Solving Advanced Task-Specific Problems in Measurement Sciences with Generative AI.

The Generative Pre-Trained Transformer known as ChatGPT-4 has undergone extensive pretraining on a diverse data set, enabling it to generate coherent and contextually relevant text based on the input it receives. This capability allows it to perform tasks from answering questions and has attracted significant interest in material sciences, synthetic chemistry, and drug discovery. In this work, we posed four advanced task-specific problems to ChatGPT, which were recently published in leading journals for topics in analytical chemistry, spectroscopy, bioimage super-resolution, and electrochemistry. ChatGPT-4 successfully implemented the four ideas after assigning the "persona" to the AI and posing targeted questions. We show two cases where "unguided" ChatGPT could complete the assignments with minimal human direction. The construction of a microwave spectrum from a free induction curve and super-resolution of bioimages was accomplished using this approach. Two other specific tasks, correcting a complex baseline with morphological operations of set theory and estimating the diffusion current, required additional input, e.g., equations and specific directions from the user. In each case, the MATLAB code was eventually generated by ChatGPT-4 even when the original authors did not provide any code themselves. We show that a validation test must be implemented to detect and correct mistakes made by ChatGPT-4, followed by feedback correction. These approaches will pave the way for open and transparent science and eliminate the black boxes in measurement science when it comes to advanced data processing.

Transgenic tobacco plants overexpressing a wheat salt stress root protein (TaSSRP) exhibit enhanced tolerance to heat stress.

BACKGROUND: Heat stress is a detrimental abiotic stress that limits the development of many plant species and is linked to a variety of cellular and physiological problems. Heat stress affects membrane fluidity, which leads to negative effects on cell permeability and ion transport. Research reveals that heat stress causes severe damage to cells and leads to rapid accumulation of reactive oxygen species (ROS), which could cause programmed cell death. METHODS AND RESULTS: This current study aimed to validate the role of Triticum aestivum Salt Stress Root Protein (TaSSRP) in plants' tolerance to heat stress by modulating its expression in tobacco plants. The Relative Water Content (RWC), total chlorophyll content, and Membrane Stability Index (MSI) of the seven distinct transgenic lines (T0 - 2, T0 - 3, T0 - 6, T0 - 8, T0 - 9, T0 - 11, and T0 - 13), increased in response to heat stress. Despite the fact that the same tendency was detected in wild-type (WT) plants, changes in physio-biochemical parameters were greater in transgenic lines than in WT plants. The expression analysis revealed that the transgene TaSSRP expressed from 1.00 to 1.809 folds in different lines in the transgenic tobacco plants. The gene TaSSRP offered resistance to heat stress in Nicotiana tabacum, according to the results of the study. CONCLUSION: These findings could help to improve our knowledge and understanding of the mechanism underlying thermotolerance in wheat, and the novel identified gene TaSSRP could be used in generating wheat varieties with enhanced tolerance to heat stress.

Automated Regularized Deconvolution for Eliminating Extra-Column Effects in Fast High-Efficiency Separations.

With the introduction of ultrahigh efficiency columns and fast separations, the need to eliminate peak deformation contributed by the instrument must be effectively solved. Herein, we develop a robust framework to automate deconvolution and minimize its artifacts, such as negative dips, wild noise oscillations, and ringing, by combining regularized deconvolution and Perona-Malik (PM) anisotropic diffusion methods. A asymmetric generalized normal (AGN) function is proposed to model the instrumental response for the first time. With no-column data at various flow rates, the interior point optimization algorithm extracts the parameters describing instrumental distortion. The column-only chromatogram was reconstructed using the Tikhonov regularization technique with minimal instrumental distortion. For illustration, four different chromatography systems are used in fast chiral and achiral separations with 2.1 and 4.6 mm i.d. columns. Ordinary HPLC data can approach highly optimized UHPLC data. Similarly, in fast HPLC-circular dichroism (CD) detection, 8000 plates were gained for a fast chiral separation. Moment analysis of deconvolved peaks confirms correction of the center of mass, variance, skew, and kurtosis. This approach can be easily integrated and used with virtually any separation and detection system to provide enhanced analytical data.

Symmetrization of Peaks in Chiral Chromatography with an Area-Invariant Resolution Enhancement Method.

