Fundamental insight into electrochemical oxidation of methane towards methanol on transition metal oxides.

Electrochemical oxidation of CH4 is known to be inefficient in aqueous electrolytes. The lower activity of methane oxidation reaction (MOR) is primarily attributed to the dominant oxygen evolution reaction (OER) and the higher barrier for CH4 activation on transition metal oxides (TMOs). However, a satisfactory explanation for the origins of such lower activity of MOR on TMOs, along with the enabling strategies to partially oxidize CH4 to CH3OH, have not been developed yet. We report here the activation of CH4 is governed by a previously unrecognized consequence of electrostatic (or Madelung) potential of metal atom in TMOs. The measured binding energies of CH4 on 12 different TMOs scale linearly with the Madelung potentials of the metal in the TMOs. The MOR active TMOs are the ones with higher CH4 binding energy and lower Madelung potential. Out of 12 TMOs studied here, only TiO2, IrO2, PbO2, and PtO2 are active for MOR, where the stable active site is the O on top of the metal in TMOs. The reaction pathway for MOR proceeds primarily through *CH x intermediates at lower potentials and through *CH3OH intermediates at higher potentials. The key MOR intermediate *CH3OH is identified on TiO2 under operando conditions at higher potential using transient open-circuit potential measurement. To minimize the overoxidation of *CH3OH, a bimetallic Cu2O3 on TiO2 catalysts is developed, in which Cu reduces the barrier for the reaction of *CH3 and *OH and facilitates the desorption of *CH3OH. The highest faradaic efficiency of 6% is obtained using Cu-Ti bimetallic TMO.

Constitutive relationship and governing physical properties for magnetophoresis.

Magnetophoresis is an important physical process with application to drug delivery, biomedical imaging, separation, and mixing. Other than empirically, little is known about how the magnetic field and magnetic properties of a solution affect the flux of magnetic particles. A comprehensive explanation of these effects on the transport of magnetic particles has not been developed yet. Here we formulate a consistent, constitutive equation for the magnetophoretic flux of magnetic nanoparticles suspended in a medium exposed to a stationary magnetic field. The constitutive relationship accounts for contributions from magnetic diffusion, magnetic convection, residual magnetization, and electromagnetic drift. We discovered that the key physical properties governing the magnetophoresis are magnetic diffusion coefficient, magnetic velocity, and activity coefficient, which depend on relative magnetic energy and the molar magnetic susceptibility of particles. The constitutive equation also reveals previously unknown ballistic and diffusive limits for magnetophoresis wherein the paramagnetic particles either aggregate near the magnet or diffusive away from the magnet, respectively. In the diffusive limit, the particle concentration is linearly proportional to the relative magnetic energy of the suspension of paramagnetic particles. The region of the localization of paramagnetic particles near the magnet decreases with increasing the strength of the magnet. The dynamic accumulation of nanoparticles, measured as the thickness of the nanoparticle aggregate, near the magnet compares well with the theoretical prediction. The effect of convective mixing on the rate of magnetophoresis is also discussed for the magnetic targeting applications.

Achievements, Challenges, and Perspectives on Nitrogen Electrochemistry for Carbon-Neutral Energy Technologies.

Unrestrained anthropogenic activities have severely disrupted the global natural nitrogen cycle, causing numerous energy and environmental issues. Electrocatalytic nitrogen transformation is a feasible and promising strategy for achieving a sustainable nitrogen economy. Synergistically combining multiple nitrogen reactions can realize efficient renewable energy storage and conversion, restore the global nitrogen balance, and remediate environmental crises. Here, we provide a unique aspect to discuss the intriguing nitrogen electrochemistry by linking three essential nitrogen-containing compounds (i.e., N2 , NH3 , and NO3 - ) and integrating four essential electrochemical reactions, i.e., the nitrogen reduction reaction (N2 RR), nitrogen oxidation reaction (N2 OR), nitrate reduction reaction (NO3 RR), and ammonia oxidation reaction (NH3 OR). This minireview also summarizes the acquired knowledge of rational catalyst design and underlying reaction mechanisms for these interlinked nitrogen reactions. We further underscore the associated clean energy technologies and a sustainable nitrogen-based economy.

