Time-of-flight Secondary Ion Mass Spectrometry Research Articles

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone.

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy-electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. We determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

Bortezomib-releasing silica-collagen xerogels for local treatment of osteolytic bone- and minimal residual disease in multiple myeloma

BackgroundAccumulation of malignant plasma cells in the bone marrow causes lytic bone lesions in 80% of multiple myeloma patients. Frequently fracturing, they are challenging to treat surgically. Myeloma cells surviving treatment in the presumably protective environment of bone lesions impede their healing by continued impact on bone turnover and can explain regular progression of patients without detectable minimal residual disease (MRD). Locally applicable biomaterials could stabilize and foster healing of bone defects, simultaneously delivering anti-cancer compounds at systemically intolerable concentrations, overcoming drug resistance.MethodsWe developed silica-collagen xerogels (sicXer) and bortezomib-releasing silica-collagen xerogels (boXer) for local treatment of osteolytic bone disease and MRD. In vitro and in vivo (tissue sections) release of bortezomib was assessed by ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Material impact on bone formation was assessed in vitro regarding osteoclast/osteoblast numbers and activity. In vivo, drilling defects in a rat- and the 5T33-myeloma mouse model were treated by both materials and assessed by immunohistochemistry, UPLC-MS/MS, µCT, and ToF-SIMS. The material’s anti-myeloma activity was assessed using ten human myeloma cell lines (HMCLs) and eight primary myeloma cell samples including four patients refractory to systemic bortezomib treatment.ResultssicXer and boXer show primary stability comparable to trabecular bone. Granule size and preparation method tailor degradation as indicated by release of the xerogel components (silica and collagen) and bortezomib into culture medium. In vitro, both materials reduce osteoclast activity and do not negatively interfere with osteoblast differentiation and function. The presumed resulting net bone formation with maintained basic remodeling properties was validated in vivo in a rat bone defect model, showing significantly enhanced bone formation for boXer compared to non-treated defects. Both materials induce myeloma cell apoptosis in all HMCLs and primary myeloma cell samples. In the 5T33-myeloma mouse model, both materials stabilized drilling defects and locally controlled malignant plasma cell growth.ConclusionsThe combination of stabilization of fracture-prone lesions, stimulation of bone healing, and anti-tumor effect suggest clinical testing of sicXer and boXer as part of a combined systemic/local treatment strategy in multiple myeloma and non-malignant diseases.

Enhancing Cu interconnect reflow in back-end-of-line metal wiring with ultrathin Co liners

Abstract This research investigates the gap-fill characteristics of Cu in back-end-of-line (BEOL) interconnects, focusing on Co liner deposition using chemical vapor deposition (CVD) and cyclic-CVD (C-CVD). Providing superior gap-fill characteristics for BEOL interconnect applications is important. Three methods—CVD, C-CVD, and a combination of the two—were compared in terms of their effects on Cu reflow and electrical performance. CVD exhibited the lowest resistivity (44 μΩ cm at 10 nm thickness) and the fewest carbon impurities, confirmed by time-of-flight secondary ion mass spectrometry (ToF-SIMS). Atomic force microscopy (AFM) revealed that CVD produced the smoothest surface (Rq ~0.5 nm), enabling better adhesion and uniform Cu reflow. At 300°C, Co liners deposited by CVD achieved void-free Cu–Mn filling in 20 nm trenches, which showed CVD to outperform other methods. These findings highlight CVD as the most effective technique for precise Co liner deposition, ensuring reliable Cu interconnects in advanced semiconductor nodes.


Subcellular ToF-SIMS Imaging of the Snow Alga Sanguina nivaloides by Combining High Mass and High Lateral Resolution Acquisitions.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging has demonstrated great potential for metabolic imaging; however, achieving sufficiently high lateral and mass resolution to reach the organelle scale remains challenging. To address this, we have developed an approach that combines imaging acquisitions close to the highest lateral resolution (<150 nm) and mass resolution (9,000) reachable by ToF-SIMS. The data were then merged and processed using multivariate analysis (MVA), providing the identification and annotation of 85% of the main contributors to the multivariate analysis components at high lateral resolution. Insights into the electron microscopy sample preparation were provided, especially as we revealed that at least three different osmium-containing complexes can be found depending on the specific chemical environment of organelles. In cells of the snow alga Sanguina nivaloides, living in a natural environment limited in nutrients such as phosphorus (P), we mapped elements and molecules within their subcellular context, allowing for the molecular fingerprinting of organelles at a resolution of ∼150 nm, as confirmed by correlative electron microscopy. It was thus possible to highlight that S. nivaloides likely absorbed selectively some inorganic P forms provided by P-rich dust deposited on the snow surface. S. nivaloides cells could maintain phosphorylations in the stroma of the chloroplast, consistently with the preservation of photosynthetic activity. The presented method can thus overcome the current limitations of ToF-SIMS for subcellular imaging and contributes to the understanding of key questions, such as P homeostasis and other cell physiological processes.