A majority of enantiomeric separations show some degree of peak asymmetry, which is detrimental to quantitative and semiquantitative chiral analysis. This paper presents a simple and rapid peak symmetrization algorithm for the correction or reduction of peak tailing or fronting in exponentially modified Gaussians. Raw chromatographic data can be symmetrized by adding a correct fraction of the first derivative to the chromatogram. The area remains invariant since the area under the first derivative is zero for a pure Gaussian and numerically close to zero for asymmetric peaks. A method of easily extracting the distortion parameter is provided, as well as insight into how pre-smoothing the data with the "perfect smoother" algorithm can suppress high frequencies effectively. The central difference method is also used to compute the first derivative, reducing root-mean-square noise by up to 28% compared to the standard forward difference method. A survey of 40 chiral separations is presented, demonstrating the range of asymmetry observed in chiral separations. Examples of symmetrization of the peaks from enantiomers in comparable and disproportionate concentrations are also provided. Artifacts of deconvolution are discussed, along with methods to mitigate such artifacts.

Direct Construction of Peaks from Free Induction Decay Curves for Gas Chromatography-Molecular Rotational Resonance Spectroscopy without Fourier Transforms.

The concept of coupling gas chromatography with molecular rotational resonance spectroscopy (GC-MRR) was introduced in 2020, combining the separation capabilities of GC with the unparalleled specificity of MRR. In this study, we address the challenge of the high data throughput of MRR spectrometers, as GC-MRR spectrometers can generate thousands to millions of data points per second. In the previous GC-MRR studies, a free induction decay (FID) measurement was Fourier transformed to generate each point on the chromatogram. Such extensive calculations limit the performance, sensitivity, and speed of GC-MRR. A direct approach is proposed here to extract peak intensity from FID using the Gram-Schmidt vector orthogonalization method. First, analyte-free FIDs are used to construct a basis set representing the instrument's background noise, and then the remaining FIDs are orthogonalized to this fixed basis set. Each FID yields a single intensity value after Gram-Schmidt orthogonalization. The magnitude of the orthogonalized analyte FID is the signal intensity plotted in the chromatogram. This approach is computationally much faster (up to 10 times) than the conventional Fourier transform algorithm, is at least as sensitive as the FT algorithm, and maintains or improves the chromatographic peak shape. We compare the sensitivity, linearity, and chromatographic peak shapes for the Fourier transform and Gram-Schmidt approaches using both synthetically generated FIDs and instrumental data. This approach would allow the summed peak intensity to be displayed essentially in real-time, following which identified peaks can be further investigated to identify and quantify the species associated with each.

Recent Progress, Challenges, and Opportunities of Membrane Distillation for Heavy Metals Removal.

Water is essential for the presence of life on this earth. However, water contamination due to the presence of heavy/toxic metals is one of the serious environmental issues for living beings. Several methods have been devoted to separating or removing those heavy metals from wastewater. Among them, membrane distillation (MD) has become one of the most attractive approaches due to its higher rejection rate than processes driven by pressure, lower energy consumption than traditional distillation processes. MD has gained significant attention for removing heavy metals than other techniques like ion exchange and adsorption in the last two decades. This review provides insight knowledge to the reader and focuses on how heavy metals impact humans and the environment, sources of heavy metals, current and especially removal methods using the MD method. Moreover, recent studies, challenges, and opportunities on MD membrane modules and heavy metal removal systems are discussed. More importantly, in this review, we have identified the gaps and opportunities that are required for enhancing the MD approach and its practical suitability for heavy metal removals. MD module and system showed high performance, proving their possible applications to remove heavy metal ions in water/wastewater treatment.

Enhanced and tunable femtosecond nonlinear optical properties of pure and nickel-doped zinc oxide films.

The nonlinear optical properties of pure ZnO and Ni-doped ZnO thin films are explored using the Z-scan technique at different input laser intensities and an excitation wavelength of 750 nm by 100 fs laser pulses. The pure ZnO and Ni-doped ZnO thin films were prepared by radio frequency magnetron sputtering at room temperature. A scanning electron microscope equipped with energy-dispersive x-ray spectroscopy was used to measure the thickness and composition of the thin films, while a UV-visible spectrophotometer was used to measure the linear optical properties. The structure of the thin films was measured using x-ray diffraction. Saturable absorption (SA) was observed in the pure ZnO thin film, while Ni-doped ZnO illustrated a combination of SA and reverse SA (RSA). The nonlinear absorption coefficient (ß) and nonlinear refractive index (n2) of both pure ZnO and Ni-doped ZnO thin films were found to be input laser intensity dependent. As the input laser intensity increased, the nonlinear absorption coefficient and the nonlinear refractive index of both samples increased. An enhancement of two times in the nonlinear refractive index was observed for the Ni-doped ZnO thin film compared to the pure ZnO thin film. The optical limiting behavior of pure ZnO and Ni-doped ZnO thin films was investigated, and the data demonstrated that Ni-doped ZnO thin film is a good candidate for optical limiter applications due to the presence of strong RSA.