Solvent fluctuations in the solvation shell determine the activation barrier for crystal growth rates.

Solution crystallization is a common technique to grow advanced, functional crystalline materials. Supersaturation, temperature, and solvent composition are known to influence the growth rates and thereby properties of crystalline materials; however, a satisfactory explanation of how these factors affect the activation barrier for growth rates has not been developed. We report here that these effects can be attributed to a previously unrecognized consequence of solvent fluctuations in the solvation shell of solute molecules attaching to the crystal surface. With increasing supersaturation, the average hydration number of the glutamic acid molecule decreases and can reach an asymptotic limit corresponding to the number of adsorption sites on the molecule. The hydration number of the glutamic acid molecule also fluctuates due to the rapid exchange of solvent in the solvation shell and local variation in the supersaturation. These rapid fluctuations allow quasi-equilibrium between fully solvated and partially desolvated states of molecules, which can be used to construct a double-well potential and thereby to identify the transition state and the required activation barrier. The partially desolvated molecules are not stable and can attach spontaneously to the crystal surface. The activation barrier versus hydration number follows the Evans-Polanyi relation. The predicted absolute growth rates of the α-glutamic acid crystal at lower supersaturations are in reasonable agreement with the experimental observations.

Mechanistic insights into electrochemical reduction of CO2 over Ag using density functional theory and transport models.

Electrochemical reduction of CO2 using renewable sources of electrical energy holds promise for converting CO2 to fuels and chemicals. Since this process is complex and involves a large number of species and physical phenomena, a comprehensive understanding of the factors controlling product distribution is required. While the most plausible reaction pathway is usually identified from quantum-chemical calculation of the lowest free-energy pathway, this approach can be misleading when coverages of adsorbed species determined for alternative mechanism differ significantly, since elementary reaction rates depend on the product of the rate coefficient and the coverage of species involved in the reaction. Moreover, cathode polarization can influence the kinetics of CO2 reduction. Here, we present a multiscale framework for ab initio simulation of the electrochemical reduction of CO2 over an Ag(110) surface. A continuum model for species transport is combined with a microkinetic model for the cathode reaction dynamics. Free energies of activation for all elementary reactions are determined from density functional theory calculations. Using this approach, three alternative mechanisms for CO2 reduction were examined. The rate-limiting step in each mechanism is **COOH formation at higher negative potentials. However, only via the multiscale simulation was it possible to identify the mechanism that leads to a dependence of the rate of CO formation on the partial pressure of CO2 that is consistent with experiments. Simulations based on this mechanism also describe the dependence of the H2 and CO current densities on cathode voltage that are in strikingly good agreement with experimental observation.

Thermodynamic and achievable efficiencies for solar-driven electrochemical reduction of carbon dioxide to transportation fuels.

Thermodynamic, achievable, and realistic efficiency limits of solar-driven electrochemical conversion of water and carbon dioxide to fuels are investigated as functions of light-absorber composition and configuration, and catalyst composition. The maximum thermodynamic efficiency at 1-sun illumination for adiabatic electrochemical synthesis of various solar fuels is in the range of 32-42%. Single-, double-, and triple-junction light absorbers are found to be optimal for electrochemical load ranges of 0-0.9 V, 0.9-1.95 V, and 1.95-3.5 V, respectively. Achievable solar-to-fuel (STF) efficiencies are determined using ideal double- and triple-junction light absorbers and the electrochemical load curves for CO2 reduction on silver and copper cathodes, and water oxidation kinetics over iridium oxide. The maximum achievable STF efficiencies for synthesis gas (H2 and CO) and Hythane (H2 and CH4) are 18.4% and 20.3%, respectively. Whereas the realistic STF efficiency of photoelectrochemical cells (PECs) can be as low as 0.8%, tandem PECs and photovoltaic (PV)-electrolyzers can operate at 7.2% under identical operating conditions. We show that the composition and energy content of solar fuels can also be adjusted by tuning the band-gaps of triple-junction light absorbers and/or the ratio of catalyst-to-PV area, and that the synthesis of liquid products and C2H4 have high profitability indices.

