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Colloidal AInSe 2 (A = K, Rb, Cs) Nanocrystals with Tunable Crystal and Band Structures
Wide band gap AInSe 2 (A = K, Rb, Cs) is an important interlayer material for improving the efficiency of Cu(In,Ga)(S,Se) 2 (CIGS) solar cells. Compared to high-vacuum deposition and solid-state synthesis, a less energyintensive method is of interest for its fabrication. Herein, we present the rapid, low-temperature colloidal synthesis of AInSe 2 nanocrystals that opens a pathway for convenient solution processing. The crystal structures and electronic band structures of the nanocrystals were studied, and their particle morphology was found to be dependent on the choice of alkali metal and selenium precursors. Homogeneous solid solution (K,Rb,Cs)InSe 2 nanocrystals were synthesized using a mixture of alkali metal precursors. Their compositions, lattice parameters, and band gaps were easily tuned based on the K:Rb:Cs precursor ratio, providing potential for interface engineering of CIGS nanocrystal-based solar cells.
Can Multiple Ions in an Ionic Liquid Improve the Biomass Pretreatment Efficacy?
we report over the last few decades, efforts to transition the global production of fuels and chemicals toward renewable carbon feedstocks have accelerated. A large portion of these efforts have focused on valorization of one of the most abundant renewable carbon sources, lignocellulose. Pretreatment of lignocellulose is the first critical step in this process. In this study, novel ionic liquid (IL) systems consisting of multiple ions known to be effective at biomass pretreatment were tested on woody and grassy biomass. Molecular simulations and experimental results established the synergistic advantages of combining specific individual components in these systems. For pine (woody) biomass, pretreatment with the combination of imidazolium, cholinium, acetate, and lysinate ions achieved 80% glucose and 70% xylose yields at high biomass loading. For sorghum biomass, an IL system comprising cholinium, lysinate, and palmitate ions not only enabled a 98% glucose yield but was also found to be biocompatible in a one-pot configuration, producing the biofuel precursor bisabolene using an engineered strain of the yeast Rhodosporidium toruloides.
Machine learning approaches for intentional materials engineering
In this article, the development of nanoporous metals and metallic composites through dealloying processes presents significant opportunities in materials engineering. However, designing multicomponent precursor alloys and establishing corresponding processing methods that yield predictable compositions and nanostructures remain a complex challenge. This article explores how machine learning (ML)-augmented computational and experimental methodologies can tackle these challenges by predicting precursor alloy compositions, final nanoporous structures, and mechanical properties, while integrating ML-enabled autonomous experimentation for material design and quantification. We highlight recent advancements in applying ML to nanostructured materials design via dealloying and discuss how techniques from other nanomaterial designs can be adapted for improved control over morphological and compositional outcomes in nanoporous and nanocomposite materials. Furthermore, we explore the role of ML in autonomous synchrotron x-ray experimentation, enabling real-time feedback between modeling and experimental setups. ML-driven approaches to microstructure characterization and mechanical property prediction are also examined, with a focus on modeling and advanced imaging techniques such as three-dimensional nanotomography. Finally, this article outlines future directions for ML-enhanced materials science, emphasizing the exploration of high-dimensional parameter spaces and the incorporation of materials kinetics into processing and property evaluation, ultimately advancing the design of nanoporous structures and materials science.
Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data
Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.
Anomalous Self-Optimizing Microporous Graphene-Based Lithium-ion Battery Anode from Laser Activation
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Autonomous stabilization with programmable stabilized state
Reservoir engineering is a powerful technique to autonomously stabilize a quantum state. Traditional schemes involving multi-body states typically function for discrete entangled states. In this work, we enhance the stabilization capability to a continuous manifold of states with programmable stabilized state selection using multiple continuous tuning parameters. We experimentally achieve 84.6% and 82.5% stabilization fidelity for the odd and even-parity Bell states as two special points in the manifold. We also perform fast dissipative switching between these opposite parity states within 1.8 μs and 0.9 μs by sequentially applying different stabilization drives. Our result is a precursor for new reservoir engineering-based error correction schemes.