Mapping active pharmaceutical ingredients Distributions in tablets using Time-of-Flight secondary ion mass spectrometry with multivariate curve resolution

This study introduces an advanced approach to identifying signals associated with indapamide, amlodipine, and perindopril in solid dosage form using time-of-flight secondary ion mass spectrometry (ToF-SIMS) combined with multivariate curve resolution (MCR). The primary objective was to obtain and characterize these signals through MCR factors, which then led to identifying unique signals specific to each active pharmaceutical ingredient (API). These unique signals were crucial for constructing detailed 2D and 3D images of the API distribution within the tablet. The results demonstrated that indapamide and amlodipine exhibited multiple unique peaks, while perindopril had only one. Additionally, the study revealed non-homogeneous distribution patterns of APIs and excipients, such as SiO2 and Mg stearate. This work highlights the significance of applying advanced analytical techniques such as ToF-SIMS and MCR in the pharmaceutical field to ensure consistent therapeutic efficacy through a better understanding of API distribution.

Interface Degradation of LaCl3-Based Solid Electrolytes Coupled with Ultrahigh-Nickel Cathodes.

Despite competitive compatibility with high-nickel cathodes, chloride solid electrolytes (SEs) still experience inevitable side reactions at the cathode/SE interface, causing capacity decay in all-solid-state lithium batteries (ASSLBs) during cycling. Herein, a three-electrode ASSLB testing device is developed to comprehensively reveal the interface failure mechanisms of the ultrahigh-nickel LiNi0.92Co0.05Mn0.03O2 (NCM92) cathode paired with LaCl3-based chloride SE Li0.447La0.475Zr0.059Ta0.179Cl3 (LLZTC). Distribution of relaxation time (DRT) analysis clearly shows the ASSLB degradation accompanied by a significant NCM92/LLZTC interface impedance increase, which becomes more pronounced at the higher cutoff charging voltage of 4.8 V vs Li+/Li. Furthermore, time-of-flight secondary ion mass spectrometry (ToF-SIMS) and focused ion beam scanning electron microscopy (FIB-SEM) analysis also confirm the deterioration arising from active lattice oxygen and loss of physical contact at the NCM92/LLZTC interface. These findings reveal both electrochemical degradation and physical contact failure at the cathode/SE interface as key causes of the ASSLBs' capacity decay.

Hydrophilic Modification of Macroscopically Hydrophobic Mineral Talc and Its Specific Application in Flotation.

Sodium diethyldithiocarbamate (DDTC), a common collector used to enhance the hydrophobicity of minerals in froth flotation, nevertheless weakens the hydrophobicity of the talc surface. To rationalize this anomaly, the interactions of a hydrophobic alkyl group and hydrophilic mineralophilic group (-NCS2-) of heteropolar surfactant DDTC, and a water molecule with the talc (001) surface, were investigated. Herein, DFT simulations found that the talc (001) surface features natural hydrophobicity determined by the competition between adhesion (surface water) and cohesion (water-water interactions). The interaction of the hydrophobic alkyl group of DDTC with the talc surface is more favorable compared to that of the -NCS2- group and H2O, favoring the hydrophilic modification of the talc surface. Additionally, adsorption isotherms, time-of-flight secondary ion mass spectrometry (ToF-SIMS), microflotation tests, and contact angle measurements also indicate that the differences in adsorption orientation of the heteropolar surfactant DDTC on the talc surface enhance the hydrophilicity of the talc surface, leading to a decreased recovery of the talc. This study provides crucial surface chemistry evidence for the selective adsorption of heteropolar surfactants and contributes to the understanding of the mechanism for the efficient flotation separation of molybdenite from talc.