Hydrolysis of Electrolyte Cations Enhances the Electrochemical Reduction of CO2 over Ag and Cu.

Electrolyte cation size is known to influence the electrochemical reduction of CO2 over metals; however, a satisfactory explanation for this phenomenon has not been developed. We report here that these effects can be attributed to a previously unrecognized consequence of cation hydrolysis occurring in the vicinity of the cathode. With increasing cation size, the pKa for cation hydrolysis decreases and is sufficiently low for hydrated K+, Rb+, and Cs+ to serve as buffering agents. Buffering lowers the pH near the cathode, leading to an increase in the local concentration of dissolved CO2. The consequences of these changes are an increase in cathode activity, a decrease in Faradaic efficiencies for H2 and CH4, and an increase in Faradaic efficiencies for CO, C2H4, and C2H5OH, in full agreement with experimental observations for CO2 reduction over Ag and Cu.

Effects of temperature and gas-liquid mass transfer on the operation of small electrochemical cells for the quantitative evaluation of CO2 reduction electrocatalysts.

In the last few years, there has been increased interest in electrochemical CO2 reduction (CO2R). Many experimental studies employ a membrane separated, electrochemical cell with a mini H-cell geometry to characterize CO2R catalysts in aqueous solution. This type of electrochemical cell is a mini-chemical reactor and it is important to monitor the reaction conditions within the reactor to ensure that they are constant throughout the study. We show that operating cells with high catalyst surface area to electrolyte volume ratios (S/V) at high current densities can have subtle consequences due to the complexity of the physical phenomena taking place on electrode surfaces during CO2R, particularly as they relate to the cell temperature and bulk electrolyte CO2 concentration. Both effects were evaluated quantitatively in high S/V cells using Cu electrodes and a bicarbonate buffer electrolyte. Electrolyte temperature is a function of the current/total voltage passed through the cell and the cell geometry. Even at a very high current density, 20 mA cm-2, the temperature increase was less than 4 °C and a decrease of <10% in the dissolved CO2 concentration is predicted. In contrast, limits on the CO2 gas-liquid mass transfer into the cells produce much larger effects. By using the pH in the cell to measure the CO2 concentration, significant undersaturation of CO2 is observed in the bulk electrolyte, even at more modest current densities of 10 mA cm-2. Undersaturation of CO2 produces large changes in the faradaic efficiency observed on Cu electrodes, with H2 production becoming increasingly favored. We show that the size of the CO2 bubbles being introduced into the cell is critical for maintaining the equilibrium CO2 concentration in the electrolyte, and we have designed a high S/V cell that is able to maintain the near-equilibrium CO2 concentration at current densities up to 15 mA cm-2.

Modeling, Simulation, and Implementation of Solar-Driven Water-Splitting Devices.

An integrated cell for the solar-driven splitting of water consists of multiple functional components and couples various photoelectrochemical (PEC) processes at different length and time scales. The overall solar-to-hydrogen (STH) conversion efficiency of such a system depends on the performance and materials properties of the individual components as well as on the component integration, overall device architecture, and system operating conditions. This Review focuses on the modeling- and simulation-guided development and implementation of solar-driven water-splitting prototypes from a holistic viewpoint that explores the various interplays between the components. The underlying physics and interactions at the cell level is are reviewed and discussed, followed by an overview of the use of the cell model to provide target properties of materials and guide the design of a range of traditional and unique device architectures.

Differential Electrochemical Mass Spectrometer Cell Design for Online Quantification of Products Produced during Electrochemical Reduction of CO2.

