically modulated liquid chromatography (EMLC). FAIMS RNA MS increases both coverage and throughput, while EMLC LC-MS orthogonally separates RNA molecules of different lengths and charges. The combination of the two methods offers a broadly applicable platform to improve the length and depth of MS-based RNA sequencing while providing contextual access to the analysis of RNA modifications.

Identification of proteoforms by top-down proteomics using two-dimensional low/low pH reversed-phase liquid chromatography-mass spectrometry.

In top-down (TD) proteomics, efficient proteoform separation is crucial to reduce the sample complexity and increase the depth of the analysis. Here, we developed a two-dimensional low pH/low pH reversed-phase liquid chromatography separation scheme for TD proteomics. The first dimension for offline fractionation was performed using a polymeric reversed-phase (PLRP-S) column with trifluoroacetic acid as ion-pairing reagent. The second dimension, a C4 nanocolumn with formic acid as ion-pairing reagent, was coupled online with a high-field asymmetric ion mobility spectrometry (FAIMS) Orbitrap Tribrid mass spectrometer. For both dimensions several parameters were optimized, such as the adaption of the LC gradients in the second dimension according to the elution time (i.e., fraction number) in the first dimension. Avoidance of elevated temperatures and prolonged exposure to acidic conditions minimized cleavage of acid labile aspartate-proline peptide bonds. Furthermore, a concatenation strategy was developed to reduce the total measurement time. We compared our low/low pH with a previously published high pH (C4, ammonium formate)/low pH strategy and found that both separation strategies led to complementary proteoform identifications, mainly below 20kDa, with a higher number of proteoforms identified by the low/low pH separation. With the optimized separation scheme, more than 4900 proteoforms from 1250 protein groups were identified in Caco-2 cells.

Integrated Lithium Battery-Powered High-Field Asymmetric Ion Mobility Spectrometer (FAIMS) for Molecular Structure Fingerprinting and Deep Learning

A portable high-field asymmetric ion transfer spectrometer (FAIMS) was miniaturized to improve the design. The prototype consists of a main controller, a galvanometer, a high-voltage square-wave power supply, a Raspberry Pi module, and integrated circuitry. The new design eliminates a main power supply and meets the high- and low-voltage requirements. Qt, a cross-platform software package for creating graphical user interfaces, was used to map the molecular structure fingerprint. The timing, circuit structure, and mechanical assembly were optimized. The dimensions were 45 cm × 48 cm × 23 cm. 16 s were required to collect 1000 data points; the usage time exceeded 8 h, and the background noise was approximately 0.2 pA. The prototype offers excellent efficiency, stability, and multiple applications. The accuracy of FAIMS with the deep-learning model for data acquisition is good. This system is anticipated to evaluate the concentrations of volatiles in diverse types of samples.

High-field charge transport and noise in p -Si from first principles

The parameter-free computation of charge transport properties of semiconductors is now routine owing to advances in the ab-initio description of the electron-phonon interaction. Many studies focus on the low-field regime in which the carrier temperature equals the lattice temperature and the current power spectral density (PSD) is proportional to the mobility. The calculation of high-field transport and noise properties offers a stricter test of the theory as these relations no longer hold, yet few such calculations have been reported. Here, we compute the high-field mobility and PSD of hot holes in silicon from first principles at temperatures of 77 and 300 K and electric fields up to 20 kV cm$^{-1}$ along various crystallographic axes. We find that the calculations quantitatively reproduce experimental trends including the anisotropy and electric-field dependence of hole mobility and PSD. The experimentally observed rapid variation of energy relaxation time with electric field at cryogenic temperatures is also correctly predicted. However, as in low-field studies, absolute quantitative agreement is in general lacking, a discrepancy that has been attributed to inaccuracies in the calculated valence band structure. Our work highlights the use of high-field transport and noise properties as a rigorous test of the theory of electron-phonon interactions in semiconductors.

MobCal-MPI 2.0: an accurate and parallelized package for calculating field-dependent collision cross sections and ion mobilities.

Ion mobility spectrometry (IMS), which can be employed as either a stand-alone instrument or coupled to mass spectrometry, has become an important tool for analytical chemistry. Because of the direct relation between an ion's mobility and its structure, which is intrinsically related to its collision cross section (CCS), IMS techniques can be used in tandem with computational tools to elucidate ion geometric structure. Here, we present MobCal-MPI 2.0, a software package that demonstrates excellent accuracy (RMSE 2.16%) and efficiency in calculating low-field CCSs via the trajectory method (≤30 minutes on 8 cores for ions with ≤70 atoms). MobCal-MPI 2.0 expands on its predecessor by enabling the calculation of high-field mobilities through the implementation of the 2nd order approximation to two-temperature theory (2TT). By further introducing an empirical correction to account for deviations between 2TT and experiment, MobCal-MPI 2.0 can compute accurate high-field mobilities that exhibit a mean deviation of <4% from experimentally measured values. Moreover, the velocities used to sample ion-neutral collisions were updated from a weighted to a linear grid, enabling the near-instantaneous evaluation of mobility/CCS at any effective temperature from a single set of N2 scattering trajectories. Several enhancements made to the code are also discussed, including updates to the statistical analysis of collision event sampling and benchmarking of overall performance.

(Invited) Ultrawide Bandgap Transistors for High Temperature and Radiation Hard Applications

Ultra-wide bandgap semiconductors - boron nitride, diamond, gallium oxide, and AlN - have a potential for high-temperature and radiation hard applications. These materials have a high breakdown field and large atom displacement energy correlated with a higher radiation hardness. Some of these materials, especially diamond, have a high thermal conductivity supporting a better heat handling capability, high low field mobility, and a high saturation velocity (for example, boron nitride) enabling a higher operating frequency, better microwave devices, and supporting operation in the 300 GHz band and above.