Exploring the structure of pure germanophospate glasses with different concentrations probed by magic angle spinning NMR spectroscopy.

Phosphate-based glasses such as pure germanophosphate can be achieved at moderately low temperature by means of affordable chemical substances. Nowadays, they become more stimulating because they can be easily doped with alkali, transition metal ions, and rare earth oxides to afford the anticipated physical and/or chemical features for nanoscience applications. Herein, we report an experimental study dealing with the structure of pure germanophosphate glass samples of GeO 2 prepared with different concentrations ranging from 20 up to 70 mole%. 31 P magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy has been employed to characterize the co-formed glasses by two different glass-forming oxides. The components of the phosphate species ( Q n ) in each sample were determined by analyzing the MAS NMR spectra. Interestingly, 31 P MAS NMR spectrum for each sample was found to be characteristic powder patterns of the middle units Q2 . Q2  unit found herein has one oxygen atom bonded towards one germanium atom (non-bridging) and the other two oxygens are bonding towards two phosphorus atoms (bridging) of phosphate group (PO4 ). The results show that Q2 split into two units, Q2 I and Q2 II, due to different shielding of the phosphorus nucleus provided by the next nearest neighbor atoms. The chemical shift is interpreted in terms of the structure of each building unit of the phosphate group. The results obtained herein shed light on the way how to explore the revealed structure of the prepared glasses for the development of supported catalysts. Indeed, owing to their high chemical/thermal stability, the co-formed germanophosphate glasses obtained may prove as useful substrates for potential nanocatalysts.

Enhancing Sensitivity for High-Selectivity Gas Chromatography-Molecular Rotational Resonance Spectroscopy.

A next-generation gas chromatograph-molecular rotational resonance (MRR) spectrometer (GC-MRR) with instrumental improvements and higher sensitivity is described. MRR serves as a structural information-rich detector for GC with extremely narrow linewidths and capabilities surpassing 1H nuclear magnetic resonance/Fourier transform infrared spectroscopy/mass spectrometry (MS) while offering unparalleled specificity in regard to a molecule's three-dimensional structure. With a Fabry-Pérot cavity and a supersonic jet incorporated into a GC-MRR, dramatic improvements in sensitivity for molecules up to 244 Da were achieved in the microwave region compared to the only prior work, which demonstrated the GC-MRR idea for the first time with millimeter waves. The supersonic jet cools the analytes to ∼2 K, resulting in a limited number of molecular rotational and vibrational levels and enabling us to obtain stronger GC-MRR signals. This has allowed the limits of detection of the GC-MRR to be comparable to a GC thermal conductivity detector with an optimized choice of gases. The performance of this GC-MRR system is reported for a range of molecules with permanent dipole moments, including alcohols, nitrogen heterocyclics, halogenated compounds, dioxins, and nitro compounds in the molecular mass range of 46-244 Da. The lowest amount of any substance yet detected by MRR in terms of mass is reported in this work. A theoretically unexpected finding is reported for the first time about the effect of the GC carrier gas (He, Ne, and N2) on the sensitivity of the analysis in the presence of the gas driving the supersonic jet (He, Ne, and N2) in the GC-MRR. Finally, the idea of total molecule monitoring in the GC-MRR analogous to selected ion monitoring in GC-MS is illustrated. Structural isomers and isotopologues of bromobutanes and bromonitrobenzenes are used to demonstrate this concept.

Pre-procedural high-pitch coronary CT angiography assessment of patients undergoing transcatheter aortic valve implantation (TAVI) without patient-specific adjustment: analysis of diagnostic performance.

