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The Anderson localization effect has been exploited in the design of high-temperature dielectric polymers, resulting in reduced conduction loss and outstanding capacitive energy storage performance over a wide temperature range up to 250 °C.
Traditionally, Fe-SACs are prepared through energy-intense processes, which often lead to the loss of precision in structural features from the starting substrates and impeding rational design. In this work, we have described the synthesis of a unique catechol-containing porous polymer with designed features in the substrates maintained, affording atomically dispersed iron catalyst (Fe-SAC) through treatment of ferrous chloride (FeCl 2 ). An aberration-corrected scanning transmission electron microscope (AC-STEM) and synchrotron X-ray absorption spectroscopy (XAS) were employed to shed light on the local coordination geometry of the atomically dispersed iron catalyst. The resulting Fe-SAC exhibits excellent catalytic performance in reduction of nitroaromatics with highest molar K app among all Fe based catalysts.
Ladder-type structures can impart exceptional stability to polymeric electronic materials. This article introduces a new class of conductive polymers featuring a fully ladder-type backbone. A judicious molecular design strategy enables the synthesis of a low-defect ladder polymer, which can be efficiently oxidized and acid-doped to achieve its conductive state. The structural elucidation of this polymer and the characterization of its open-shell nature are facilitated with the assistance of studies on small molecular models. An autonomous robotic system is used to optimize the conductivity of the polymer thin film, achieving over 7 mS cm −1 . Impressively, this polymer demonstrates unparalleled stability in strong acid and under harsh UV-irradiation, significantly surpassing commercial benchmarks like PEDOT:PSS and polyaniline. Moreover, it displays superior durability across numerous redox cycles as the active material in an electrochromic device and as the pseudocapacitive material in a supercapacitor device. This work provides structural design guidance for durable conductive polymers for long-term device operation.
The polymerized small-molecule acceptors have attracted great attention for application as polymer acceptor in all-polymer solar cells recently. The modification of small molecule acceptor building block and the π-bridge linker is an effective strategy to improve the photovoltaic performance of the polymer acceptors. In this work, we synthesized a new polymer acceptor PG-IT2F which is a modification of the representative polymer acceptor PY-IT by replacing its upper linear alkyl side chains on the small molecule building block with branched alkyl chains and attaching difluorene substituents on its thiophene π-bridge linker. Through this synergistic optimization, PG-IT2F possesses more suitable phase separation, increased charge transportation, better exciton dissociation, lower bimolecular recombination, and longer charge transfer state lifetime than PY-IT in their polymer solar cells with PM6 as polymer donor. Therefore, the devices based on PM6:PG-IT2F demonstrated a high power conversion efficiency of 17.24%, which is one of the highest efficiency reported for the binary all polymer solar cells to date. This work indicates that the synergistic regulation of small molecule acceptor building block and π-bridge linker plays a key role in designing and developing highly efficient polymer acceptors.
Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.
Isolating electronically conducting material from internal short circuits is a promising way to prevent the onset of thermal runaway within lithium-ion cells. Here, a metal-coated polymer current collector, which is designed to disconnect internal short circuits by withdrawing from the heating region, is tested in 18650 cells. In addition to having lower mass and manufacturing costs, cells with metal-coated polymer current collectors demonstrate a reduced risk of thermal runaway during nail penetration. High-speed synchrotron X-ray radiography of 18650 cells during nail-penetration testing, in tandem with pre- and post-mortem X-ray computed tomography, provides insights into the function of the current collectors. The results are compared with those of 18650 cells with standard commercial aluminum and copper current collectors. Cells with aluminum-coated polymer current collectors demonstrated 100% success in thermal runaway prevention during nail penetration, retaining a cell voltage >4.00 V, while standard cells consistently experienced thermal runaway.
Current research on ferroelectric polymers centers predominantly on poly(vinylidene fluoride) (PVDF)–based fluoropolymers because of their superior performance. However, they are considered “forever chemicals” with environmental concerns. Here, we describe a family of rationally designed fluorine-free ferroelectric polymers, featuring a polyoxypropylene main chain and disulfonyl alkyl side chains with a C3 spacer: −SO 2 CH 2 CHRCH 2 SO 2 − (R = −H or −CH 3 ). Both experimental and simulation results demonstrate that strong dipole-dipole interactions between neighboring disulfonyl groups induce ferroelectric ordering in the condensed state, which can be tailored by changing the R group: ferroelectric for R = −H or relaxor ferroelectric for R = −CH 3 . At low electric fields, the relaxor polymer exhibits electroactuation and electrocaloric performance comparable with those of state-of-the-art PVDF-based tetrapolymers.