Verazine biosynthesis from simple sugars in engineered Saccharomyces cerevisiae
Steroidal alkaloids are FDA-approved drugs (e.g., Zytiga) and promising drug candidates/leads (e.g., cyclopamine); yet many of the ≥697 known steroidal alkaloid natural products remain underutilized as drugs because it can be challenging to scale their biosynthesis in their producing organisms. Cyclopamine is a steroidal alkaloid produced by corn lily (Veratrum spp.) plants, and it is an inhibitor of the Hedgehog (Hh) signaling pathway. Therefore, cyclopamine is an important drug candidate/lead to treat human diseases that are associated with dysregulated Hh signaling, such as basal cell carcinoma and acute myeloid leukemia. Cyclopamine and its semi-synthetic derivatives have been studied in (pre)clinical trials as Hh inhibitor-based drugs. However, challenges in scaling the production of cyclopamine have slowed efforts to improve its efficacy and safety profile through (bio)synthetic derivatization, often limiting drug development to synthetic analogs of cyclopamine such as the FDA-approved drugs Odomzo, Daurismo, and Erivedge. If a platform for the scalable and sustainable production of cyclopamine were established, then its (bio)synthetic derivatization, clinical development, and, ultimately, widespread distribution could be accelerated. Ongoing efforts to achieve this goal include the biosynthesis of cyclopamine in Veratrum plant cell culture and the semi-/total chemical synthesis of cyclopamine. Herein, this work advances efforts towards a promising future approach: the biosynthesis of cyclopamine in engineered microorganisms. We completed the heterologous microbial production of verazine (biosynthetic precursor to cyclopamine) from simple sugars (i.e., glucose and galactose) in engineered Saccharomyces cerevisiae (S. cerevisiae) through the inducible upregulation of the native yeast mevalonate and lanosterol biosynthetic pathways, diversion of biosynthetic flux from ergosterol (i.e., native sterol in S. cerevisiae) to cholesterol (i.e., biosynthetic precursor to verazine), and expression of a refactored five-step verazine biosynthetic pathway. The engineered S. cerevisiae strain that produced verazine contains eight heterologous enzymes sourced from seven different species. Importantly, S. cerevisiae-produced verazine was indistinguishable via liquid chromatography-mass spectrometry from both a commercial standard (Veratrum spp. plant-produced) and Nicotiana benthamiana-produced verazine. To the best of our knowledge, this is the first report describing the heterologous production of a steroidal alkaloid in an engineered yeast. Verazine production was ultimately increased through design-build-test-learn cycles to a final titer of 83 ± 3 μg/L (4.1 ± 0.1 μg/g DCW). Finally, this research lays the groundwork for future microbial biosynthesis of cyclopamine, (bio)synthetic derivatives of cyclopamine, and other steroidal alkaloid natural products.
Conjugation-based genome engineering enables rapid prototyping and bioproduction in non-model bacteria
Abstract Non-model bacteria offer unique metabolic capabilities for sustainable bioproduction, yet their limited genetic accessibility hinders systematic strain development. Here we present conjugation-based serine recombinase-assisted genome engineering (cSAGE), a broad-host-range platform that enables predictable, iterative genomic integration in transformation-resistant bacteria. cSAGE combines conjugative DNA delivery, standardized low-copy vectors, orthogonal recombinases, and modular genetic parts to support rapid pathway assembly and cross-host benchmarking. Using purple nonsulfur bacteria as a testbed, we integrate promoter engineering, multi-payload genome modification, and genome-scale metabolic modeling to empirically evaluate host-dependent pathway performance. Applying this workflow, we identify strain-specific differences in photosynthetic conversion of lignin-derived p -coumarate to the thermoplastic precursor p -vinylphenol. By enabling genome engineering and functional comparison across diverse bacteria using a single plasmid system, cSAGE provides a general framework for non-model strain prototyping and biotransformation discovery.
