Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

Enders, Abigail; North, Nicole M; Fensore, Chase M; Velez-Alvarez, Juan; Allen, Heather C.

doi:10.1021/acs.analchem.1c00867

Cited by 93 publications

(72 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Machine learning algorithms , build a model based on sample data, known as “training data”, to make predictions or decisions without completely understanding the “black box”, which represents the mechanism and learning process during model training. These characteristics enable machine learning to be successfully applied in the fields of chemistry and biology, such as spectral prediction, − cancer biomarker detection, − biosensor advancement, − and chemical synthesis. − Despite this progress, the application of machine learning algorithms to guide CD synthesis is still limited. In our previous studies, we developed a deep convolution neural network (DCNN) model for predicting the optical properties of CDs .…”

Section: Introductionmentioning

confidence: 99%

Customized Carbon Dots with Predictable Optical Properties Synthesized at Room Temperature Guided by Machine Learning

et al. 2022

View full text Add to dashboard Cite

Fluorescent carbon dots (CDs) have been increasingly used in fluorescence detection and imaging based on their tunable fluorescence (FL) and resistance to photobleaching. However, the fast and reliable design of fluorescent CDs with specific optical properties involves a number of factors, such as the concentration of precursors, reaction time, and solvents. Therefore, it is usually considered difficult to design CDs with favorable optical properties. Herein, we report an extreme gradient boosting (XGBoost) model for guiding the fabrication of CDs with high FL intensity and tunable emission from p-benzoquinone (PBQ) and ethylenediamine (EDA) in different solvents at room temperature. Among a variety of studied machine learning models, XGBoost shows the best performance in the field of material synthesis, with a prediction coefficient of determination (R 2) higher than 0.96. The XGBoost model can effectively predict the optical properties of CDs, including the maximum FL intensity and emission centers. Guided by the XGBoost model, various green or blue fluorescent CDs with adjustable emission centers and solubility properties are designed and fabricated accurately. These CDs are successfully applied for Fe3+ detection, sustained drug release, whole-cell imaging, and poly(vinyl alcohol) (PVA) film preparation. These results suggest the great potential of the combination of machine learning and CD synthesis as an effective strategy to help researchers realize accurate selection of reasonable CDs with individual customized properties to achieve different goals.

show abstract

Section: Introductionmentioning

confidence: 99%

Customized Carbon Dots with Predictable Optical Properties Synthesized at Room Temperature Guided by Machine Learning

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The surface chemical properties of the synthesized mCNCs and presence of functional groups were examined through the FTIR spectroscopy. As observed from FTIR spectrum, the stretching bands appeared at 3311, 1735, 1653, 1440, 1125, 881, and 844 cm –1 as specified for the existence of −NH, −CH, −CO, −CC–, −NO, −CN, and epoxy ring, respectively (see Figure A). The strong absorption band appeared at 3200–3600 cm –1 and could be assigned to the presence of O–H (stretching) and N–H (stretching) vibration bands.…”

Section: Resultsmentioning

confidence: 74%

Azadirachta indica Seed Derived Carbon Nanocapsules: Cell Imaging, Depolarization of Mitochondrial Membrane Potential, and Dose-Dependent Control Death of Breast Cancer

Maity

Tomar

Wasnik

et al. 2022

ACS Biomater. Sci. Eng.

View full text Add to dashboard Cite

In this work, a series of mesoporous carbon nanocapsules (mCNS) of size below 10 nm have been prepared from Azadirachta indica seeds with a very easy and cost-effective approach. These nanocapsules can emit red and green light and are effective for cell imaging. Further, these carbon nanocapsules are biocompatible toward the normal healthy cells, however, they possess modest cytotoxicity against the MCF-7 (human breast cancer) and triple-negative breast cancer (TNBC) (MDA-MB-231 breast cancer cells), and the rate of killing cancer cells strongly depends on the dose of mCNCs. Further, the mitochondrial membrane potential and apoptosis assay were performed to analyze the therapeutic significance of these nanocapsules to kill breast cancer. Results showed that these carbon nanocapsules can depolarize the mitochondrial membrane potential alone (without using conventional drugs) and can change the physiological parameters and cellular metabolic energy of the cancer cells and kill them. The apoptosis results confirmed the death of breast cancer cells in the form of apoptosis and necrosis. Moreover, the results suggested that the porous carbon nanocapsules (mCNCs) reported herein can be used as a potential candidate and useful for the theranostic applications such as for cancer cell detection and therapy without using any conventional drugs.

show abstract

“…Therefore, infrared spectrum analysis and stress analysis of phosphate rock were conducted. The phosphate rock at different positions in the mining area (area 1#, 2#, 3#, and 4#, as shown in Figure 1) was assessed by Fourier infrared spectrometer (Barra et al, 2021;Enders et al, 2021). The infrared spectrum analysis results of ore rock at different positions are shown in Figure 2.…”

Section: Phosphate Rock Specimensmentioning

confidence: 99%

Characteristics of Infrared Radiation in the Failure of Phosphate Rock at Different Loading Rates

Gao

Lin

et al. 2022

Front. Earth Sci.

View full text Add to dashboard Cite

Safe and effective mining of phosphate rock plays an important role in the sustainable development of phosphorus resources. The mechanical properties and failure process of phosphate rock under different mining rates remain unclear, further restricting the safe and efficient mining of phosphate rock. In this paper, infrared radiation and uniaxial compression tests of phosphate rock under different loading rates, e.g., 0.0005, 0.001, 0.005, and 0.01 mm/s, were conducted to investigate the failure process of phosphate rock. Energy evolution and infrared radiation characteristics of the phosphate rock damage process were analyzed using nondestructive, real-time, and noncontact infrared thermal imaging technology. The results show that the higher the loading rate of phosphate rock, the more obvious the high-temperature zone and high-temperature point of phosphate rock in the loading process. At failure, the friction and slippage between internal cracks are intense, showing that the infrared radiation temperature difference increases with the increase of loading rate. As loading rate increases, the energy release time of phosphate rock before damage is reduced, resulting in more energy stored in the rock as evinced by its infrared radiation characteristics, finally resulting in greater damage. The increase of loading rate reduces the dissipation energy of phosphate rock before failure so that more energy remains in the rock mass through the weak surface of the grain boundary. The results of this work will be helpful in enhancing theoretical support for prevention and control of dynamic disasters in phosphate mines.

show abstract

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

Cited by 93 publications

References 45 publications

Customized Carbon Dots with Predictable Optical Properties Synthesized at Room Temperature Guided by Machine Learning

Customized Carbon Dots with Predictable Optical Properties Synthesized at Room Temperature Guided by Machine Learning

Azadirachta indica Seed Derived Carbon Nanocapsules: Cell Imaging, Depolarization of Mitochondrial Membrane Potential, and Dose-Dependent Control Death of Breast Cancer

Characteristics of Infrared Radiation in the Failure of Phosphate Rock at Different Loading Rates

Contact Info

Product

Resources

About