Plastic recycling rates are still low in the United States (U.S.), with less than 10% of municipal solid waste (MSW) plastic being recycled. Most unrecycled plastics are identified by Resin Identification Codes (RIC) from #3–7, which are commonly destined for landfill or waste-to-energy facilities (WTE). Therefore, the composition and quality of outbound bales containing #3–7 plastics were assessed to understand the potential to increase recycling rates. Three bales were sourced from three different Material Recovery Facilities (MRFs) located in the United States. Each bale was manually sorted and characterized for quality and performance via multiple plastic characterization techniques. Considerable differences in bale composition were observed between MRFs, which correlated with the technology used by each MRF in the sorting process. The differences were substantial in the residual levels of poly(ethylene terephthalate) (PET) and high-density polyethylene (HDPE), which are highly desired for mechanical recycling processes and not expected in #3–7 plastics bales. Traditional recycling processes including washing, extrusion, and injection molding of the sorted material were employed prior to the physical, thermal, and molecular characterization. Despite differences in bale composition by plastic type, some polymer properties were similar across MRFs. Here, this research suggests that landfill-diverted mixed plastic waste can be utilized in the mechanical recycling of currently unrecycled materials, as processes can be designed to work with consistent polymer properties. It also highlights the need to upgrade the sorting systems to prevent waste feedstocks, which can be recycled with current technologies, from contaminating other plastic streams or reach landfills.
Stimuli-responsive polymeric materials have attracted significant attention due to their ability to change properties in response to various external stimuli. Using an electric field as the stimulus is of particular interest as it possesses the potential for seamless integration of materials with electronic systems. While many materials with electric field responsive actuation have an associated mechanical property change, it is beneficial to develop materials that exhibit mechanical property changes without accompanying significant shape deformation. To address this challenge, here we designed a semi-interpenetrating polymer network (semi-IPN) hydrogel system containing both polyelectrolytes and salt ions, which enables electric field induced changes in mechanical properties while minimizing actuation. We first successfully verified the viability of our design by removing salt ions through a diffusion-only method where we witnessed the stiffness increased to 4.5 times the initial value while still being highly deformable. After this, we applied an electric field to transport the salt ions out of the hydrogel, as shown by both Raman spectroscopy and scanning electron microscopy. We were able to show a time-dependent stiffness increase, the maximum of which was 5 times the original stiffness. We quantified ion transport and water-splitting in the hydrogel by both experiments and simulations. Following this, we showed functional system reversibility by reversing the direction of the current to reinject salt ions into the semi-IPN hydrogel and reducing its stiffness to below the initial value. It's worth noting that our simulations enable us to understand the governing mechanisms behind ion generation and salt transport that leads to mechanical property changes. Finally, we were able to fabricate a spatially variable stiffness haptic interface with our hydrogel, with demonstrated reversibility and cyclability. This research can possibly find applications in soft robotics and haptics and also inspire the development of bio-compatible electronics related devices.
Over the past two decades, serial X-ray crystallography has enabled the structure determination of a wide range of proteins. With the advent of X-ray free-electron lasers (XFELs), ever-smaller crystals have yielded high-resolution diffraction and structure determination. A crucial need to continue advancement is the efficient delivery of fragile and micrometre-sized crystals to the X-ray beam intersection. This paper presents an improved design of an all-polymer microfluidic `chip' for room-temperature fixed-target serial crystallography that can be tailored to broadly meet the needs of users at either synchrotron or XFEL light sources. The chips are designed to be customized around different types of crystals and offer users a friendly, quick, convenient, ultra-low-cost and robust sample-delivery platform. Compared with the previous iteration of the chip [Gilbile et al. (2021), Lab Chip , 21 , 4831–4845], the new design eliminates cleanroom fabrication. It has a larger imaging area to volume, while maintaining crystal hydration stability for both in situ crystallization or direct crystal slurry loading. Crystals of two model proteins, lysozyme and thaumatin, were used to validate the effectiveness of the design at both synchrotron (lysozyme and thaumatin) and XFEL (lysozyme only) facilities, yielding complete data sets with resolutions of 1.42, 1.48 and 1.70 Å, respectively. Overall, the improved chip design, ease of fabrication and high modifiability create a powerful, all-around sample-delivery tool that structural biologists can quickly adopt, especially in cases of limited sample volume and small, fragile crystals.