AIM: To evaluate the ability to assess the coronary arteries using pre-procedural computed tomography (CT; high-pitch mode) in patients referred for transcatheter aortic valve implantation (TAVI). METHODS AND MATERIALS: CT and invasive coronary angiography (ICA) were performed pre-TAVI in 100 patients (46 women; 79 ± 5.9 years). CT was performed in prospectively ECG-triggered high-pitch mode after intravenous administration of 70 ml iodinated contrast medium. Image quality was assessed using a four-point scale (graded 0-3). Significant coronary artery stenosis (≥50% diameter) was graded as either present or absent by one observer and in one-third of patients by two observers independently. ICA was the standard of reference. Results were reported per segment and per patient. RESULTS: Twenty-two percent of patients had known coronary artery disease (CAD). In two cases, a coronary anomaly was detected. Diagnostic image quality (grade 1-3) was achieved in 30.3% of segments. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 75%, 80.5%, 16%, and 98.5%, respectively. Significant coronary stenosis could be ruled out completely in all segments in three patients. The interrater agreement per patient was excellent (kappa = 1). CONCLUSION: Relevant coronary findings can frequently be observed in high-pitch TAVI-planning CT. Despite the limitations of the technique and in patients referred to pre-TAVI evaluation (rapid heart rate, coronary calcifications, etc.), a valid evaluation of coronary arteries is possible in a considerable proportion of segments with a high NPV; however, few studies were completely free of motion artefacts to dependably exclude CAD using this technique in this challenging group of patients.

Correction to: Nuclear medicine services after COVID-19: gearing up back to normality.

The authors P. Orellana and N. El-Haj were inadvertently deleted in the original paper.

Facile Solutions to the Problems Associated with Chemical Information and Mathematical Symbolism While Using Machine Translation Tools.

Advances in computer-aided translation technology have made tremendous progress in accuracy in the past few years. Chemical Abstracts Service of the American Chemical Society summarizes scientific works from more than 50 languages and allows the users to search papers in nine selected languages. Currently, only the abstracts are rendered into English by human experts or by machine translation because full text translation of millions of articles is beyond the human capacity today. An English translation of a research paper, scientific book, or patent is often required for research, data mining, and for historical purposes from various foreign languages. Many fundamental papers in chemistry, quantum chemistry, physics, and mathematics contain a significant number of chemical or mathematical equations. One of the major known problems in machine translation of such symbolically dense texts is incorrect or meaningless output. This article describes how to optimize the existing machine translation tools to read foreign language papers embedded with chemical/mathematical equations. German and French languages have been selected for illustrative purposes for English translation. Direct upload of text with extensive symbolism is possible with certain services, but this also occasionally produces erroneous rendition into English. A facile solution to the associated problems with embedded equations and mathematical formulas is replacing the equations and notations with "dummy" variables. The placeholder or dummy symbols can be removed after translation, and the original equations are substituted again. This approach, which can be automated in future, relies on the idea that chemical formulas and mathematical notations are universal. Following the guidelines in the article, excellent translations can be produced from a text having interspersed equations and chemical symbols.

Improving peak capacities over 100 in less than 60 seconds: operating above normal peak capacity limits with signal processing.

A primary focus in liquid chromatography analysis of complex samples is high peak capacity separations. Using advanced instrumentation and optimal small, high-efficiency columns, complex multicomponent mixtures can now be analyzed in relatively short times. Despite these advances, chromatographic peak overlap is still observed. Recently, attention has shifted from improvements in chromatographic efficiency and selectivity to enhancing data processing after collection. Curve fitting methods can be used to trace underlying peaks, but do not directly enhance chromatographic resolution. Methods based on the properties of derivatives and power transform were recently shown to enhance chromatographic peak resolution while maintaining critical peak information (peak areas and retention times). These protocols have been extensively investigated for their fundamental properties, advantages, and limitations, but they have not been evaluated with complex chromatograms. Herein, we evaluate the use of deconvolution via Fourier transform (FT), even-derivative peak sharpening, and power law with the fast separation (< 60 s) of a 101-component mixture using ultra-high-pressure liquid chromatography. High noise and peak overlap are present in this gradient separation, which is representative of fast chromatography. Chromatographic resolution enhancement is demonstrated and described. Further, accurate quantitation is maintained and shown with representative examples. Enhancements in peak capacity and peak-to-peak resolutions are discussed. Finally, the statistical theory of overlap is used for 101 peaks and predictions are made for the number of singlet, doublet, and multiplets analyte peaks. The effect of increasing peak capacity by FT even derivative sharpening and power laws leads to a decrease in the number of peak overlaps and an increase in total peak number. Graphical abstract.

