23 Search Results

Lignin-derived aromatic carboxylic acids can be produced from oxidative catalytic processes and are promising building blocks for performance-advantaged bioproducts that leverage their inherent heteroatom functionalities. Here, we synthesize 2-methoxyterephthalate and 2,6-dimethoxyterephthalate derivatives by electrochemical carboxylation of guaiacyl- and syringyl-derived lignin monomers obtained from the oxidative deconstruction of lignin. These methoxylated terephthalates are evaluated as comonomers in poly(ethylene terephthalate) (PET) and as plasticizers that could replace petrochemically-derived isophthalate and phthalate, respectively. Specifically, we copolymerize 2-methoxy- and 2,6-dimethoxyterephthalate with dimethyl terephthalate to form several PET copolymers, both of which enable the properties of PET to be tuned, with an incorporation beyond 25%more » producing amorphous polyesters. At 10 mol % loading in the copolymers, we demonstrate that the bioderived comonomers exhibit comparable behavior to isophthalic acid, a commonly used comonomer in PET, by lowering the crystallinity and melting temperature. Moreover, methoxyterephthalate esters (2-ethylhexyl and butyl) are compared to phthalate and terephthalate ester counterparts used as poly(vinyl chloride) (PVC) plasticizers. The bioderived plasticizers are comparable to the petroleum-derived incumbents in reducing the glass transition temperature and increasing the thermal stability of PVC. Furthermore, the dimethoxyterephthalic esters are expected to have an extended lifetime in the polymer matrix due to their lower volatility and lower diffusion coefficients calculated by molecular dynamic simulations. These results demonstrate that the isophthalate and phthalate components in polyesters and plasticizers, respectively, could be substituted with biobased methoxyterephthalate derivatives.« less

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers:more » knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.« less

As weather-dependent renewable generation increases its share in the generation mix of most electric energy systems, a stochastic unit commitment becomes the natural day-ahead scheduling tool. However, such a tool is generally computationally intractable if a detailed uncertainty description is considered. Taking this into account, we proposed a learning method to make the stochastic unit commitment problem tractable. Here, recent advances in statistical learning and machine learning to address optimization problems can be advantageously applied to the rather intractable stochastic unit commitment problem. Considering these advances, we explore simple learning techniques to drastically reduce the size of a stochastic unitmore » commitment problem without significantly altering its optimal solution. The considered stochastic unit commitment problem is formulated as a two-stage stochastic programming problem. The first stage represents commitment decisions, while the second one represents the operation conditions under different scenarios. Taking into account historical solved instances (or proxies for them), we reduce the size (measured by numbers of constraints and variables) of the stochastic unit commitment problem by (i) fixing unchanged binary variables and by (ii) eliminating inactive inequality constraints. Our numerical results show that the reduced problem generally requires significantly less time to solve while obtaining high-quality solutions, which are very close to or indistinguishable from the one obtained by solving the original problem. We use an Illinois 200-bus system to illustrate and characterize the performance of the proposed problem-reduction method.« less

Photolysis reaction pathways of [Au(III)Cl₄]^- in aqueous solution have been investigated by time-resolved X-ray absorption spectroscopy. Ultraviolet excitation directly breaks the Au-Cl bond in [Au(III)Cl₄]^- to form [Au(II)Cl₃]^- that becomes highly reactive within 79 ps. Disproportionation of [Au(II)Cl₃]^- generates [Au(I)Cl₂]^-, which is stable for ≤ 10 mu s. In contrast, intense near-infrared lasers photolyze water to generate hydrated electrons, which then reduce [Au(III)Cl₄]^- to [Au(II)Cl₃]^- at 5 ns. Hydrated electrons further induce a chain reaction from [Au(II)Cl₃]^- to [Au(0)Cl]^- by successively removing one Cl^-. The zero-valency Au anions quickly polymerize and condense to form Au nanoparticles, which become the dominatingmore » product after 400 s. Here our results reveal that the condensation of zero-valency Au starts with dimerization of gold clusters coordinated with chloride ions rather than direct condensation of pristine Au atoms.« less

Abstract Electrochemical CO ₂ reduction (CO ₂ R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO ₂ R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application ofmore » data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.« less

Abstract Nickel (Ni)‐based superalloys for high‐temperature applications are often designed to form a continuous and slow‐growing oxide scale by adding Al and Cr and other beneficial elements. In the present work, the critical Al concentration in Ni–Al alloys needed to establish an α‐Al ₂ O ₃ scale in contrast to internal oxide formation is predicted as a function of temperature by means of the CALPHAD approach coupled with models in the literature, which account for the thermodynamics and kinetics of oxidation. The present thermodynamic remodeling of the Ni–O system results in a better agreement with experimental data of oxygen solubilitymore » in Ni at high temperatures. The oxygen solubility is combined with kinetic parameters to determine oxygen permeability in Ni, and the critical Al concentration needed to establish an α‐Al ₂ O ₃ scale at a given exposure temperature. Good agreement is found with available experimental data for both oxygen permeability and critical Al concentration, indicating the capacity of the CALPHAD approach to tailor oxidation resistance for materials of interest using thermodynamic and kinetic knowledge.« less

It is very attractive yet underexplored to synthesize heterocyclic moieties pertaining to biologically active molecules from biomass-based starting compounds. Herein, we report an electrocatalytic Achmatowicz reaction for the synthesis of hydropyranones from furfuryl alcohols, which can be readily produced from biomass-derived and industrially available furfural. Taking advantage of photo-induced polymerization of a bipyridyl ligand, we demonstrate the facile preparation of a heterogenized nickel electrocatalyst, which effectively drives the Achmatowicz reaction electrochemically. A suite of characterization techniques and density functional theory computations were performed to aid the understanding of the reaction mechanism. It is rationalized that the unsaturated coordination sphere ofmore » nickel sites in our electrocatalyst plays an important role at low applied potential, not only allowing the intimate interaction between the nickel center and furfuryl alcohol but also enabling the transfer of hydroxide from nickel to the bound furfuryl alcohol.« less