High-throughput Synthesis Research Articles

High-throughput synthesis of AlPO and SAPO zeolites by ink jet printing.

Ink jet printing is for the first time introduced into the synthesis of aluminophosphate (AlPO) and silicoaluminophosphate (SAPO) zeolite. As a high-throughput technique, 256 zeolite precursors with multiple formulations could be obtained within 2 h, while the product phase was regulated relative to the variant compositions.

Beyond nature's base pairs: machine learning-enabled design of DNA-stabilized silver nanoclusters.

Sequence-encoded biomolecules such as DNA and peptides are powerful programmable building blocks for nanomaterials. This paradigm is enabled by decades of prior research into how nucleic acid and amino acid sequences dictate biomolecular interactions. The properties of biomolecular materials can be significantly expanded with non-natural interactions, including metal ion coordination of nucleic acids and amino acids. However, these approaches present design challenges because it is often not well-understood how biomolecular sequence dictates such non-natural interactions. This Feature Article presents a case study in overcoming challenges in biomolecular materials with emerging approaches in data mining and machine learning for chemical design. We review progress in this area for a specific class of DNA-templated metal nanomaterials with complex sequence-to-property relationships: DNA-stabilized silver nanoclusters (AgN-DNAs) with bright, sequence-tuned fluorescence colors and promise for biophotonics applications. A brief overview of machine learning concepts is presented, and high-throughput experimental synthesis and characterization of AgN-DNAs are discussed. Then, recent progress in machine learning-guided design of DNA sequences that select for specific AgN-DNA fluorescence properties is reviewed. We conclude with emerging opportunities in machine learning-guided design and discovery of AgN-DNAs and other sequence-encoded biomolecular nanomaterials.

High-throughput concurrent synthesis of core-crosslinked star-polydimethylsiloxane using an arm-first approach

In this work we use RAFT crosslinking polymerisation coupled with a Chemspeed robotic synthesis platform to optimise conditions to produce PDMS-arm star polymers by an arm-first strategy.

A proxy for oxygen storage capacity from high-throughput screening and automated data analysis.

Oxygen storage and release is a foundational part of many key pathways in heterogeneous catalysis, such as the Mars-van Krevelen mechanism. However, direct measurement of oxygen storage capacity (OSC) is time-consuming and difficult to parallelise. To accelerate the discovery of stable high OSC rare-earth doped ceria-zirconia oxygen storage catalysts, a high-throughput robotic-based co-precipitation synthesis route was coupled with sequentially automated powder X-ray diffraction (PXRD), Raman and thermogravimetric analysis (TGA) characterisation of the resulting materials libraries. Automated extraction of data enabled rapid trend identification and provided a data set for the development of an OSC prediction model, investigating the significance of each extracted quantity towards OSC. The optimal OSC prediction model produced incorporated variables from only fast-to-measure analytical techniques and gave predicted values of OSC that agreed with experimental observations across an independent validation set. Those measured quantities that feature in the model emerge as proxies for OSC performance. The ability to predict the OSC of the materials accelerates the discovery of high-capacity oxygen storage materials and motivates the development of similar high-throughput workflows to identify candidate catalysts for other heterogeneous transformations.

Development of a two-phase flow reaction system for DNA-encoded amide coupling

Synthesis platforms are of particular interest to DNA-encoded library (DEL) technologies to facilitate chemistry development, building block validation, and high-throughput library synthesis.

How machine learning can accelerate electrocatalysis discovery and optimization.

Advances in machine learning (ML) provide the means to bypass bottlenecks in the discovery of new electrocatalysts using traditional approaches. In this review, we highlight the currently achieved work in ML-accelerated discovery and optimization of electrocatalysts via a tight collaboration between computational models and experiments. First, the applicability of available methods for constructing machine-learned potentials (MLPs), which provide accurate energies and forces for atomistic simulations, are discussed. Meanwhile, the current challenges for MLPs in the context of electrocatalysis are highlighted. Then, we review the recent progress in predicting catalytic activities using surrogate models, including microkinetic simulations and more global proxies thereof. Several typical applications of using ML to rationalize thermodynamic proxies and predict the adsorption and activation energies are also discussed. Next, recent developments of ML-assisted experiments for catalyst characterization, synthesis optimization and reaction condition optimization are illustrated. In particular, the applications in ML-enhanced spectra analysis and the use of ML to interpret experimental kinetic data are highlighted. Additionally, we also show how robotics are applied to high-throughput synthesis, characterization and testing of electrocatalysts to accelerate the materials exploration process and how this equipment can be assembled into self-driven laboratories.