A Gas Chromatography-Molecular Rotational Resonance Spectroscopy Based System of Singular Specificity.

We designed and demonstrated the unique abilities of the first gas chromatography-molecular rotational resonance spectrometer (GC-MRR). While broadly and routinely applicable, its capabilities can exceed those of high-resolution MS and NMR spectroscopy in terms of selectivity, resolution, and compound identification. A series of 24 isotopologues and isotopomers of five organic compounds are separated, identified, and quantified in a single run. Natural isotopic abundances of mixtures of compounds containing chlorine, bromine, and sulfur heteroatoms are easily determined. MRR detection provides the added high specificity for these selective gas-phase separations. GC-MRR is shown to be ideal for compound-specific isotope analysis (CSIA). Different bacterial cultures and groundwater were shown to have contrasting isotopic selectivities for common organic compounds. The ease of such GC-MRR measurements may initiate a new era in biosynthetic/degradation and geochemical isotopic compound studies.

Ramifications and Insights on the Role of Water in Chiral Sub/Supercritical Fluid Chromatography.

More than 40 cosolvents have been used with carbon dioxide to alter its solvation strength. Among the most interesting systems is the subcritical/supercritical CO2/alkanol eluents. Using small amounts of water in CO2/MeOH is known to be beneficial in chiral subcritical/supercritical chromatography. However, the ramifications of introducing water as a cosolvent component is not entirely understood. In this work, we demonstrate important aspects of the CO2/MeOH/H2O system on nine chiral stationary phases with very different surface chemistries, encompassing derivatized polysaccharides, macrocyclic glycopeptides, iso-butylmercaptoquinine, isopropyl macrocyclic oligosaccharides, and π-electron acceptor/π-electron donor phases. A hydrophilicity scale has been shown to be useful in predicting if a given chiral column chemistry would show a significant enhancement in separation efficiency in the presence of water in the CO2/MeOH system. We demonstrate up to 8-fold enhancements in plate counts of chiral separations with a concomitant decrease in retention times, as predicted by the qualitative test. The same chiral analysis can now be completed in almost a third of the time with the addition of small amounts of water, thereby decreasing organic solvent consumption by a considerable amount. Hydrophobic stationary phases show a minimal increase in efficiency and decrease in analysis times and optimized separations show much larger reduced plate heights, compared to more hydrophilic stationary phases. Furthermore, the presence of water can alter the nature of the adsorption isotherm under nonlinear conditions. Small amounts of water can be used to tune nonlinear tailing peaks into fronting ones, significantly improving preparative enantiomeric separations.

The utility of statistical moments in chromatography using trapezoidal and Simpson's rules of peak integration.

Modern chromatographic data acquisition softwares often behave as black boxes where the researchers have little control over the raw data processing. One of the significant interests of separation scientists is to extract physico-chemical information from chromatographic experiments and peak parameters. In addition, column developers need the total peak shape analysis to characterize the flow profile in chromatographic beds. Statistical moments offer a robust approach for providing detailed information for peaks in terms of area, its center of gravity, variance, resolution, and its skew without assuming any peak model or shape. Despite their utility and theoretical significance, statistical moments are rarely incorporated as they often provide underestimated or overestimated results because of inappropriate choice of the integration method and selection of integration limits. The Gaussian model is universally used in most chromatography softwares to assess efficiency, resolution, and peak position. Herein we present a user-friendly, and accessible approach for calculating the zeroth, first, second, and third moments through more accurate numerical integration techniques (Trapezoidal and Simpson's rule) which provide an accurate estimate of peak parameters as compared to rectangular integration. An Excel template is also provided which can calculate the four moments in three steps with or without baseline correction.

Extending the power transform approach for recovering areas of overlapping peaks.