The discovery of electrocatalysts that can efficiently reduce CO2 to fuels with high selectivity is a subject of contemporary interest. Currently, the available analytical methods for characterizing the products of CO2 reduction require tens of hours to obtain the dependence of product distribution on applied potential. As a consequence, there is a need to develop novel analytical approaches that can reduce this analysis time down to about an hour. We report here the design, construction, and operation of a novel differential electrochemical mass spectrometer (DEMS) cell geometry that enables the partial current densities of volatile electrochemical reaction products to be quantified in real time. The capabilities of the novel DEMS cell design are demonstrated by carrying out the electrochemical reduction of CO2 over polycrystalline copper. The reaction products are quantified in real time as a function of the applied potential during linear sweep voltammetry, enabling the product spectrum produced by a given electrocatalyst to be determined as a function of applied potential on a time scale of roughly 1 h.

Effects of electrolyte, catalyst, and membrane composition and operating conditions on the performance of solar-driven electrochemical reduction of carbon dioxide.

Solar-driven electrochemical cells can be used to convert carbon dioxide, water, and sunlight into transportation fuels or into precursors to such fuels. The voltage efficiency of such devices depends on the (i) physical properties of its components (catalysts, electrolyte, and membrane); (ii) operating conditions (carbon dioxide flowrate and pressure, current density); and (iii) physical dimensions of the cell. The sources of energy loss in a carbon dioxide reduction (CO2R) cell are the anode and cathode overpotentials, the difference in pH between the anode and cathode, the difference in the partial pressure of carbon dioxide between the bulk electrolyte and the cathode, the ohmic loss across the electrolyte and the diffusional resistances across the boundary layers near the electrodes. In this study, we analyze the effects of these losses and propose optimal device configurations for the efficient operation of a CO2R electrochemical cell operating at a current density of 10 mA cm(-2). Cell operation at near-neutral bulk pH offers not only lower polarization losses but also better selectivity to CO2R versus hydrogen evolution. Addition of supporting electrolyte to increase its conductivity has a negative impact on cell performance because it reduces the electric field and the solubility of CO2. Addition of a pH buffer reduces the polarization losses but may affect catalyst selectivity. The carbon dioxide flowrate and partial pressure can have severe effects on the cell efficiency if the carbon dioxide supply rate falls below the consumption rate. The overall potential losses can be reduced by use of an anion, rather than a cation, exchange membrane. We also show that the maximum polarization losses occur for the electrochemical synthesis of CO and that such losses are lower for the synthesis of products requiring a larger number of electrons per molecule, assuming a fixed current density. We also find that the reported electrocatalytic activity of copper below -1 V vs. RHE is strongly influenced by excessive polarization of the cathode and, hence, does not represent its true activity at bulk conditions. This article provides useful guidelines for minimizing polarization losses in solar-driven CO2R electrochemical cells and a method for predicting polarization losses and obtaining kinetic overpotentials from measured partial current densities.

Effect of K+ Force Fields on Ionic Conductivity and Charge Dynamics of KOH in Ethylene Glycol.

Predicting ionic conductivity is crucial for developing efficient electrolytes for energy storage and conversion and other electrochemical applications. An accurate estimate of ionic conductivity requires understanding complex ion-ion and ion-solvent interactions governing the charge transport at the molecular level. Molecular simulations can provide key insights into the spatial and temporal behavior of electrolyte constituents. However, such insights depend on the ability of force fields to describe the underlying phenomena. In this work, molecular dynamics simulations were leveraged to delineate the impact of force field parameters on ionic conductivity predictions of potassium hydroxide (KOH) in ethylene glycol (EG). Four different force fields were used to represent the K+ ion. Diffusion-based Nernst-Einstein and correlation-based Einstein approaches were implemented to estimate the ionic conductivity, and the predicted values were compared with experimental measurements. The physical aspects, including ion-aggregation, charge distribution, cluster correlation, and cluster dynamics, were also examined. A force field was identified that provides reasonably accurate Einstein conductivity values and a physically coherent representation of the electrolyte at the molecular level.

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers.