The design of safe and high-performance, nanostructured, block polymer (BP) electrolytes for lithium-ion batteries requires a thorough understanding of the key parameters that govern local structure and dynamics. Yet, the interfaces between microphase separated domains can introduce complexities in this local behavior that can be challenging to quantify. Herein, the local polymer, cation (Li + ), and anion dynamics were described in salt-doped polystyrene block poly(oligo-oxyethylene methyl ether methacrylate) (PS-b-POEM) through a quantitative framework that considered the effects of polymer architecture, segmental mixing, chain stretching, and confinement on polymer mobility and ion transport. This framework was validated through nuclear magnetic resonance (NMR) spectroscopy measurements on solid (dry) polymer electrolyte samples. Notably, a mobility transition temperature (T mobility ) was identified through NMR spectroscopy that captured the local dynamics more accurately than the thermal glass transition temperature. Additionally, the approach quantitatively described the mobility gradient across a domain when segmental mixing effects were combined with chain stretching and confinement information, especially at higher segregation strengths – facilitating the assessment of local ion diffusion and conductivity. As a result, spatially averaged local ion diffusion predictions quantitatively matched NMR-measured ion diffusivities in the BP samples, while spatially summed ionic conductivity predictions across a domain qualitatively captured trends in the measured ionic conductivities.
Abstract In this paper, a difluoro‐monobromo end group is designed and synthesized, which is then used to construct a novel polymer acceptor (named PY2F‐T) yielding high‐performance all‐polymer solar cells with 15.22% efficiency. The fluorination strategy can increase the intramolecular charge transfer and interchain packing of the previous PY‐T based acceptor, and significantly improve photon harvesting and charge mobility of the resulting polymer acceptor. In addition, detailed morphology investigations reveal that the PY2F‐T‐based blend shows smaller domain spacing and higher domain purity, which significantly suppress charge recombination as supported by time‐resolved techniques. These polymer properties enable simultaneously enhanced J SC and FF of the PY2F‐T‐based devices, eventually delivering device efficiencies of over 15%, significantly outperforming that of the devices based on the non‐fluorinated PY‐T polymer (13%). More importantly, the PY2F‐T‐based active layers can be processed under ambient conditions and still achieve a 14.37% efficiency. They can also be processed using non‐halogenated solvent o ‐xylene (no additive) and yield a decent performance of 13.05%. This work demonstrates the success of the fluorination strategy in the design of high‐performance polymer acceptors, which provide guidelines for developing new all‐PSCs with better efficiencies and stabilities for commercial applications.
Molecularly doped conjugated polymers with polar side chains are an emerging class of conducting materials exhibiting enhanced and thermally stable conductivity. In this work, we study the electronic conductivity (σ) and the corresponding thermal stability of two polythiophene derivatives comprising oligoethylene glycol side chains: one having oxygen attached to the thiophene ring (poly(3-(methoxyethoxyethoxy)thiophene) (P3MEET)) and the other having a methylene spacer between the oxygen and the thiophene ring (poly(3-(methoxyethoxyethoxymethyl)thiophene) (P3MEEMT)). Thin films were vapor-doped with fluorinated derivatives of tetracyanoquinodimethane (FnTCNQ, n = 4, 2, 1) to determine the role of dopant strength (electron affinity) in maximum achievable σ. Specifically, when vapor doping with F 4 TCNQ, P3MEET achieved a substantially higher σ of 37.1 ± 10.1 S/cm compared to a σ of 0.82 ± 0.06 S/cm for P3MEEMT. Structural characterization using a combination of X-ray and optical spectroscopy reveals that the higher degree of conformational order of polymer chains in the amorphous domain upon doping with F 4 TCNQ in P3MEET is a major contributing factor for the higher σ of P3MEET. Additionally, vapor-doped P3MEET exhibited superior thermal stability compared to P3MEEMT, highlighting that the presence of polar side chains alone does not ensure higher thermal stability. Molecular dynamics simulations indicate that the dopant–side-chain nonbond energy is lower in the P3MEET:F 4 TCNQ mixture, suggesting more favorable dopant–side-chain interaction, which is a factor in improving the thermal stability of a polymer/dopant pair. Our results reveal that additional factors such as polymer ionization energy and side-chain–dopant interaction should be taken into account for the design of thermally stable, highly conductive polymers.