Power functions, p n ( x ) = [ f ( x ) ] n , are embedded in some modern chromatography detectors and software which not only alter the linear dynamic range of such detectors but also improve the cosmetic aspects of the chromatograms. These aspects include a reduction in baseline noise, improved peak symmetry, and better resolution. However, after raising the electronic output of a detector to a selected power (n > 1), the original peak area information is lost as are very small peaks. Recent advances in the peak processing protocol allow us to recover peak areas from overlapping peak areas, even in noisy environments using power functions. One of the primary protocol requirements of this approach was to have resolution factors ≥0.9. An increasing positive bias in the recovered area was observed as the resolution factors decreased below 0.9. In this work, we extend the capabilities of power function to lower resolution values. This bias is addressed by considering the increasing contributions in peak height coming from adjacent peaks. It is shown that the power function can now be used as long as the peak maxima are visible, making R s  = 0.5, the lower treatable resolution factor for two peaks of similar areas.

Assessment of undernutrition using Composite Index of Anthropometric Failure among children aged < 5 years in rural Yemen.

BACKGROUND: Impaired nutritional status is a major health problem affecting young children in developing countries that has a significant impact on child morbidity and mortality. AIMS: This study aimed to assess the prevalence of undernutrition among children aged < 5 years, using conventional indices and the Composite Index of Anthropometric Failure (CIAF), and then comparing their estimated results. METHODS: A community-based cross-sectional study was conducted and information was collected through house-tohouse visits using precoded structured records. We analysed data from 1292 children aged 6-59 months, from Ahwar and Al-Mahfed rural districts in Abyan Governate, South Yemen, with reference to the 2006 World Health Organization growth standards. RESULTS: CIAF identified undernutrition in 70.1% of children, while conventional anthropometric indices revealed 38.5% stunting, 39.9% wasting, and 55.1% underweight. Compared with conventional indices, CIAF aggregate recognized 31.6%, 30.2% and 15% more undernourished children than stunting, wasting and underweight separately. According to CIAF, 21% had a single anthropometric failure and 49.2% exhibited multiple failures. Stunting Index, Wasting Index and Underweight Index were 0.55, 0.57 and 0.79, respectively. CONCLUSIONS: CIAF gives a better estimate of undernutrition than currently used conventional indices; identifies more children with multiple anthropometric failures; and reflects a wider view of the extent and pattern of undernutrition of children living in communities with limited resource settings.

Separations at the Speed of Sensors.

The virtue of chemical sensors is speed and analyte specificity. The response time to generate an analytical signal typically varies from ∼1 to 20 s, and they are generally limited to a single analyte. Chemical sensors are significantly affected by multiple interferents, matrix effects, temperature, and can vary widely in sensitivity depending on the sensor format. Separation-based analyses remove matrix effects and interferents and are compatible with multiple analytes. However, the speed of such analyses has not been commensurate with traditional sensors until now. Beds of very small size with optimal geometry, containing core-shell particles of judicious immobilized selectors, can be used in an ultrahigh-flow regime, thereby providing subsecond separations of up to 10 analytes. Short polyether ether ketone lined stainless steel columns of various geometries were evaluated to determine the optimal bed geometry for subsecond analysis. Coupling these approaches provides subsecond-based detection and quantitation of multiple chiral and achiral species, including nucleotides, plant hormones, acids, amino acid derivatives, and sedatives among a variety of other compounds. The subsecond separations were reproducible with 0.9% RSD on retention times and showed consistent performance with 0.9% RSD on reduced plate height in van Deemter curves. A new powerful signal processing algorithm is proposed that can further enhance separation outputs and optical spectra without altering band areas on more complex separations such as 10 peaks under a second.

Geopolymers as a New Class of High pH Stable Supports with Different Chromatographic Selectivity.

Geopolymers belong to an interesting class of X-ray amorphous polycondensed aluminosilicate ceramic solids. The high mechanical strength, chemical stability in basic conditions, and water insolubility make geopolymers a unique solid support in separation science. This work describes a new straightforward synthetic procedure for making spherical porous geopolymer particles with high surface area which are amenable for chromatographic purposes. In-depth physicochemical evaluation of geopolymers is conducted via particle size distribution, porosity measurements, X-ray diffraction, pH titration, and energy-dispersive spectroscopy and compared with silica, titania, and zirconia. Chromatographic selectivity shows that the surface chemistry of geopolymers has strong hydrophilic and electrostatic character, which makes it different from 36 chromatographic columns. Hydrophilic interaction liquid chromatography in columns packed with geopolymer particles shows different selectivity than that in silica columns, with excellent peak shapes. Phosphate or fluoride additives are not required as they are for zirconia or titania phase.