Using automated synthesis to understand the role of side chains on molecular charge transport

Single-Molecule Conductance of Neutral Closed-Shell and Open-Shell Diradical Indenofluorenes

Organic diradicals are highly promising candidates as future components in molecular electronic and spintronic devices because of their low spin-orbit coupling. To advance toward final circuit realizations, a thorough knowledge of the behavior of diradicals within a single-molecule junction framework is imperative. In this work, we have measured for the first time the single-molecule conductance of a neutral open-shell diradical compound, a [2,1-b] isomer of indenofluorene (IF). Our results reveal that the conductance of the [2,1-b] isomer is about 1 order of magnitude higher than that of the corresponding closed-shell regioisomer [1,2-b] IF. This is significant, as it fundamentally demonstrates the possibility of forming stable single-molecule junctions using neutral diradical compounds which are also highly conducting. This opens up a new approach to the development of externally addressable spintronic devices operable at room temperature.

From Molecular Electronics to Molecular Intelligence

Molecular electronics is a field that explores the ultimate limits of electronic device dimensions by using individual molecules as operable electronic devices. Over the past five decades since the proposal of a molecular rectifier by Aviram and Ratner in 1974 ( Chem. Phys. Lett.1974,29, 277-283), researchers have developed various fabrication and characterization techniques to explore the electrical properties of molecules. With the push of electrical characterizations and data analysis methodologies, the reproducibility issues of the single-molecule conductance measurement have been chiefly resolved, and the origins of conductance variation among different devices have been investigated. Numerous prototypical molecular electronic devices with external physical and chemical stimuli have been demonstrated based on the advances of instrumental and methodological developments. These devices enable functions such as switching, logic computing, and synaptic-like computing. However, as the goal of molecular electronics, how can molecular-based intelligence be achieved through single-molecule electronic devices? At the fiftieth anniversary of molecular electronics, we try to answer this question by summarizing recent progress and providing an outlook on single-molecule electronics. First, we review the fabrication methodologies for molecular junctions, which provide the foundation of molecular electronics. Second, the preliminary efforts of molecular logic devices toward integration circuits are discussed for future potential intelligent applications. Third, some molecular devices with sensing applications through physical and chemical stimuli are introduced, demonstrating phenomena at a single-molecule scale beyond conventional macroscopic devices. From this perspective, we summarize the current challenges and outlook prospects by describing the concepts of "AI for single-molecule electronics" and "single-molecule electronics for AI".

Massive acceleration of SN2 reaction using the oriented external electric field

Nucleophilic substitution is one of the most fundamental chemical reactions, and the pursuit of high reaction rates of the reaction is one of the ultimate goals in catalytic and organic chemistry. The reaction barrier of the nucleophilic substitution originates from the highly polar nature of the transition state that can be stabilized under the electric field created by the solvent environment. However, the intensity of the induced solvent-electric field is relatively small due to the random orientation of solvent molecules, which hinders the catalytic effects and restricts the reaction rates. This work shows that oriented external electric fields applied within a confined nanogap between two nanoscopic tips could accelerate the Menshutkin reaction by more than four orders of magnitude (over 39 000 times). The theoretical calculations reveal that the electric field inside the nanogap reduces the energy barrier to increase the reaction rate. Our work suggests the great potential of electrostatic catalysis for green synthesis in the future.

Machine-Guided Discovery of Acrylate Photopolymer Compositions

Additive manufacturing (AM) can be advanced by the diverse characteristics offered by thermoplastic and thermoset polymers and the further benefits of copolymerization. However, the availability of suitable polymeric materials for AM is limited and may not always be ideal for specific applications. Additionally, the extensive number of potential monomers and their combinations make experimental determination of resin compositions extremely time-consuming and costly. To overcome these challenges, we develop an active learning (AL) approach to effectively choose compositions in a ternary monomer space ranging from rigid to elastomeric. Our AL algorithm dynamically suggests monomer composition ratios for the subsequent round of testing, allowing us to efficiently build a robust machine learning (ML) model capable of predicting polymer properties, including Young's modulus, peak stress, ultimate strain, and Shore A hardness based on composition while minimizing the number of experiments. As a demonstration of the effectiveness of our approach, we use the ML model to drive material selection for a specific property, namely, Young's modulus. The results indicate that the ML model can be used to select material compositions within at least 10% of a targeted value of Young's modulus. We then use the materials designed by the ML model to 3D print a multimaterial "hand" with soft "skin" and rigid "bones". This work presents a promising tool for enabling informed AM material selection tailored to user specifications and accelerating material discovery using a limited monomer space.