High-throughput synthesis of nanoparticles using oscillating feedback microreactors: a selective scaling-out strategy

High-throughput synthesis of high-quality nanoparticles using passive and chaotic oscillating feedback microreactors to be selectively scaled out.

High-Performance Oxygen Evolution Reaction Electrocatalysts Discovered via High-Throughput Aerogel Synthesis

A combinatorial high-throughput aerogel synthesis method is developed to systematically study the synergistic catalytic effects of multiple non-noble metal elements. A large number of aerogels with different compositions were synthesized and the corresponding ternary phase diagrams of the composition–electrocatalytic performance were constructed. A batch of aerogel catalysts with outstanding catalytic performance and stability for the electrochemical oxygen evolution reaction (OER) were discovered. Amorphous Fe3Co3Ni2-(oxy)hydroxide with excellent electrocatalytic performance (Tafel slope of 49 mV dec–1 and η100 of 421.48 ± 6.41 mV) was found to achieve a mass activity of 611.23 A/gmetal at 1.63 V (vs RHE). X-ray photoemission spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) studies reveal that the incorporation of a third atom (Ni and Ce) into the binary aerogels enlarges the Co–O atomic distance and reduces the average valence state of Co, which in turn speed up the oxygen evolution reaction kinetics. This work puts forward a strategy for high-throughput synthesis and screening of electrocatalysts and provides valuable data sets for future machine learning and prediction of high-performance electrocatalysts.

Direct Deaminative Functionalization.

Selective functional group interconversions in complex molecular settings underpin many of the challenges facing modern organic synthesis. Currently, a privileged subset of functional groups dominates this landscape, while others, despite their abundance, are sorely underdeveloped. Amines epitomize this dichotomy; they are abundant but otherwise intransigent toward direct interconversion. Here, we report an approach that enables the direct conversion of amines to bromides, chlorides, iodides, phosphates, thioethers, and alcohols, the heart of which is a deaminative carbon-centered radical formation process using an anomeric amide reagent. Experimental and computational mechanistic studies demonstrate that successful deaminative functionalization relies not only on outcompeting the H-atom transfer to the incipient radical but also on the generation of polarity-matched, productive chain-carrying radicals that continue to react efficiently. The overall implications of this technology for interconverting amine libraries were evaluated via high-throughput parallel synthesis and applied in the development of one-pot diversification protocols.

Rapid fabrication and screening of tailored functional 3D biomaterials: Validation in bone tissue repair – Part II

Regenerative medicine strategies place increasingly sophisticated demands on 3D biomaterials to promote tissue formation at sites where tissue would otherwise not form. Ideally, the discovery/fabrication of the 3D scaffolds needs to be high-throughput and uniform to ensure quick and in-depth analysis in order to pinpoint appropriate chemical and mechanical properties of a biomaterial. Herein we present a versatile technique to screen new potential biocompatible acrylate-based 3D scaffolds with the ultimate aim of application in tissue repair. As part of this process, we identified an acrylate-based 3D porous scaffold that promoted cell proliferation followed by accelerated tissue formation, pre-requisites for tissue repair. Scaffolds were fabricated by a facile freeze-casting and an in-situ photo-polymerization route, embracing a high-throughput synthesis, screening and characterization protocol. The current studies demonstrate the dependence of cellular growth and vascularization on the porosity and intrinsic chemical nature of the scaffolds, with tuneable 3D scaffolds generated with large, interconnected pores suitable for cellular growth applied to skeletal reparation. Our studies showed increased cell proliferation, collagen and ALP expression, while chorioallantoic membrane assays indicated biocompatibility and demonstrated the angiogenic nature of the scaffolds. VEGRF2 expression in vivo observed throughout the 3D scaffolds in the absence of growth factor supplementation demonstrates a potential for angiogenesis. This novel platform provides an innovative approach to 3D scanning of synthetic biomaterials for tissue regeneration.