Investigation of sub-nm binary oxidic surface modifications on mixed ionic electronic conductors with ToF-SIMS: Oxidic overlayer stability and ionic interdiffusion behavior

Modifications of mixed ionic electronic conductor (MIEC) surfaces are a promising approach to improve oxygen exchange reaction (OER) kinetics and can have a tremendous impact on surface charges and secondary ion yields. Utilizing time-of-flight secondary ion mass spectrometry (ToF-SIMS), we examined degradation, segregation, and cation interdiffusion behaviors on La0.6Sr0.4CoO3-δ (LSC) and Pr0.2Ce0.8O2-δ (PCO) thin films modified with ∼0.5 nm CaO, TiO2, and SnO2 overlayers after annealing at 700 °C and 800 °C, respectively. Surface profiles (AFM; ToF-SIMS) and depth profiles (ToF-SIMS) revealed structural and chemical transformations, including particle formation and surface roughening. The overlayer stability varied significantly for different overlayers on the same material and for the same overlayer on LSC and PCO. All oxidic overlayers were more stable on PCO than LSC. Depth profiling indicated that 40Ca+ ions penetrated the entire LSC and PCO layers (30 nm). 48Ti+ aligns more accurately with a typical analytical solution to Fick’s diffusion equation for finite systems, showing higher diffusion coefficients in LSC than PCO. 120Sn+ exhibited minimal penetration, indicating high stability on the surface and less intermixing with either MIEC. These results hint at the need to differentiate between the stability of the binary oxides on the surface and the bulk diffusivity.

Biomimetics through bioconjugation of 16-methylheptadecanoic acid to damaged hair for hair barrier recovery

The primary component of the lipid barrier on human hair, which is essential for defense against aging and environmental stresses, is 18-methyleicosanoic acid (18-MEA), which provides hydrophobic properties and protective benefits. Since 18-MEA cannot be regenerated once damaged, developing technology that can permanently bind alternative materials to hair is critical. Once 18-MEA was removed from hair via X-ray photoelectron spectroscopy (XPS), pentaerythritol tetraisoosterate (PTIS) was hydrolyzed and observed via gas chromatography/mass spectrometry (GC/MS) to confirm that it mimicked 18-MEA, and 16-methylheptadecanoic acid (16-MHA) was obtained at pH 4 or lower. 16-MHA was bioconjugated to damaged hair from which 18-MEA was removed via a carbodiimide reaction using polycarbodiimide. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) confirmed that 16-MHA remained on the surface of the bioconjugated hair even after washing. Observation of the endothermic reaction of moisture in hair via a differential scanning calorimetry (DSC) and evaluation of the moisture content confirmed that the physical properties of hair enriched with 16-MHA were similar to those of virgin hair. This biomimetic approach has been shown to restore both external structural integrity and internal moisture homeostasis.

Peak-Based Machine Learning for Plastic Type Classification in Time-of-Flight Secondary Ion Mass Spectrometry.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurement data and machine learning were used in this work to classify six different types of plastics. In order to take into account the characteristics of the measurement data, the local maxima of the measurement data were first examined in a preprocessing step. Several machine learning methods were then implemented to create a model that could successfully classify the plastics. To visualize the data distribution, we applied a dimensionality reduction method, namely, principal component analysis. Finally, to distinguish between the six types of plastics, we conducted an ensemble analysis using four tree-based algorithms: decision tree, random forest, gradient boosting, and LIGHTGBM. This approach can identify the feature importance of plastic samples and allow the inference of the chemical properties of each plastic type. In this way, ToF-SIMS data could be utilized to successfully classify plastics and enhance explainability.

Longitudinal Piezoelectricity and Polarization-Insensitive Oxidation in Janus vdWs Nb3SeI7.