Lightweight Materials - Carbon Fiber and Polymer Composites, Integrated Computational Materials Engineering (ICME) Predictive Tools Development for Low-Cost Carbon Fiber for Lightweight Vehicles (University of Virginia) (Final Report)
This project aimed to develop low-cost alternative precursors and processing techniques through the implementation of an integrated computational materials engineering (ICME) framework to evaluate precursor conversion kinetics. Once established, this framework was then used to down-select precursors for laboratory- and pilot-scale production to validate resulting carbon fiber (CF) material properties and process cost-savings. The two most promising approaches to reduce the cost of CFs were to (1) use new low-cost precursors and (2) reduce the energy requirements of CF processing. These approaches were investigated over the course of three phases of work, spanning 3.5 years. This report describes the overall project objectives, approach, and the key accomplishments in each phase.
Automated Power System Fault Prediction and Precursor Discovery Using Multi-Modal Data
Not Available
Discovery of the Azaserine Biosynthetic Pathway Uncovers a Biological Route for α‐Diazoester Production
Abstract Azaserine is a bacterial metabolite containing a biologically unusual and synthetically enabling α‐diazoester functional group. Herein, we report the discovery of the azaserine ( aza ) biosynthetic gene cluster from Glycomyces harbinensis . Discovery of related gene clusters reveals previously unappreciated azaserine producers, and heterologous expression of the aza gene cluster confirms its role in azaserine assembly. Notably, this gene cluster encodes homologues of hydrazonoacetic acid (HYAA)‐producing enzymes, implicating HYAA in α‐diazoester biosynthesis. Isotope feeding and biochemical experiments support this hypothesis. These discoveries indicate that a 2‐electron oxidation of a hydrazonoacetyl intermediate is required for α‐diazoester formation, constituting a distinct logic for diazo biosynthesis. Uncovering this biological route for α‐diazoester synthesis now enables the production of a highly versatile carbene precursor in cells, facilitating approaches for engineering complete carbene‐mediated biosynthetic transformations in vivo.
Discovery of the Azaserine Biosynthetic Pathway Uncovers a Biological Route for α‐Diazoester Production
Abstract Azaserine is a bacterial metabolite containing a biologically unusual and synthetically enabling α‐diazoester functional group. Herein, we report the discovery of the azaserine ( aza ) biosynthetic gene cluster from Glycomyces harbinensis . Discovery of related gene clusters reveals previously unappreciated azaserine producers, and heterologous expression of the aza gene cluster confirms its role in azaserine assembly. Notably, this gene cluster encodes homologues of hydrazonoacetic acid (HYAA)‐producing enzymes, implicating HYAA in α‐diazoester biosynthesis. Isotope feeding and biochemical experiments support this hypothesis. These discoveries indicate that a 2‐electron oxidation of a hydrazonoacetyl intermediate is required for α‐diazoester formation, constituting a distinct logic for diazo biosynthesis. Uncovering this biological route for α‐diazoester synthesis now enables the production of a highly versatile carbene precursor in cells, facilitating approaches for engineering complete carbene‐mediated biosynthetic transformations in vivo.
Surface Engineering Strategy to Synthesize Bicomponent Carbons for Rechargeable Zinc-Air Batteries
Atomic Fe-N x moieties and nanosized FeCo species anchored on carbons have each been demonstrated to be among the most effective active components for oxygen reduction and evolution reactions (ORR/OER), respectively in rechargeable zinc -air batteries (ZABs). However, incorporating both of these components in a single catalyst presents a great challenge due to the trade-off in formation between them during hightemperature preparation. Herein, we integrate them into a bicomponent carbon through a surface engineering strategy. In this process, K 3 [Fe(CN) 6 ] is engineered on the surface of a precursor mixture consisting of polyaniline-coated graphene oxide and ZIF-67. This is followed by pyrolysis to produce the bicomponent carbon catalyst of FeCo nanoparticles modified carbon polyhedron (for accelerating the OER), supported on atomically dispersed Fe -N -doped carbon nanosheet (for boosting the ORR). The catalyst exhibits a small potential gap of 0.69 V for OER/ORR. In situ Raman spectroscopy demonstrates that spinel FeCo oxides may be responsible for OER. The use of this catalyst in ZABs achieves high power densities of 225 mW cm -2 in aqueous electrolyte and 164 mW cm -2 in solid-state electrolyte. Additionally, a small and stable voltage gap of 0.712 V at 10 mA cm -2 is maintained after 1035 discharge -charge cycles demonstrating the great application potential in energy devices.