Fe Substitutions Improve Spectral Response of Bi2WO6-Based Photoanodes

The quest for a scalable solar fuel technology has stimulated a concerted effort to develop a metal oxide semiconductor for solar-driven photoelectrochemical water oxidation (oxygen evolution reaction) in an efficient and durable manner. So far, the search for such a metal oxide photoanode has highlighted the promise of Bi-based oxides, which have also been extensively studied for other photocatalyst applications. Bi2WO6 is a durable photocatalyst whose primary shortcoming is a 2.8 eV band gap that limits utilization of the solar spectrum. Improvements in visible photoresponse upon incorporation of Fe have been reported in the photocatalysis literature, motivating our use of high-throughput synthesis and photoelectrochemistry to determine the spectral photoresponse for Bi–W–Fe oxides synthesized under nonequilibrium conditions based on thermal oxidation of metallic films. Photoactivity down to 2 eV was achieved over a broad range of compositions, with detailed characterization of optimal compositions revealing that Fe incorporation increases the valence band position by 0.75 eV. Density functional theory calculations of Fe substitutions on W sites in Bi2WO6 are consistent with this valence band shift, providing a plausible explanation for the experiments. This Fe-mediated band tuning yields a ca. 2 eV band gap while retaining a turn-on potential for photoanodic current near 0.4 V versus RHE, which combined with the operational durability motivates continuous study and development of this promising class of metal oxide photoanodes.

In-Plate Chemical Synthesis of Isopeptide-Linked SUMOylated Peptide Fluorescence Polarization Reagents for High-Throughput Screening of SENP Preferences.

Small ubiquitin-like modifiers (SUMOs) are conjugated to protein substrates in cells to regulate their function. The attachment of SUMO family members SUMO1-3 to substrate proteins is reversed by specific isopeptidases called SENPs (sentrin-specific protease). Whereas SENPs are SUMO-isoform or linkage type specific, comprehensive analysis is missing. Furthermore, the underlying mechanism of SENP linkage specificity remains unclear. We present a high-throughput synthesis of 83 isopeptide-linked SUMO-based fluorescence polarization reagents to study enzyme preferences. The assay reagents were synthesized via a native chemical ligation-desulfurization protocol between 11-mer peptides containing a γ-thiolysine and a SUMO3 thioester. Subsequently, five recombinantly expressed SENPs were screened using these assay reagents to reveal their deconjugation activity and substrate preferences. In general, we observed that SENP1 is the most active and nonselective SENP while SENP6 and SENP7 show the least activity. Furthermore, SENPs differentially process peptides derived from SUMO1-3, who form a minimalistic representation of diSUMO chains. To validate our findings, five distinct isopeptide-linked diSUMO chains were chemically synthesized and proteolysis was monitored using a gel-based read-out.

Integrated and automated high-throughput purification of libraries on microscale.

We herein report the development of an automation platform for rapid purification and quantification of chemical libraries including reformatting of chemical matter to 10mM DMSO stock solutions. This fully integrated workflow features tailored conditions for preparative reversed-phase (RP) HPLC-MS on microscale based on analytical data, online fraction QC and CAD-based quantification as well as automated reformatting to enable rapid purification of chemical libraries. This automated workflow is entirely solution-based, eliminating the need to weigh or handle solids. This increases process efficiency and creates a link between high-throughput synthesis and profiling of novel chemical matter with respect to biological and physicochemical properties in relevant assays.

Zinc oxide tetrapod sponges for environmental pollutant monitoring and degradation

