Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery.

Solid polymer electrolytes (SPEs) have the potential to improve lithium-ion batteries by enhancing safety and enabling higher energy densities. However, SPEs suffer from significantly lower ionic conductivity than liquid and solid ceramic electrolytes, limiting their adoption in functional batteries. To facilitate more rapid discovery of high ionic conductivity SPEs, we developed a chemistry-informed machine learning model that accurately predicts ionic conductivity of SPEs. The model was trained on SPE ionic conductivity data from hundreds of experimental publications. Our chemistry-informed model encodes the Arrhenius equation, which describes temperature activated processes, into the readout layer of a state-of-the-art message passing neural network and has significantly improved accuracy over models that do not encode temperature dependence. Chemically informed readout layers are compatible with deep learning for other property prediction tasks and are especially useful where limited training data are available. Using the trained model, ionic conductivity values were predicted for several thousand candidate SPE formulations, allowing us to identify promising candidate SPEs. We also generated predictions for several different anions in poly(ethylene oxide) and poly(trimethylene carbonate), demonstrating the utility of our model in identifying descriptors for SPE ionic conductivity.

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties.

Polymer electrolytes are promising candidates for the next generation lithium-ion battery technology. Large scale screening of polymer electrolytes is hindered by the significant cost of molecular dynamics (MD) simulation in amorphous systems: the amorphous structure of polymers requires multiple, repeated sampling to reduce noise and the slow relaxation requires long simulation time for convergence. Here, we accelerate the screening with a multi-task graph neural network that learns from a large amount of noisy, unconverged, short MD data and a small number of converged, long MD data. We achieve accurate predictions of 4 different converged properties and screen a space of 6247 polymers that is orders of magnitude larger than previous computational studies. Further, we extract several design principles for polymer electrolytes and provide an open dataset for the community. Our approach could be applicable to a broad class of material discovery problems that involve the simulation of complex, amorphous materials.

Harnessing Ionic Selectivity in Acetyltransferase Chemoproteomic Probes.

Chemical proteomics provides a powerful strategy for the high-throughput assignment of enzyme function or inhibitor selectivity. However, identifying optimized probes for an enzyme family member of interest and differentiating signal from the background remain persistent challenges in the field. To address this obstacle, here we report a physiochemical discernment strategy for optimizing chemical proteomics based on the coenzyme A (CoA) cofactor. First, we synthesize a pair of CoA-based sepharose pulldown resins differentiated by a single negatively charged residue and find this change alters their capture properties in gel-based profiling experiments. Next, we integrate these probes with quantitative proteomics and benchmark analysis of "probe selectivity" versus traditional "competitive chemical proteomics." This reveals that the former is well-suited for the identification of optimized pulldown probes for specific enzyme family members, while the latter may have advantages in discovery applications. Finally, we apply our anionic CoA pulldown probe to evaluate the selectivity of a recently reported small molecule N-terminal acetyltransferase inhibitor. These studies further validate the use of physical discriminant strategies in chemoproteomic hit identification and demonstrate how CoA-based chemoproteomic probes can be used to evaluate the selectivity of small molecule protein acetyltransferase inhibitors, an emerging class of preclinical therapeutic agents.

Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethylene Glycol-Based Lithium Electrolytes.

Molecular details often dictate the macroscopic properties of materials, yet due to their vastly different length scales, relationships between molecular structure and bulk properties can be difficult to predict a priori, requiring Edisonian optimizations and preventing rational design. Here, we introduce an easy-to-execute strategy based on linear free energy relationships (LFERs) that enables quantitative correlation and prediction of how molecular modifications, i.e., substituents, impact the ensemble properties of materials. First, we developed substituent parameters based on inexpensive, DFT-computed energetics of elementary pairwise interactions between a given substituent and other constant components of the material. These substituent parameters were then used as inputs to regression analyses of experimentally measured bulk properties, generating a predictive statistical model. We applied this approach to a widely studied class of electrolyte materials: oligo-ethylene glycol (OEG)-LiTFSI mixtures; the resulting model enables elucidation of fundamental physical principles that govern the properties of these electrolytes and also enables prediction of the properties of novel, improved OEG-LiTFSI-based electrolytes. The framework presented here for using context-specific substituent parameters will potentially enhance the throughput of screening new molecular designs for next-generation energy storage devices and other materials-oriented contexts where classical substituent parameters (e.g., Hammett parameters) may not be available or effective.

