An integrated self-optimizing programmable chemical synthesis and reaction engine

Robotic platforms for chemistry are developing rapidly but most systems are not currently able to adapt to changing circumstances in real-time. We present a dynamically programmable system capable of making, optimizing, and discovering new molecules which utilizes seven sensors that continuously monitor the reaction. By developing a dynamic programming language, we demonstrate the 10-fold scale-up of a highly exothermic oxidation reaction, end point detection, as well as detecting critical hardware failures. We also show how the use of in-line spectroscopy such as HPLC, Raman, and NMR can be used for closed-loop optimization of reactions, exemplified using Van Leusen oxazole synthesis, a four-component Ugi condensation and manganese-catalysed epoxidation reactions, as well as two previously unreported reactions, discovered from a selected chemical space, providing up to 50% yield improvement over 25–50 iterations. Finally, we demonstrate an experimental pipeline to explore a trifluoromethylations reaction space, that discovers new molecules

Heterogeneous Catalysis "On Demand": Mechanically Controlled Catalytic Activity of a Metal Surface

A metal surface passivated with a tightly packed self assembled monolayer (SAM) can be made catalytically active upon the metal's mechanical deformation. This deformation renders the SAM sparser and exposes additional catalytic sites on the metal's surface. If the deformation is elastic, return of the metal to the original shape "heals" the SAM and nearly extinguishes the catalytic activity. Kelvin probe force microscopy and theoretical considerations both indicate that the catalytic domains "opening up" in the deformed SAM are of nanoscopic dimensions

Heterogeneous Catalysis “On Demand”: Mechanically Controlled Catalytic Activity of a Metal Surface

A metal surface passivated with a tightly packed self-assembled monolayer (SAM) can be made catalytically active upon the metal’s mechanical deformation. This deformation renders the SAM sparser and exposes additional catalytic sites on the metal’s surface. If the deformation is elastic, return of the metal to the original shape “heals” the SAM and nearly extinguishes the catalytic activity. Kelvin probe force microscopy and theoretical considerations both indicate that the catalytic domains “opening up” in the deformed SAM are of nanoscopic dimensions

Metal-Organic Framework swimmers with Energy-Efficient Autonomous Motility

Placed at a water/air interface, particles of porphyrin-based MOFs (metal-organic frameworks) cut from large-area films display efficient, multiple-use autonomous motility powered by release of solvents incorporated in the MOF matrix and directionality dictated by their shapes. The particles can be refueled multiple times and can achieve speeds of ca. 200 mm??s-1 with high kinetic energy per unit of chemical fuel expended (>50 ??J??g-1). Efficiency of motion depends on the nature of the fuel used as well as the microstructure and surface wettability of the MOF surface. When multiple movers are present at the interface, they organize into open structures that exhibit collective, time-periodic motions

DMPC Phospholipid Bilayer as a Potential Interface for Human Cystatin C Oligomerization: Analysis of Protein-Liposome Interactions Using NMR Spectroscopy

Studies revolving around mechanisms responsible for the development of amyloid-based diseases lay the foundations for the recognition of molecular targets of future to-be-developed treatments. However, the vast number of peptides and proteins known to be responsible for fibril formation, combined with their complexity and complexity of their interactions with various cellular components, renders this task extremely difficult and time-consuming. One of these proteins, human cystatin C (hCC), is a well-known and studied cysteine-protease inhibitor. While being a monomer in physiological conditions, under the necessary stimulus—usually a mutation, it tends to form fibrils, which later participate in the disease development. This process can potentially be regulated (in several ways) by many cellular components and it is being hypothesized that the cell membrane might play a key role in the oligomerization pathway. Studies involving cell membranes pose several difficulties; therefore, an alternative in the form of membrane mimetics is a very attractive solution. Here, we would like to present the first study on hCC oligomerization under the influence of phospholipid liposomes, acting as a membrane mimetic. The protein–mimetic interactions are studied utilizing circular dichroism, nuclear magnetic resonance, and size exclusion chromatography

Targeted crystallization of mixed-charge nanoparticles in lysosomes induces selective death of cancer cells

Lysosomes have become an important target for anticancer therapeutics because lysosomal cell death bypasses the classical caspase-dependent apoptosis pathway, enabling the targeting of apoptosis- and drug-resistant cancers. However, only a few small molecules-mostly repurposed drugs-have been tested so far, and these typically exhibit low cancer selectivity, making them suitable only for combination therapies. Here, we show that mixed-charge nanoparticles covered with certain ratios of positively and negatively charged ligands can selectively target lysosomes in cancerous cells while exhibiting only marginal cytotoxicity towards normal cells. This selectivity results from distinct pH-dependent aggregation events, starting from the formation of small, endocytosis-prone clusters at cell surfaces and ending with the formation of large and well-ordered nanoparticle assemblies and crystals inside cancer lysosomes. These assemblies cannot be cleared by exocytosis and cause lysosome swelling, which gradually disrupts the integrity of lysosomal membranes, ultimately impairing lysosomal functions and triggering cell death. Mixed-charge nanoparticles preferentially assemble inside the lysosomes of cancer cells, which causes lysosomal membrane disruption and lysosome-dependent cell death in cancer but not in healthy cells

Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters

<p>Datasets related to the paper "Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters".</p> <ul> <li>Structures of all building blocks (cap_building_blocks.csv, bridge_building_blocks.csv, core_building_blocks.csv)</li> <li>Seed dataset of OSL emitters and their spectroscopic properties (seed_dataset_exp.csv)</li> <li>Full dataset of OSL emitters and their spectroscopic properties (full_dataset_exp.csv)</li> <li>Selected computed excited-state descriptors for training the graph neural network (seed_dataset_tddft.csv)</li> <li>Full dataset of computed excited-state descriptors (full_dataset_comp.csv)</li> <li>Raw HPLC-MS data of all synthesis – characterization runs (hplcms_runs.zip)</li> <li>Raw NMR data of all fully characterized compounds (nmr_data.zip)</li> </ul&gt

Delocalized, asynchronous, closed-loop discovery of organic laser emitters

Contemporary materials discovery requires intricate sequences of synthesis, formulation, and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy that enabled delocalized and asynchronous design-make-test-analyze cycles. We showcased this approach through the exploration of molecular gain materials for organic solid-state lasers as a frontier application in molecular optoelectronics. Distributed robotic synthesis and in-line property characterization, orchestrated by a cloud-based artificial intelligence experiment planner, resulted in the discovery of 21 new state-of-the-art materials. Gram-scale synthesis ultimately allowed for the verification of best-in-class stimulated emission in a thin-film device. Demonstrating the asynchronous integration of five laboratories across the globe, this workflow provides a blueprint for delocalizing—and democratizing—scientific discovery

Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters

Contemporary materials discovery requires intricate sequences of synthesis, formulation and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy that enables delocalized and asynchronous design–make–test–analyze cycles. We showcase this approach through the exploration of molecular gain materials for organic solid-state lasers as a frontier application in molecular optoelectronics. Distributed robotic synthesis and in-line property characterization, orchestrated by a cloud-based AI experiment planner, resulted in the discovery of 21 new state-of-the-art materials. Automated gram-scale synthesis ultimately allowed for the verification of best-in-class stimulated emission in a thin-film device. Demonstrating the asynchronous integration of five laboratories across the globe, this workflow provides a blueprint for delocalizing – and democratizing – scientific discovery