Environmental monitoring systems enable the collection of information about the various environmental parameters, pollution levels, and the presence of environmental hazards affecting human and marine life. Highly sensitive, stable, and low-power-consuming sensors are vital for such operations. Nanomaterials with different surface morphologies can play a vital role in multiple applications, such as gas sensors, photocatalysts, erosion monitoring, or fine dust sensor. Zinc oxide (ZnO) tetrapod, in particular, shows 3D morphologies that exhibit exciting properties, making them applicable in several device engineering. This work provides a simple yet high-throughput single-step synthesis of ZnO tetrapod with different arm sizes using the flame transport method at various growth conditions. The physicochemical and structural properties have been deeply investigated to shed light on the formation of these 3D structures. The detailed mechanism of the ZnO tetrapod as a gas monitoring material and a photocatalyst has been presented in detail. The sponge-based ZnO gas sensor can selectively sense NO2 gas with a limit of detection (LOD) value of 8.56 ppb. In addition, ZnO tetrapods samples exhibit high photocatalytic activity toward methylene blue and methyl orange degradation under UV illumination. The reaction rate constants of 3.6 (2)·10−4 s−1 and 1.7 (1)·10−4 s−1 are determined for the photocatalytic decomposition of methylene blue and methyl orange, respectively. The results suggest that ZnO tetrapod-based sponges can be a promising material for building next-generation pollution monitoring and degradation systems.

Cell-cell communications: new insights into targeting efficacy of phytochemical adjuvants on tight junctions and pathophysiology of various malignancies.

Cancer is a cellular impairment disorder characterized by the loss of cell cycle regulation leading to aberrant cell proliferation. Cell-cell communication plays a crucial role in cell signaling which is highly disrupted in various malignancies. Tight junctions (TJs) are major proteins that regulate the proper communication, and the dysregulation of TJ proteins makes these tumor cells more aggressive, leading to tumor invasion and metastasis. Hence targeting TJs might be a novel insight towards addressing these highly invasive, metastatic tumors. Due to the prohibitive costs of treatments, side effects, and development of resistance, herbal medications comprising bioactive ingredients have become more popular for various human ailments. Unfortunately, the importance of natural compounds has significantly reduced due to the development of modern synthetic techniques to formulate drugs. However, the pharmaceutical industry that adopts chemistry-based drug development in combination with high throughput synthesis have not resulted in the expected drug productivity. Hence, the focus was shifted back to natural compounds in search of novel drugs with advanced technology to isolate the biologically active compound from the natural ones. The current review delivers the importance of TJ regulation, promoting it through phytochemicals to target malignant tumor cells.

A rapid and systematic approach for the optimization of radio thin-layer chromatography resolution

Radiopharmaceutical analysis is limited by conventional methods. Radio-HPLC may be inaccurate for some compounds (e.g., 18F-radiopharmaceuticals) due to radionuclide sequester. Radio-TLC is simpler, faster, and detects all species but has limited resolution. Imaging-based readout of TLC plates (e.g., using Cerenkov luminescence imaging) can improve readout resolution, but the underlying chromatographic separation efficiency may be insufficient to resolve chemically similar species such as product and precursor-derived impurities. This study applies a systematic mobile phase optimization method, PRISMA, to improve radio-TLC resolution. The PRISMA method optimizes the mobile phase by selecting the correct solvent, optimizing solvent polarity, and optimizing composition. Without prior knowledge of impurities and by simply observing the separation resolution between a radiopharmaceutical and its nearest radioactive or non-radioactive impurities (observed via UV imaging) for different mobile phases, the PRISMA method enabled the development of high-resolution separation conditions for a wide range of 18F-radiopharmaceuticals ( [18F]PBR-06, [18F]FEPPA, [18F]Fallypride, [18F]FPEB, and [18F]FDOPA). Each optimization required a single batch of crude radiopharmaceutical and a few hours. Interestingly, the optimized TLC method provided greater accuracy (compared to other published TLC methods) in determining the product abundance of one radiopharmaceutical studied in more depth ( [18F]Fallypride) and was capable of resolving a comparable number of species as isocratic radio-HPLC. We used the PRISMA-optimized mobile phase for [18F]FPEB in combination with multi-lane radio-TLC techniques to evaluate reaction performance during high-throughput synthesis optimization of [18F]FPEB. The PRISMA methodology, in combination with high-resolution radio-TLC readout, enables a rapid and systematic approach to achieving high-resolution and accurate analysis of radiopharmaceuticals without the need for radio-HPLC.