An N-Heterocyclic-Carbene-Derived Distonic Radical Cation.

We present the discovery of a novel radical cation formed through one-electron oxidation of an N-heterocyclic carbene-carbodiimide (NHC-CDI) zwitterionic adduct. This compound possesses a distonic electronic structure (spatially separate spin and charge regions) and displays persistence under ambient conditions. We demonstrate its application in a redox-flow battery exhibiting minimal voltage hysteresis, a flat voltage plateau, high Coulombic efficiency, and no performance decay for at least 100 cycles. The chemical tunability of NHCs and CDIs suggests that this approach could provide a general entry to redox-active NHC-CDI adducts and their persistent radical ions for various applications.

Stretchable self-healable semiconducting polymer film for active-matrix strain-sensing array.

Skin-like sensory devices should be stretchable and self-healable to meet the demands for future electronic skin applications. Despite recent notable advances in skin-inspired electronic materials, it remains challenging to confer these desired functionalities to an active semiconductor. Here, we report a strain-sensitive, stretchable, and autonomously self-healable semiconducting film achieved through blending of a polymer semiconductor and a self-healable elastomer, both of which are dynamically cross-linked by metal coordination. We observed that by controlling the percolation threshold of the polymer semiconductor, the blend film became strain sensitive, with a gauge factor of 5.75 × 105 at 100% strain in a stretchable transistor. The blend film is also highly stretchable (fracture strain, >1300%) and autonomously self-healable at room temperature. We proceed to demonstrate a fully integrated 5 × 5 stretchable active-matrix transistor sensor array capable of detecting strain distribution through surface deformation.

Decoupling of mechanical properties and ionic conductivity in supramolecular lithium ion conductors.

The emergence of wearable electronics puts batteries closer to the human skin, exacerbating the need for battery materials that are robust, highly ionically conductive, and stretchable. Herein, we introduce a supramolecular design as an effective strategy to overcome the canonical tradeoff between mechanical robustness and ionic conductivity in polymer electrolytes. The supramolecular lithium ion conductor utilizes orthogonally functional H-bonding domains and ion-conducting domains to create a polymer electrolyte with unprecedented toughness (29.3 MJ m-3) and high ionic conductivity (1.2 × 10-4 S cm-1 at 25 °C). Implementation of the supramolecular ion conductor as a binder material allows for the creation of stretchable lithium-ion battery electrodes with strain capability of over 900% via a conventional slurry process. The supramolecular nature of these battery components enables intimate bonding at the electrode-electrolyte interface. Combination of these stretchable components leads to a stretchable battery with a capacity of 1.1 mAh cm-2 that functions even when stretched to 70% strain. The method reported here of decoupling ionic conductivity from mechanical properties opens a promising route to create high-toughness ion transport materials for energy storage applications.

High-Rate and Large-Capacity Lithium Metal Anode Enabled by Volume Conformal and Self-Healable Composite Polymer Electrolyte.

The widespread implementation of lithium-metal batteries (LMBs) with Li metal anodes of high energy density has long been prevented due to the safety concern of dendrite-related failure. Here a solid-liquid hybrid electrolyte consisting of composite polymer electrolyte (CPE) soaked with liquid electrolyte is reported. The CPE membrane composes of self-healing polymer and Li+-conducting nanoparticles. The electrodeposited lithium metal in a uniform, smooth, and dense behavior is achieved using a hybrid electrolyte, rather than dendritic and pulverized structure for a conventional separator. The Li foil symmetric cells can deliver remarkable cycling performance at ultrahigh current density up to 20 mA cm-2 with an extremely low voltage hysteresis over 1500 cycles. A large areal capacity of 10 mAh cm-2 at 10 mA cm-2 could also be obtained. Furthermore, the Li|Li4Ti5O12 cells based on the hybrid electrolyte achieve a higher specific capacity and longer cycling life than those using conventional separators. The superior performances are mainly attributed to strong adhesion, volume conformity, and self-healing functionality of CPE, providing a novel approach and a significant step toward cost-effective and large-scalable LMBs.