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities. This review encompasses various techniques and strategies to evaluate and enhance mixing efficiency in these confined environments. It explores the significance of mixing in micro- and millichannels, highlighting its relevance for enhanced reaction kinetics, homogeneity in mixed fluids, and analytical accuracy. We discuss various mixing methodologies that have been employed to get a narrower residence time distribution. The role of channel geometry, flow conditions, and mixing mechanisms in influencing the mixing performance are also discussed. Various emerging technologies and advancements in microfluidic devices and tools specifically designed to enhance mixing efficiency are highlighted. We emphasize the potential applications of micro- and millichannels in fields of nanoparticle synthesis, which can be utilized for biological applications. Additionally, the prospects of machine learning and artificial intelligence are offered toward incorporating better mixing to achieve precise control over nanoparticle synthesis, ultimately enhancing the potential for applications in these miniature fluidic systems.

Pathway toward Scalable Energy-Efficient Li-Mediated Ammonia Synthesis.

Lithium-mediated ammonia synthesis (LiMAS) is an emerging electrochemical method for NH3 production, featuring a meticulous three-step process involving Li+ electrodeposition, Li nitridation, and Li3N protolysis. The essence lies in the electrodeposition of Li+, a critical phase demanding current oscillations to fortify the solid-electrolyte interface (SEI) and ensure voltage stability. This distinctive operational cadence orchestrates Li nitridation and Li3N protolysis, profoundly influencing the NH3 selectivity. Increasing N2 pressure enhances the NH3 faradaic efficiency (FE) up to 20 bar, beyond which proton availability controls selectivity between Li nitridation and Li3N protolysis. The proton donor, typically alcohols, is a key factor, with 1-butanol observed to yield the highest NH3 FE. Counterion in the Li salt is also observed to be significant, with larger anions (e.g., exemplified by BF4-) improving SEI stability, directly impacting LiMAS efficacy. Notably, we report a peak NH3 FE of ∼70% and an NH3 current density of ∼-100 mA/cm2 via a delicate balance of process conditions, encompassing N2 pressure, proton donor, Li salt, and their respective concentrations. In contrast to the recent literature, we find that the theoretical maximum energy efficiency of LiMAS hinges significantly on the proton source, with LiMAS utilizing H2O calculated to have a maximum achievable energy efficiency of 27.8%. Despite inherent challenges, a technoeconomic analysis suggests high-pressure LiMAS to be more feasible than both ambient LiMAS and a modified green Haber-Bosch process. Our analysis finds that, at a 100 mA/cm2 NH3 current density and a 6 V cell voltage, LiMAS delivers green NH3 at an all-inclusive cost of $456 per ton, significantly lower than conventional cost barriers. Our economic analysis underscores high-pressure LiMAS as a potentially transformative technology that may revolutionize large-scale NH3 production, paving the way for a sustainable future.

Determination of spinal tracer dispersion after intrathecal injection in a deformable CNS model.

Background: Traditionally, there is a widely held belief that drug dispersion after intrathecal (IT) delivery is confined locally near the injection site. We posit that high-volume infusions can overcome this perceived limitation of IT administration. Methods: To test our hypothesis, subject-specific deformable phantom models of the human central nervous system were manufactured so that tracer infusion could be realistically replicated in vitro over the entire physiological range of pulsating cerebrospinal fluid (CSF) amplitudes and frequencies. The distribution of IT injected tracers was studied systematically with high-speed optical methods to determine its dependence on injection parameters (infusion volume, flow rate, and catheter configurations) and natural CSF oscillations in a deformable model of the central nervous system (CNS). Results: Optical imaging analysis of high-volume infusion experiments showed that tracers spread quickly throughout the spinal subarachnoid space, reaching the cervical region in less than 10 min. The experimentally observed biodispersion is much slower than suggested by the Taylor-Aris dispersion theory. Our experiments indicate that micro-mixing patterns induced by oscillatory CSF flow around microanatomical features such as nerve roots significantly accelerate solute transport. Strong micro-mixing effects due to anatomical features in the spinal subarachnoid space were found to be active in intrathecal drug administration but were not considered in prior dispersion theories. Their omission explains why prior models developed in the engineering community are poor predictors for IT delivery. Conclusion: Our experiments support the feasibility of targeting large sections of the neuroaxis or brain utilizing high-volume IT injection protocols. The experimental tracer dispersion profiles acquired with an anatomically accurate, deformable, and closed in vitro human CNS analog informed a new predictive model of tracer dispersion as a function of physiological CSF pulsations and adjustable infusion parameters. The ability to predict spatiotemporal dispersion patterns is an essential prerequisite for exploring new indications of IT drug delivery that targets specific regions in the CNS or the brain.