High throughput synthesis of BaSnO3 microcrystals by molten salt technique

This paper reports the high-throughput synthesis of BaSnO3 microcrystals using an environmentally friendly and energy-efficient process. Our method is based on the molten salt technique and uses bio-friendly salts NaCl and KCl. BaCO3 and SnO2 were used as the sources for Ba and Sn, respectively. Synthesis was carried out at several different temperatures to find the optimum temperature needed to produce the high-quality material. Samples were thoroughly characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and uv–vis spectroscopy. It was found that the formation of BaSnO3 starts at temperatures as low as 700 °C. Analysis of XRD peaks showed that the sample possesses a cubic structure with a lattice parameter ranging from 4.157 Å to 4.201 Å. SEM micrographs showed the samples to comprise uniformly distributed micron-sized cubes. Analysis of uv–vis spectroscopy data showed the BaSnO3 samples to be transparent in the visible range and opaque in the ultraviolet range of the spectrum. Samples prepared at 700 °C showed a bandgap of 2.72 eV, which increased with an increase in the synthesis temperature and became 3.14 eV for the samples synthesized at 850 °C.

Mixing Characteristic and High-Throughput Synthesis of Cadmium Sulfide Nanoparticles with Cubic Hexagonal Phase Junctions in a Chaotic Millireactor.

A four-stage oscillating feedback millireactor with splitters (S-OFM) was designed to improve the mixing performance based on chaotic advection. Three-dimensional CFD simulations were used to investigate its flow characteristics and mixing performance, and the generation mechanisms of secondary flows were examined. The results show that the mixing index (MIcup) increased with the increase in the Reynolds number (Re), and MIcup could reach 99.8% at Re = 663. Poincaré mapping and Kolmogorov entropy were adopted to characterize the chaotic advection intensity, which indicates that there is a intensity increase with the increase in Re. In addition, the results of Villermaux-Dushman experiments demonstrate that S-OFM performs excellently, and the mixing time could reach 1.04 ms at Re = 2764. Finally, S-OFM was successfully used to synthesize CdS nanoparticles with cubic hexagonal phase junctions. At a flow rate of 180 mL/min, the average particle size was 10.5 nm and the particle size distribution was narrow (with a coefficient of variation of 0.14).

Optimized design of block copolymers with covarying properties for nanolithography.

The ability to impart multiple covarying properties into a single material represents a grand challenge in manufacturing. In the design of block copolymers (BCPs) for directed self-assembly and nanolithography, materials often balance orthogonal properties to meet constraints related to processing, structure and defectivity. Although iterative synthesis strategies deliver BCPs with attractive properties, identifying materials with all the required attributes has been difficult. Here we report a high-throughput synthesis and characterization platform for the discovery and optimization of BCPs with A-block-(B-random-C) architectures for lithographic patterning in semiconductor manufacturing. Starting from a parent BCP and using thiol-epoxy 'click' chemistry, we synthesize a library of BCPs that cover a large and complex parameter space. This allows us to readily identify feature-size-dependent BCP chemistries for 8-20-nm-pitch patterns. These blocks have similar surface energies for directed self-assembly, and control over the segregation strength to optimize the structure (favoured at higher segregation strengths) and defectivity (favoured at lower segregation strengths).

A high-throughput catalyst synthesis system for Ag-based catalysts

Ag-based catalysts have been used in many practical reactions, such as p-nitrophenol reduction, due to the advantages of low cost and excellent activity. In order to facilitate the development of Ag-based catalysts, it may be helpful to use automated equipment for experiments. In this study, a system for the high-throughput synthesis of Ag-based catalysts was developed based on a facile impregnation method. Notably, the system automates the batch synthesis of Ag-based catalysts by setting the catalyst formulation in a dedicated software. Moreover, the software used employs the ant colony algorithm to optimize the synthesis path and improve the synthesis efficiency. The catalysts obtained from the high-throughput system are found to be similar to the manually prepared samples based on comparison of characterization results. In addition, experiments also reveal that this high-throughput system is capable of achieving high-throughput synthesis of Ag-based catalysts at the gram level. The synthesis of Pt-Ag bimetallic catalysts shows that this high-throughput system can be effectively used for exploratory experiments. This work paves the way for a high-throughput technique to synthesize Ag-based catalysts in a short period of time, which could be extended to the preparation of other catalyst systems. Moreover, the high-throughput synthesis system of Ag-based catalysts provides a feasible prerequisite for subsequent high-throughput characterization, which is a significant advancement in the development of industrial catalysts.