Inhibition of tumour necrosis factor alpha in the R6/2 mouse model of Huntington's disease by etanercept treatment.

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by the expansion of the CAG repeat in exon 1 of the huntingtin (HTT) gene, which results in a mutant protein with an extended polyglutamine tract. Inflammation occurs in both the brain and the periphery of HD patients and mouse models, with increases in brain and/or plasma levels of neurotoxic TNFα and several other proinflammatory cytokines. TNFα promotes the generation of many of these cytokines, such as IL6, which raises the possibility that TNFα is central to the inflammatory milieu associated with HD. A number of mouse studies have reported that the suppression of chronic immune activation during HD has beneficial consequences. Here, we investigated whether TNFα contributes to the peripheral inflammation that occurs in the R6/2 mouse model, and whether the in vivo blockade of TNFα, via etanercept treatment, can modify disease progression. We found that etanercept treatment normalised the elevated plasma levels of some cytokines. This did not modify the progression of certain behavioural measures, but slightly ameliorated brain weight loss, possibly related to a reduction in the elevated striatal level of soluble TNFα.

Multi-scale ordering in highly stretchable polymer semiconducting films.

Stretchable semiconducting polymers have been developed as a key component to enable skin-like wearable electronics, but their electrical performance must be improved to enable more advanced functionalities. Here, we report a solution processing approach that can achieve multi-scale ordering and alignment of conjugated polymers in stretchable semiconductors to substantially improve their charge carrier mobility. Using solution shearing with a patterned microtrench coating blade, macroscale alignment of conjugated-polymer nanostructures was achieved along the charge transport direction. In conjunction, the nanoscale spatial confinement aligns chain conformation and promotes short-range π-π ordering, substantially reducing the energetic barrier for charge carrier transport. As a result, the mobilities of stretchable conjugated-polymer films have been enhanced up to threefold and maintained under a strain up to 100%. This method may also serve as the basis for large-area manufacturing of stretchable semiconducting films, as demonstrated by the roll-to-roll coating of metre-scale films.

A Dual-Crosslinking Design for Resilient Lithium-Ion Conductors.

Solid-state electrolyte materials are attractive options for meeting the safety and performance needs of advanced lithium-based rechargeable battery technologies because of their improved mechanical and thermal stability compared to liquid electrolytes. However, there is typically a tradeoff between mechanical and electrochemical performance. Here an elastic Li-ion conductor with dual covalent and dynamic hydrogen bonding crosslinks is described to provide high mechanical resilience without sacrificing the room-temperature ionic conductivity. A solid-state lithium-metal/LiFePO4 cell with this resilient electrolyte can operate at room temperature with a high cathode capacity of 152 mAh g-1 for 300 cycles and can maintain operation even after being subjected to intense mechanical impact testing. This new dual crosslinking design provides robust mechanical properties while maintaining ionic conductivity similar to state-of-the-art polymer-based electrolytes. This approach opens a route toward stable, high-performance operation of solid-state batteries even under extreme abuse.

A Chemical Signature for Cytidine Acetylation in RNA.

N4-acetylcytidine (ac4C) is a highly conserved modified RNA nucleobase whose formation is catalyzed by the disease-associated N-acetyltransferase 10 (NAT10). Here we report a sensitive chemical method to localize ac4C in RNA. Specifically, we characterize the susceptibility of ac4C to borohydride-based reduction and show this reaction can cause introduction of noncognate base pairs during reverse transcription (RT). Combining borohydride-dependent misincorporation with ac4C's known base-sensitivity provides a unique chemical signature for this modified nucleobase. We show this unique reactivity can be used to quantitatively analyze cellular RNA acetylation, study adapters responsible for ac4C targeting, and probe the timing of RNA acetylation during ribosome biogenesis. Overall, our studies provide a chemical foundation for defining an expanding landscape of cytidine acetyltransferase activity and its impact on biology and disease.

In vivo neutralization of the protagonist role of macrophages during the chronic inflammatory stage of Huntington's disease.