Microkinetic insights into the role of catalyst and water activity on the nucleation, growth, and dissolution during COF-5 synthesis.

The chemical pathway for synthesizing covalent organic frameworks (COFs) involves a complex medley of reaction sequences over a rippling energy landscape that cannot be adequately described using existing theories. Even with the development of state-of-the-art experimental and computational tools, identifying primary mechanisms of nucleation and growth of COFs remains elusive. Other than empirically, little is known about how the catalyst composition and water activity affect the kinetics of the reaction pathway. Here, for the first time, we employ time-resolved in situ Fourier transform infrared spectroscopy (FT-IR) coupled with a six-parameter microkinetic model consisting of ∼10 million reactions and over 20 000 species. The integrated approach elucidates previously unrecognized roles of catalyst pKa on COF yield and water on growth rate and size distribution. COF crystalline yield increases with decreasing pKa of the catalysts, whereas the effect of water is to reduce the growth rate of COF and broaden the size distribution. The microkinetic model reproduces the experimental data and quantitatively predicts the role of synthesis conditions such as temperature, catalyst, and precursor concentration on the nucleation and growth rates. Furthermore, the model also validates the second-order reaction mechanism of COF-5 and predicts the activation barriers for classical and non-classical growth of COF-5 crystals. The microkinetic model developed here is generalizable to different COFs and other multicomponent systems.

Snap-on Adaptor for Microtiter Plates to Enable Continuous-Flow Microfluidic Screening and Harvesting of Crystalline Materials.

Microtiter plate assay is a conventional and standard tool for high-throughput (HT) screening that allows the synthesis, harvesting, and analysis of crystals. The microtiter plate screening assays require a small amount of solute in each experiment, which is adequate for a solid-state crystal analysis such as X-ray diffraction (XRD) or Raman spectroscopy. Despite the advantages of these high-throughput assays, their batch operational nature results in a continuous decrease in supersaturation due to crystal nucleation and growth. Continuous-flow microfluidic mixer devices have evolved as an alternate technique for efficiently screening crystals under controlled supersaturation. However, such a microfluidic device requires a minimum of two inlets per micromixer to create cyclonic flow, thereby creating physical limitations for implementing such a device for HT screening. Additionally, the monolithic design of these microfluidic devices makes it challenging to harvest crystals for post-screening analysis. Here, we develop a snap-on adapter that can be reversibly attached to a microtiter plate and convert it into a continuous-flow microfluidic mixer device. The integration of the snap-on adapter with a flow distributor and concentration gradient generator provides greater control over screening conditions while minimizing the number of independent inlets and pumps required. The three-dimensional (3D)-printed snap-on adaptor is plugged into a 24-well plate assay to demonstrate salt screening of naproxen crystals. Different naproxen salts are crystallized using four different salt formers (SFs)-sodium hydroxide, potassium hydroxide, pyridine, and arginine-and four different solvents-ethanol, methanol, isopropyl alcohol, and deionized water. The wells are further inspected under an optical microscope to identify their morphological forms and yields. The crystals are then harvested for solid-state characterization using XRD and Fourier transform infrared spectroscopy, followed by measurement of their dissolution rates. The flexibility of the snap-on adapter to fit on a wide range of microtiter plates and the ease in harvesting and analyzing crystals postscreening are two significant advantages that make this device versatile for various applications.

Selective desolvation in two-step nucleation mechanism steers crystal structure formation.