Solid-state batteries are attractive energy storage systems as a result of their inherent safety, but their development hinges on advanced solid-state electrolytes (SSEs). Most SSEs remain largely confined to single-anion systems (e.g., sulfides, oxides, halides, and polymers). Through mixed-anion design strategy, we develop crystalline Li 3 Ta 3 O 4 Cl 10 (LTOC) and its derivatives with excellent ionic conductivities (up to 13.7 millisiemens per centimeter at 25°C) and electrochemical stability. The LTOC structure features mixed-anion spiral chains, consisting of corner-shared oxygen and terminal chlorine atoms, which induces continuous “tetrahedron-tetrahedron” Li-ion migration pathways with low energy barriers. Additionally, LTOC demonstrates holistic cathode compatibility, enabling solid-state batteries operation at 4.9 volts versus Li/Li + and low temperature, down to −50°C. In conclusion, these findings describe a promising class of superionic conductors for high-performance solid-state batteries.
Abstract The self-assembly of DNA-coated colloids into highly-ordered structures offers great promise for advanced optical materials. However, control of disorder, defects, melting, and crystal growth is hindered by the lack of a microscopic understanding of DNA-mediated colloidal interactions. Here we use total internal reflection microscopy to measure in situ the interaction potential between DNA-coated colloids with nanometer resolution and the macroscopic melting behavior. The range and strength of the interaction are measured and linked to key material design parameters, including DNA sequence, polymer length, grafting density, and complementary fraction. We present a first-principles model that screens and combines existing theories into one coherent framework and quantitatively reproduces our experimental data without fitting parameters over a wide range of DNA ligand designs. Our theory identifies a subtle competition between DNA binding and steric repulsion and accurately predicts adhesion and melting at a molecular level. Combining experimental and theoretical results, our work provides a quantitative and predictive approach for guiding material design with DNA-nanotechnology and can be further extended to a diversity of colloidal and biological systems.
Polymeric nanoparticles (PNPs) are solid particles that contain macromolecular polymers ranging in size from 1-1000 nm. They have a wide variety of structures that are determined by their identity as either natural biopolymers, synthetic polymers or a combination of both. In the design of PNPs, the polymeric system, size, internal structure, additional molecules, and synthetic pathway can be engineered, allowing for a multitude of properties including differing responses to physiological environments and the incorporation of a drug. The easily accessible fine tuning of PNPs allows for a multitude of applications in medicine. PNPs allow for increased pharmacokinetics, efficacy, safety, and targeting strength when utilized as carriers for drugs. Currently there are a wide range of PNPs approved by the Food and Drug Administration for use in clinical settings and many more being investigated in clinical studies. There is also research that is being conducted for the usage of PNPs in controlled drug delivery systems and as carriers through the blood brain barrier to aid in treating neurological diseases.
Metal-organic frameworks (MOFs) are renowned for their tunable structure, porosity, and internal chemistry, with demonstrated applications in molecular separations, storage, and conversion. While they are widely usable, the powdery characteristics of MOF materials can be limiting for large-scale processing and implementation in devices. Incorporating MOF particles into polymer supports affords engineering solutions to overcome these issues, yet the nature of the resulting composites is difficult to assess. Here, in this work, we present spectroscopic and calorimetric methods that we believe help establish a holistic physicochemical picture of the composite structure using a series of Zr MOFs with different pore sizes as a testbed. Power law decays are observed in X-ray scattering profiles in low q-space ranging between 2.4 and 3.3, which we interpret as changes in scattering due to polymer infiltrating MOF particles. This interpretation is supported by solid-state nuclear magnetic resonance spectroscopy and differential scanning calorimetry measurements that identify populations of the MOF-associated polymer. Additionally, positron annihilation lifetime spectroscopy measurements collected on a series of composites with different MOF-polymer ratios show multiple decay constants, each correlated to a different free volume elements. In combination with the spectroscopic, calorimetric, and scattering results, we utilize the trends in decay constants as a function of polymer mass fraction to hypothesize a polymer infiltration mechanism whereby large pores are preferentially filled, followed by small pores and, later still, interstitial spaces between particles. Even with vigorous investigation of polymer, MOF, and interface characteristics, the complex and heterogeneous nature of the composites makes absolute structural assertions difficult. We envision that the approaches demonstrated here will be a useful foundation to assess and ultimately guide the design of future MOF-polymer composites.
Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.