Neurodegenerative diseases, characterised by the progressive and selective neuronal death in the central nervous system, are frequently accompanied by an activated immune system. In Huntington's disease (HD), clinical and animal studies show evidence of immune activity, along with hyper-reactive monocyte/macrophage responses, while application of immunosuppressive regimens have imparted beneficial effects to HD mice. These findings suggest a contributory role of the immune system in HD pathology, with immune-based interventions offering a potential therapeutic strategy. Herein, we show that peripheral and CNS immune system activity increased with disease progression in HD mouse models and defined the phenotype of the immune response. Additionally, the depletion of monocytes and macrophages in vivo, via clodronate liposome treatment, revealed a major contributory role of these innate immune cells to the chronic inflammatory milieu observed during the course of the disease. This suggests that peripheral immunomodulatory strategies targeting monocytes and macrophages could be relevant for HD.

Effects of Polymer Coatings on Electrodeposited Lithium Metal.

The electrodeposition of lithium metal is a key process in next-generation, high energy density storage devices. However, the high reactivity of the lithium metal causes short cycling lifetimes and dendrite growth that can pose a serious safety issue. Recently, a number of approaches have been pursued to stabilize the lithium metal-electrolyte interface, including soft polymeric coatings that have shown the ability to enable high-rate and high-capacity lithium metal cycling, but a clear understanding of how to design and modify these coatings has not yet been established. In this work, we studied the effects of several polymers with systematically varied chemical and mechanical properties as coatings on the lithium metal anode. By examining the early stages of lithium metal deposition, we determine that the morphology of the lithium particles is strongly influenced by the chemistry of the polymer coating. We have identified polymer dielectric constant and surface energy as two key descriptors of the lithium deposit size. Low surface energy polymers were found to promote larger deposits with smaller surface areas. This may be explained by a reduced interaction between the coating and the lithium surface and thus an increase in the interfacial energy. On the other hand, high dielectric constant polymers were found to increase the exchange current and gave larger lithium deposits due to the decreased overpotentials at a fixed current density. We also observed that the thickness of the polymer coating should be optimized for each individual polymer. Furthermore, polymer reactivity was found to strongly influence the Coulombic efficiency. Overall, this work offers new fundamental insights into lithium electrodeposition processes and provides direction for the design of new polymer coatings to better stabilize the lithium metal anode.

An Elastic Autonomous Self-Healing Capacitive Sensor Based on a Dynamic Dual Crosslinked Chemical System.

Adopting self-healing, robust, and stretchable materials is a promising method to enable next-generation wearable electronic devices, touch screens, and soft robotics. Both elasticity and self-healing are important qualities for substrate materials as they comprise the majority of device components. However, most autonomous self-healing materials reported to date have poor elastic properties, i.e., they possess only modest mechanical strength and recoverability. Here, a substrate material designed is reported based on a combination of dynamic metal-coordinated bonds (ß-diketone-europium interaction) and hydrogen bonds together in a multiphase separated network. Importantly, this material is able to undergo self-healing and exhibits excellent elasticity. The polymer network forms a microphase-separated structure and exhibits a high stress at break (≈1.8 MPa) and high fracture strain (≈900%). Additionally, it is observed that the substrate can achieve up to 98% self-healing efficiency after 48 h at 25 °C, without the need of any external stimuli. A stretchable and self-healable dielectric layer is fabricated with a dual-dynamic bonding polymer system and self-healable conductive layers are created using polymer as a matrix for a silver composite. These materials are employed to prepare capacitive sensors to demonstrate a stretchable and self-healable touch pad.

An Aqueous Inorganic Polymer Binder for High Performance Lithium-Sulfur Batteries with Flame-Retardant Properties.