The two-step nucleation (TSN) theory and crystal structure prediction (CSP) techniques are two disjointed yet popular methods to predict nucleation rate and crystal structure, respectively. The TSN theory is a well-established mechanism to describe the nucleation of a wide range of crystalline materials in different solvents. However, it has never been expanded to predict the crystal structure or polymorphism. On the contrary, the existing CSP techniques only empirically account for the solvent effects. As a result, the TSN theory and CSP techniques continue to evolve as separate methods to predict two essential attributes of nucleation - rate and structure. Here we bridge this gap and show for the first time how a crystal structure is formed within the framework of TSN theory. A sequential desolvation mechanism is proposed in TSN, where the first step involves partial desolvation to form dense clusters followed by selective desolvation of functional groups directing the formation of crystal structure. We investigate the effect of the specific interaction on the degree of solvation around different functional groups of glutamic acid molecules using molecular simulations. The simulated energy landscape and activation barriers at increasing supersaturations suggest sequential and selective desolvation. We validate computationally and experimentally that the crystal structure formation and polymorph selection are due to a previously unrecognized consequence of supersaturation-driven asymmetric desolvation of molecules.

In-line measurement of liquid-liquid phase separation boundaries using a turbidity-sensor-integrated continuous-flow microfluidic device.

Liquid-liquid phase separation (LLPS), also known as oiling-out, is the appearance of the second liquid phase preceding the crystallization. LLPS is an undesirable phenomenon that can occur during the crystallization of active pharmaceutical ingredients (APIs), proteins, and polymers. It is typically avoided during crystallization due to its detrimental impacts on crystalline products due to lowered crystallization rate, the inclusion of impurities, and alteration in particle morphology and size distribution. In situ monitoring of phase separation enables investigating LLPS and identifying the phase separation boundaries. Various process analytical technologies (PATs) have been implemented to determine the LLPS boundaries prior to crystallization to prevent oiling out of compounds. The LLPS measurements using PATs can be time-consuming, expensive, and challenging. Here, we have implemented a fully integrated continuous-flow microfluidic device with a turbidity sensor to quickly and accurately evaluate the LLPS boundaries for a ß-alanine, water, and IPA mixture. The turbidity-sensor-integrated continuous-flow microfluidic device is also placed under an optical microscope to visually track and record the appearance and disappearance of oil droplets. Streams of an aqueous solution of ß-alanine, pure solvent (water), and pure antisolvent (IPA or ethanol) are pumped into the continuous-flow microfluidic device at various flow rates to obtain the compositions at which the solution becomes turbid. The onset of turbidity is measured using a custom-designed, in-line turbidity sensor. The LLPS boundaries can be estimated using the turbidity-sensor-integrated microfluidic device in less than 30 min, which will significantly improve and enhance the workflow of the pharmaceutical drug (or crystalline material) development process.

Machine Learning-Driven, Sensor-Integrated Microfluidic Device for Monitoring and Control of Supersaturation for Automated Screening of Crystalline Materials.

Integrating sensors in miniaturized devices allow for fast and sensitive detection and precise control of experimental conditions. One of the potential applications of a sensor-integrated microfluidic system is to measure the solute concentration during crystallization. In this study, a continuous-flow microfluidic mixer is paired with an electrochemical sensor to enable in situ measurement of the supersaturation. This sensor is investigated as the predictive measurement of the supersaturation during the antisolvent crystallization of l-histidine in the water-ethanol mixture. Among the various metals tested in a batch system for their sensitivity toward l-histidine, Pt showed the highest sensitivity. A Pt-printed electrode was inserted in the continuous-flow microfluidic mixer, and the cyclic voltammograms of the system were obtained for different concentrations of l-histidine and different water-to-ethanol ratios. The sensor was calibrated for different ratios of antisolvent and concentrations of l-histidine with respect to the change of the measured anodic slope. Additionally, a machine-learning algorithm using neural networks was developed to predict the supersaturation of l-histidine from the measured anodic slope. The electrochemical sensors have shown sensitivity toward l-histidine, l-glutamic acid, and o-aminobenzoic acid, which consist of functional groups present in almost 80% of small-molecule drugs on the market. The machine learning-guided electrochemical sensors can be applied to other small molecules with similar functional groups for automated screening of crystallization conditions in microfluidic devices.