As a newly discovered Janus van der Waals (vdW) material, semiconducting Nb3SeI7 offers several notable advantages, including spontaneous out-of-plane polarization, facile exfoliation to the monolayer limit, and significant out-of-plane emission dipole in second harmonic generation. These properties make it a promising candidate for piezoelectric and piezophototronic applications in highly efficient energy conversion. However, Nb3SeI7 is prone to oxidation when exposed to oxygen, which can severely limit the exploration and utilization of these intriguing physical properties. Therefore, understanding the oxidation mechanism of pristine Nb3SeI7 and its correlation with electrical polarization-an area that remains largely unexplored-is highly significant. In this study, the out-of-plane piezoelectricity of Nb3SeI7 is experimentally demonstrated, with a piezoelectric coefficient (|d33 eff|) of 0.76nmV-1. Furthermore, by combining near ambient-pressure X-ray photoelectron spectroscopy (NAP-XPS), Time-of-Flight secondary ion mass spectrometry (ToF-SIMS), and Density functional theory (DFT)calculations, it is revealed that the oxidation of Nb3SeI7 is self-limiting and independent of its electrical polarization, owing to the similar defect formation energies of Se and I atoms. This self-limiting and polarization-insensitive oxidation provides valuable insights into the stabilization mechanisms and expands the potential applications of out-of-plane piezoelectricity and other intriguing physical properties in Janus vdW Nb3SeI7.

Enhancing Counterfeit Banknote Analysis: Case Studies Using TOF-SIMS

Counterfeiting banknotes poses a significant threat to economies worldwide, particularly in developing countries where cash transactions remain predominant. Despite advancements in security features, counterfeiters continue to adapt, necessitating more sophisticated analysis methods. Time of flight Secondary Ion Mass Spectrometry (TOF-SIMS) offers a powerful approach to surface chemical imaging and depth profiling of counterfeit currencies. Real cases of five different counterfeit Lebanese banknotes are studied, using TOF-SIMS to address specific questions regarding the composition and placement of replicated security features, gaining insights into counterfeit banknote production and the raw materials used. The findings provide essential information to decision-makers at the national bank, supporting the design of future currencies through the selection of security features best suited to the local market, thereby enhancing protection against financial fraud..

A novel method to understand and quantify silicate tetrahedron in C-S-H by Time of flight secondary ion mass spectrometry analysis

The performance of cementitious materials is highly determined by calcium silicate hydrate (C-S-H). In this work, time of flight secondary ion mass spectrometry (TOF-SIMS) characterized by its high resolution was proposed to quantitatively determine the silicate tetrahedron content of C-S-H in a specific micron area. A C-S-H database in which the silicate content in local hydrates is quantified by ion intensity, was established for TOF-SIMS analysis. Results indicate that 8 negative ions and 19 positive ion fragments can be detected among the decomposition of C-S-H. By selecting the characteristic ions representing different silicate structures from ion fragments, the functional relationship between the intensity of characteristic ions and the silicate contents in C-S-H can be established. The quantification equation was proposed to calculate Qn structure contents for various alite hydrates. The silicate structures with defects allocated in the control and pre-pressed sample was constructed successfully based on the TOF-SIMS quantitative results.

Mechanisms and Enhancement of Hydrogen Evolution for Membrane Anti-fouling and Methane Upgrading by Sacrificed Anode in a Novel Electro-AnMBR

Severe membrane fouling and low CH4 content in the produced biogas have restricted the applicability and energy recovery profit of the anaerobic membrane bioreactor (AnMBR). Herein, a novel AnMBR was constructed with an electrochemical hydrogen evolution reaction (electro-HER) by double anodes and a titanium membrane-cathode (eHAnMBR). The electro-HER was controlled and enhanced by sacrificed iron anode under low voltage, to mitigate membrane fouling and upgrade biogas simultaneously. The critical factors in electro-HER were investigated to influence the AnMBR system, including hydrogen, applied voltage, and Fe ions. The voltage and hydrogen enhanced the hydrogenotrophic methanogenesis process and enriched hydrophilic Methanobacterium and Methanosarcina, thereby improving biogas purity by up to 28% and increasing total CH₄ production by 46%. Furthermore, the electro-HER on the membrane-cathode decreased the transmembrane pressure by 30%. Time of Flight Secondary Ion Mass Spectrometry (TOF-SIMs) was innovatively applied to visualize the organic foulants in membrane pores. The electro-HER not only produced H2 to optimize cake layer structure but also produced local alkalinity on the membrane surface, to remove extracellular polymeric substances in membrane pores. Additionally, Fe2+/Fe3+ released from the sacrificial iron anode, facilitated phosphate precipitation and removal from 15.7% to 37.9%. This study presents a novel and sustainable wastewater treatment solution by integrating the electro-HER process with AnMBR, enabling both energy recovery and membrane antifouling.