Lithium-sulfur (Li-S) batteries are regarded as promising next-generation high energy density storage devices for both portable electronics and electric vehicles due to their high energy density, low cost, and environmental friendliness. However, there remain some issues yet to be fully addressed with the main challenges stemming from the ionically insulating nature of sulfur and the dissolution of polysulfides in electrolyte with subsequent parasitic reactions leading to low sulfur utilization and poor cycle life. The high flammability of sulfur is another serious safety concern which has hindered its further application. Herein, an aqueous inorganic polymer, ammonium polyphosphate (APP), has been developed as a novel multifunctional binder to address the above issues. The strong binding affinity of the main chain of APP with lithium polysulfides blocks diffusion of polysulfide anions and inhibits their shuttling effect. The coupling of APP with Li ion facilitates ion transfer and promotes the kinetics of the cathode reaction. Moreover, APP can serve as a flame retardant, thus significantly reducing the flammability of the sulfur cathode. In addition, the aqueous characteristic of the binder avoids the use of toxic organic solvents, thus significantly improving safety. As a result, a high rate capacity of 520 mAh g-1 at 4 C and excellent cycling stability of ∼0.038% capacity decay per cycle at 0.5 C for 400 cycles are achieved based on this binder. This work offers a feasible and effective strategy for employing APP as an efficient multifunctional binder toward building next-generation high energy density Li-S batteries.

Quadruple H-Bonding Cross-Linked Supramolecular Polymeric Materials as Substrates for Stretchable, Antitearing, and Self-Healable Thin Film Electrodes.

Herein, we report a de novo chemical design of supramolecular polymer materials (SPMs-1-3) by condensation polymerization, consisting of (i) soft polymeric chains (polytetramethylene glycol and tetraethylene glycol) and (ii) strong and reversible quadruple H-bonding cross-linkers (from 0 to 30 mol %). The former contributes to the formation of the soft domain of the SPMs, and the latter furnishes the SPMs with desirable mechanical properties, thereby producing soft, stretchable, yet tough elastomers. The resulting SPM-2 was observed to be highly stretchable (up to 17 000% strain), tough (fracture energy ∼30 000 J/m2), and self-healing, which are highly desirable properties and are superior to previously reported elastomers and tough hydrogels. Furthermore, a gold, thin film electrode deposited on this SPM substrate retains its conductivity and combines high stretchability (∼400%), fracture/notch insensitivity, self-healing, and good interfacial adhesion with the gold film. Again, these properties are all highly complementary to commonly used polydimethylsiloxane-based thin film metal electrodes. Last, we proceed to demonstrate the practical utility of our fabricated electrode via both in vivo and in vitro measurements of electromyography signals. This fundamental understanding obtained from the investigation of these SPMs will facilitate the progress of intelligent soft materials and flexible electronics.

Tough and Water-Insensitive Self-Healing Elastomer for Robust Electronic Skin.

An electronic (e-) skin is expected to experience significant wear and tear over time. Therefore, self-healing stretchable materials that are simultaneously soft and with high fracture energy, that is high tolerance of damage or small cracks without propagating, are essential requirements for the realization of robust e-skin. However, previously reported elastomers and especially self-healing polymers are mostly viscoelastic and lack high mechanical toughness. Here, a new class of polymeric material crosslinked through rationally designed multistrength hydrogen bonding interactions is reported. The resultant supramolecular network in polymer film realizes exceptional mechanical properties such as notch-insensitive high stretchability (1200%), high toughness of 12 000 J m-2 , and autonomous self-healing even in artificial sweat. The tough self-healing materials enable the wafer-scale fabrication of robust and stretchable self-healing e-skin devices, which will provide new directions for future soft robotics and skin prosthetics.

HDAC8 Substrates Identified by Genetically Encoded Active Site Photocrosslinking.

The histone deacetylase family comprises 18 enzymes that catalyze deacetylation of acetylated lysine residues; however, the specificity and substrate profile of each isozyme remains largely unknown. Due to transient enzyme-substrate interactions, conventional co-immunoprecipitation methods frequently fail to identify enzyme-specific substrates. Additionally, compensatory mechanisms often limit the ability of knockdown or chemical inhibition studies to achieve significant fold changes observed by acetylation proteomics methods. Furthermore, measured alterations do not guarantee a direct link between enzyme and substrate. Here we present a chemical crosslinking strategy that incorporates a photoreactive, non-natural amino acid, p-benzoyl-l-phenylalanine, into various positions of the structurally characterized isozyme histone deacetylase 8 (HDAC8). After covalent capture, co-immunoprecipitation, and mass spectrometric analysis, we identified a subset of HDAC8 substrates from human cell lysates, which were further validated for catalytic turnover. Overall, this chemical crosslinking approach identified novel HDAC8-specific substrates with high catalytic efficiency, thus presenting a general strategy for unbiased deacetylase substrate discovery.