Effect of Hydrodynamic Interactions and Flow on Charge Transport in Redox-Active Polymer Solutions

Redox-active polymers (RAPs) are a subclass of polyelectrolytes that can store charge and undergo redox self-exchange reactions. RAPs are of great interest in the field of redox flow batteries (RFBs) due to their ability to quickly charge and discharge, their chemical modularity, and their molecular size. However, designing RAPs for efficient charge transport at the molecular level requires a fundamental understanding of the charge transport mechanisms that occur in RFBs. Previous work from our group has explored these mechanisms, and in this paper, we seek to improve upon the previous model by incorporating both hydrodynamic interactions (HIs) and out-of-equilibrium dynamics, which are both highly pertinent to flow battery systems. We use a hybrid Brownian dynamics and Monte Carlo simulation to model redox-active polymer chains in both dilute and semidilute solutions. This model is used to show that HI is an important feature when charge hopping is not the major mechanism for charge displacement and leads to more rapid segmental and translational motion of polymer chains that expedites charge transport at low polymer concentrations. We demonstrate that strong extensional flows may result in either enhanced or decreased transport depending on the fraction of charges present on the RAP chain. We show that flow not only can promote charge transport by extending polymer conformations but can also suppress nonadjacent charge hopping processes that are important for transport at high charge fractions. Shear flows can similarly enhance charge transport through chain extension, but tumbling dynamics lead to oscillatory displacements that become dominant features with high charge fractions and strong flows.

Influence of Peripheral Alkyl Groups on Junction Configurations in Single-Molecule Electronics

The addition of a lateral alkyl chain is a well-known strategy to reduce π-stacked ensembles of molecules in solution, with the intention to minimize the interactions between the molecules' backbones. In this paper, we study whether this concept generalizes to single-molecule junctions by using a combination of mechanically controllable break junction (MCBJ) measurements and clustering-based data analysis with two small series of model compounds decorated with various bulky groups. The systematic study suggests that introducing alkyl side chains also favors the formation of electrode-molecule configurations that are not observed in their absence, thereby inducing broadening of the conductance peak in the one-dimensional histograms. Thus, the introduction of alkyl chains in aromatic compounds for molecular electronics must be carefully designed and optimized for the specific purpose, balancing between increased solubility and the possibility of additional junction configurations.

Enhanced Electron Transport in Nonconjugated Radical Oligomers Occurs by Tunneling

Incorporating temperature- and air-stable organic radical species into molecular designs is a potentially advantageous means of controlling the properties of electronic materials. However, we still lack a complete understanding of the structure-property relationships of organic radical species at the molecular level. In this work, the charge transport properties of (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) radical-containing nonconjugated molecules are studied using single-molecule charge transport experiments and molecular modeling. Importantly, the TEMPO pendant groups promote temperature-independent molecular charge transport in the tunneling region relative to the quenched and closed-shell phenyl pendant groups. Results from molecular modeling show that the TEMPO radicals interact with the gold metal electrodes near the interface to facilitate a high-conductance conformation. Overall, the large enhancement of charge transport by incorporation of open-shell species into a single nonconjugated molecular component opens exciting avenues for implementing molecular engineering in the development of next-generation electronic devices based on novel nonconjugated radical materials.

Hard Potato: A Python Library to Control Commercial Potentiostats and to Automate Electrochemical Experiments

Here, we develop and show the use of an open-source Python library to control commercial potentiostats. It standardizes the commands for different potentiostat models, opening the possibility to perform automated experiments independently of the instrument used. At the time of this writing, we have included potentiostats from CH Instruments (models 1205B, 1242B, 601E, and 760E) and PalmSens (model Emstat Pico), although the open-source nature of the library allows for more to be included in the future. To showcase the general workflow and implementation of a real experiment, we have automated the Randles-Ševčı́k methodology to determine the diffusion coefficient of a redox-active species in solution using cyclic voltammetry. This was accomplished by writing a Python script that includes data acquisition, data analysis, and simulation. The total run time was 1 min and 40 s, well below the time it would take even an experienced electrochemist to apply the methodology in a traditional manner. Our library has potential applications that expand beyond the automation of simple repetitive tasks; for example, it can interface with peripheral hardware and well-established third-party Python libraries as part of a more complex and intelligent setup that relies on laboratory automation, advanced optimization, and machine learning.