Microstructure evolution and hydrogen absorption characteristics of gradient-hydrogenated Ti-4.5Al-3V-2Mo-2Fe alloys

Ti-4.5Al-3V-2Mo-2Fe rolled material is a dual-phase titanium alloy with an average grain size of less than 3 μm; its optimal superplastic forming temperature of 760 °C is at least 50 °C lower than the temperature required for diffusion bonding, making it challenging to carry out superplastic forming/diffusion bonding within a process window. The promotion of hydrogen on the low-temperature diffusion bonding of the alloy was verified through thermohydrogen processing, and the absorption characteristics of hydrogen in the alloy at various temperatures, holding times, and pressures were investigated. Subsequently, a mathematical model for achieving standardized hydrogen content was developed. X-ray polycrystalline diffractometer (XRD) analysis was utilized to preliminarily explore phase differences in samples with varying levels of hydrogen content. Furthermore, scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron back scatter diffraction (EBSD) and time of flight secondary ion mass spectrometry (TOF-SIMS) were employed to analyze microstructure changes and hydrogen distribution in both the surface and core regions of the titanium alloy following hydrogenation, demonstrating its feasibility for surface hydrogenation treatment of titanium alloy sheets.

Effect of D-arginine as a novel depressant on the flotation separation of chalcopyrite from pyrite at low alkalinity

Flotation separation of Cu–Fe sulfide minerals typically necessitate the addition of substantial quantities of lime to depress pyrite flotation. Because lime can harm the environment, there is an urgent need to develop novel environmentally friendly depressants that are non-toxic and biodegradable. In this study, we investigated an environmentally friendly pyrite depressant containing amino and carboxyl groups, namely D-arginine (DA). The effect of DA on the surface hydrophobicity of Cu–Fe sulfide minerals and thus collector adsorption was investigated by analyzing zeta potentials, adsorption capacities, and contact angles. Additionally, changes in the surface properties of the minerals induced by DA were examined using X-ray photoelectron spectroscopy (XPS), time-of-flight secondary ion mass spectroscopy (ToF-SIMS), and atomic force microscopy (AFM). Flotation tests revealed that 2 × 10–4 mol/L DA reduced the flotation recovery of pyrite to 9.96 % at low alkalinity while leaving chalcopyrite recovery unchanged. The results of mineral surface analysis indicated that DA exhibited significantly stronger adsorption on the pyrite surface than on the chalcopyrite surface. Furthermore, DA effectively reduced the adsorption of the collector on the surface of pyrite, thereby weakening pyrite floatability at low alkalinity. Therefore, DA is a promising alternative depressant for the flotation separation of chalcopyrite from pyrite.

The Application of a Random Forest Classifier to ToF-SIMS Imaging Data.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging is a potent analytical tool that provides spatially resolved chemical information on surfaces at the microscale. However, the hyperspectral nature of ToF-SIMS datasets can be challenging to analyze and interpret. Both supervised and unsupervised machine learning (ML) approaches are increasingly useful to help analyze ToF-SIMS data. Random Forest (RF) has emerged as a robust and powerful algorithm for processing mass spectrometry data. This machine learning approach offers several advantages, including accommodating nonlinear relationships, robustness to outliers in the data, managing the high-dimensional feature space, and mitigating the risk of overfitting. The application of RF to ToF-SIMS imaging facilitates the classification of complex chemical compositions and the identification of features contributing to these classifications. This tutorial aims to assist nonexperts in either machine learning or ToF-SIMS to apply Random Forest to complex ToF-SIMS datasets.

