Engineering topics

Jayapurna, Ivan

Publications and source records attributed to Jayapurna, Ivan.

7 records

DOE OSTI2024

Mapping Composition Evolution through Synthesis, Purification, and Depolymerization of Random Heteropolymers

Random heteropolymers (RHPs) consisting of three or more comonomers have been routinely used to synthesize functional materials. While increasing the monomer variety diversifies the side-chain chemistry, this substantially expands the sequence space and leads to ensemble-level sequence heterogeneity. Most studies have relied on monomer composition and simulated sequences to design RHPs, but the questions remain unanswered regarding heterogeneities within each RHP ensemble and how closely these simulated sequences reflect the experimental outcomes. Here, we quantitatively mapped out the evolution of monomer compositions in four-monomer-based RHPs throughout a design-synthesis-purification-depolymerization process. By adopting a Jaacks method, we first determined 12 reactivity ratios directly from quaternary methacrylate RAFT copolymerization experiments to account for the influences of competitive monomer addition and the reversible activation/deactivation equilibria. The reliability of in silico analysis was affirmed by a quantitative agreement (<4% difference) between the simulated RHP compositions and the experimental results. Furthermore, we mapped out the conformation distribution within each ensemble in different solvents as a function of monomer chemistry, composition, and segmental characteristics via high-throughput computation based on self-consistent field theory (SCFT). These comprehensive studies confirmed monomer composition as a viable design parameter to engineer RHP-based functional materials as long as the reactivity ratios are accurately determined and the livingness of RHP synthesis is ensured.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Population-based heteropolymer design to mimic protein mixtures

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo–Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Conductive Ink with Circular Life Cycle for Printed Electronics

Electronic waste carries energetic costs and an environmental burden rivaling that of plastic waste due to the rarity and toxicity of the heavy-metal components. Recyclable conductive composites are introduced for printed circuits formulated with polycaprolactone (PCL), conductive fillers, and enzyme/protectant nanoclusters. Circuits can be printed with flexibility (breaking strain ≈80%) and conductivity (≈2.1 × 10 4 S m -1 ). These composites are degraded at the end of life by immersion in warm water with programmable latency. Approximately 94% of the functional fillers can be recycled and reused with similar device performance. The printed circuits remain functional and degradable after shelf storage for at least 7 months at room temperature and one month of continuous operation under electrical voltage. Here, the present studies provide composite design toward recyclable and easily disposable printed electronics for applications such as wearable electronics, biosensors, and soft robotics.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Synergistic Enzyme Mixtures to Realize Near-Complete Depolymerization in Biodegradable Polymer/Additive Blends

Embedding catalysts inside of plastics affords accelerated chemical modification with programmable latency and pathways. Nanoscopically embedded enzymes can lead to near-complete degradation of polyesters via chain-end mediated processive depolymerization. The overall degradation rate and pathways have a strong dependence on the morphology of semicrystalline polyesters. Yet, most studies to date focus on pristine polymers instead of mixtures that contain additives and other components despite their nearly universal use in plastic production. Here, for this study, additives are introduced to purposely change the morphology of polycaprolactone (PCL) by increasing the bending and twisting of crystalline lamellae. These morphological changes immobilize chain ends preferentially at the crystalline/amorphous interfaces and limit chain-end accessibility by the embedded processive enzyme. This chain-end redistribution reduces the polymer-to-monomer conversion from >95% to less than 50%, causing formation of highly crystalline plastic pieces, including microplastics. By synergizing both random chain scission and processive depolymerization, it is feasible to navigate morphological changes in polymer/additive blends and to achieve near-complete depolymerization. The random scission enzymes in the amorphous domains create new chain ends that are subsequently bound and depolymerized by processive enzymes. Present studies further highlight the importance to consider how the host polymer's morphologies affect the reactions catalyzed by embedded catalytic species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Near-complete depolymerization of polyesters with nano-dispersed enzymes

Successfully interfacing enzymes and biomachinery with polymers affords on-demand modification and/or programmable degradation during the manufacture, utilization and disposal of plastics, but requires controlled biocatalysis in solid matrices with macromolecular substrates. Embedding enzyme microparticles speeds up polyester degradation, but compromises host properties and unintentionally accelerates the formation of microplastics with partial polymer degradation. Here we show that by nanoscopically dispersing enzymes with deep active sites, semi-crystalline polyesters can be degraded primarily via chain-end-mediated processive depolymerization with programmable latency and material integrity, akin to polyadenylation-induced messenger RNA decay. It is also feasible to achieve processivity with enzymes that have surface-exposed active sites by engineering enzyme-protectant-polymer complexes. Poly(caprolactone) and poly(lactic acid) containing less than 2 weight per cent enzymes are depolymerized in days, with up to 98 per cent polymer-to-small-molecule conversion in standard soil composts and household tap water, completely eliminating current needs to separate and landfill their products in compost facilities. Furthermore, oxidases embedded in polyolefins retain their activities. However, hydrocarbon polymers do not closely associate with enzymes, as their polyester counterparts do, and the reactive radicals that are generated cannot chemically modify the macromolecular host. This study provides molecular guidance towards enzyme-polymer pairing and the selection of enzyme protectants to modulate substrate selectivity and optimize biocatalytic pathways. Furthermore, the results also highlight the need for in-depth research in solid-state enzymology, especially in multi-step enzymatic cascades, to tackle chemically dormant substrates without creating secondary environmental contamination and/or biosafety concerns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Nanocomposites Based on Coil-Comb Diblock Copolymers

The polymer chain architecture is an important factor determining the phase behavior of nanoparticle (NP) assembly in polymer matrices. Block copolymers (BCPs) containing a random copolymer (RCP) block present a convenient variation on traditional BCPs to tune the interaction parameters between the polymer blocks and the nanofillers as well as to evaluate the effect of the chain architecture on the NP arrangements within BCP microdomains. Here, we synthesized BCPs with a coil polystyrene (PS) block and a comb RCP block through reversible addition-fragmentation chain transfer polymerization. The RCP block consists of methyl- and lauryl acrylates, the latter of which confers a long-chain alkyl moiety to favorably interact with alkyl-passivated NPs. BCPs showing lamellar, cylindrical, and mixed morphologies were obtained by varying the volume fractions of the RCP block (f RCP ). In comparison to coil-coil BCP, the coil-comb BCPs show highly asymmetric phase behavior with respect to fRCP, where lamellar morphologies were observed at fRCP from 0.31 to 0.51. NPs in the size of 4-5 nm were successfully incorporated in the RCP block of the BCPs with periodicities of 30-60 nm. An order-to-order phase transition from lamellae to PS cylinders was observed after the addition of only 1-2 vol % 5 nm NPs into the BCP with a periodicity of 25 nm and f RCP of 0.51. Self-consistent field theory-density functional theory simulations qualitatively described the observed morphologies and phase transitions in the nanocomposites. Here, the current study presents a platform to fabricate nanocomposites with NP assemblies in coil-comb BCPs that contain a random copolymer block and provides insight into how polymer chain architectures can affect the phase behavior of BCPs and nanocomposites.

36 MATERIALS SCIENCE↗