Effects of Pt doping on surface properties and quenching of band edge emission in ZnO

Pt doped ZnO thin films were synthesized on soda-lime glass substrates using a cost-effective sol-gel method, followed by spin coating and thermal annealing at various temperatures. Several characterization techniques such as UV–Vis absorption spectroscopy, photoluminescence (PL), field emission scanning electron microscopy (FESEM), time-of-flight secondary ion mass spectroscopy (ToF-SIMS), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) are exploited to investigate the Pt doping effects on surface and optical properties of ZnO thin films. UV–Vis analysis demonstrated a slight decrease in the optical band gap from 3.3 eV to 3.2 eV with increased annealing, indicating enhanced suitability for optoelectronic applications. FESEM imaging revealed distinct worm-like structures and small Pt metal nanoparticles in unannealed samples, while thermal treatment supported the formation of spherical Pt nanoparticles and improved conductive pathways in the films. The Wagner diagram, coupled with Auger line transitions from XPS, quantified the oxidation states and chemical environments of Zn and Pt, respectively. Notably, the observed changes in the binding energy of the Zn-2p junction and the kinetic energy of the Zn-LMM Auger junction were significantly influenced by the Pt doping and the electronic properties of the substrate. The Wagner diagram provided a comprehensive visual representation of the parameters, facilitating a deeper understanding of electronic interactions and structural dynamics at the atomic level. XPS results confirmed the presence of ZnO, Zn(OH)2, Pt0 and PtO2 phases, indicating stability and constutient's interactions. ToF-SIMS also validated the uniform distribution of Pt nanoparticles within the ZnO thin film, confirming the effectiveness of the sol-gel method. As a result of Pt doping, PL studies revealed a large quenching effect on band edge emission in the UV and visible emission region of ZnO thin film, which is due to Pt acting as a recombination center for photogenerated carriers. Overall, our results highlight the influence of annealing and Pt incorporation on the optical and structural properties of ZnO thin films and highlight their potential applications for photonics and catalysis.

Ultra-High Adsorption Capacity of Calcium-Iron Layered Double Hydroxides for HEDP Removal through Phase Transition Processes.

Antiscalant disposal in reverse osmosis concentrate (ROC) treatment is a significant obstacle in desalination. This study investigated the adsorption performance of LDHs for removing 1-hydroxyethylidene-1,1-diphosphonic acid (HEDP). CaFe-LDH presented a specific adsorption behavior and ultrahigh adsorption capacity for HEDP, with a maximum adsorption capacity of 335.7 mg P/g (1116.5 mg HEDP/g) at pH 7.0. X-ray diffraction (XRD) demonstrated that HEDP adsorption induced a structural transformation of CaFe-LDH from a layered configuration to a highly ordered structure, leading to a noticeable phase transition. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) and Raman spectroscopy further confirmed that two distinct binding modes of HEDP, relating to chelation with Ca2+ and adsorption on Fe3+ simultaneously, are connected by phosphonic acid groups (-C-PO(OH)2), forming the CaFe-HEDP complex. X-ray fluorescence (XRF) and X-ray photoelectron spectroscopy (XPS) analyses revealed that the CaFe-HEDP ternary complex exhibits a highly ordered arrangement in an oxygen-bridged framework. The construction of an oxygen-coordinated framework contributes to the incorporation of more HEDP into CaFe-LDH, leading to a well-aligned lattice in the new phase. These findings provide valuable insights into developing novel LDH-based adsorbents for removing phosphorus-containing antiscalants, establishing a sustainable approach to ROC management, and potential environmental risk reduction.

Development of Peptide Identification System for ToF-SIMS Spectra Using Supervised Machine Learning.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) data interpretation for organic materials is complicated because of various fragment ions produced from each molecule and the overlapping of certain mass peaks from different molecules. Fragmentation mechanisms in SIMS are complex because different sputtering and ionization processes can simultaneously occur. Therefore, a prediction system that can identify materials in a sample is required. A novel prediction system for peptides based on ToF-SIMS and amino-acid-based teaching information (labels) for supervised machine learning was developed. To develop the prediction system for general organic materials, the annotation of materials is crucial to creating effective labels for supervised learning. Peptides are composed of 20 amino acid residues, which can be used as labels. We previously developed a peptide prediction system using Random Forest, a supervised machine-learning method. However, only the amino acids contained in the target peptide were predicted, and the amino acid sequence was unable to be assumed. In this study, the amino acid sequence of the test peptide was determined by adding the information on two adjacent amino acids to the labels. Once the prediction system learned the target peptide spectra, the peptides in the newly obtained ToF-SIMS spectra could be identified. The new prediction system also provides useful information for the identification of unknown peptides. The prediction results indicate that two adjacent permutations of amino acids are effective pieces of teaching information for expressing the amino acid sequence of a peptide.