Effect of tension during sulfonation stabilization for UHMWPE-derived carbon fibers
Polyethylene is a promising low-cost alternative precursor material for carbon fiber production, but it has yet to show mechanical properties near or surpassing polyacrylonitrile-derived carbon fibers. The high molecular weight and order of ultra-high molecular weight polyethylene (UHMWPE) may offer a pathway to realizing this promise by enabling long-range graphitic structure formation and superior mechanical properties. The tension applied during the precursor stabilization process is crucial to maintaining the shape of the fibers during the conversion process, but no published study has yet probed the relationship between sulfonation tension and carbon fiber microstructure and mechanical properties. In this work, a logarithmic sweep of tensile stress was applied to UHMWPE fibers during the stabilization process followed by carbonization. Increasing tension significantly reduced fiber shrinkage, resulted in straighter fibers with less severe kink bands, and greatly improved the mechanical properties of the fibers. Raman spectroscopy and X-ray diffraction revealed that in all cases the carbon fibers were largely amorphous, but increasing tension resulted in increased size and alignment of the turbostratic crystallites with the fiber axis. Large voids were present in the sample fibers, so the Griffith-Irwin relation was employed to predict the potential ultimate tensile strength of the fibers with voids reduced to sizes comparable to commercially produced fibers. Furthermore, this work demonstrates the importance of tension applied during the stabilization of polyethylene fibers for carbon fiber production and establishes a framework for achieving high mechanical properties from these precursors.
Complete biosynthesis of QS-21 in engineered yeast
QS-21 is a potent vaccine adjuvant and remains the only saponin-based adjuvant that has been clinically approved for use in humans. However, owing to the complex structure of QS-21, its availability is limited. Today, the supply depends on laborious extraction from the Chilean soapbark tree or on low-yielding total chemical synthesis. Here we demonstrate the complete biosynthesis of QS-21 and its precursors, as well as structural derivatives, in engineered yeast strains. The successful biosynthesis in yeast requires fine-tuning of the host’s native pathway fluxes, as well as the functional and balanced expression of 38 heterologous enzymes. The required biosynthetic pathway spans seven enzyme families—a terpene synthase, P450s, nucleotide sugar synthases, glycosyltransferases, a coenzyme A ligase, acyl transferases and polyketide synthases—from six organisms, and mimics in yeast the subcellular compartmentalization of plants from the endoplasmic reticulum membrane to the cytosol. Finally, by taking advantage of the promiscuity of certain pathway enzymes, we produced structural analogues of QS-21 using this biosynthetic platform. This microbial production scheme will allow for the future establishment of a structure–activity relationship, and will thus enable the rational design of potent vaccine adjuvants.
On the Sintering Behavior of Nb2O5 and Ta2O5 Mixed Oxide Powders
A mixed oxide system consisting of Nb2O5 and Ta2O5, was subjected to annealing in air/hydrogen up to 950 °C for 1–4 h to study its sintering behavior. The thermogravimetric–differential scanning calorimetry (TGA–DSC) thermograms indicated the formation of multiple endothermic peaks at temperatures higher than 925 °C. Subsequently, a 30% Ta2O5 and 70% Nb2O5 (mol%) pellet resulted in good sintering behavior at both 900 and 950 °C. The scanning electron microscope (SEM) images corroborated these observations with necking and particle coarsening. The sintered pellets contained a 20.4 and 20.8% mixed oxide (Nb4Ta2O15) phase, along with Ta2O5 and Nb2O5, at both 900 and 950 °C, indicating the possibility of the formation of a solid solution phase. In situ high-temperature X-ray diffraction (XRD) scans also confirmed the formation of the ternary oxide phase at 6 and 19.8% at 890 and 950 °C, respectively. The Hume–Rothery rules could explain the good sintering behavior of the Ta2O5 and Nb2O5 mixed oxides. An oxide composition of 30% Ta2O5 and 70% Nb2O5 (mol%) and a sintering temperature of 950 °C appeared adequate for fabricating well-sintered oxide precursors for subsequent electrochemical polarization studies in fused salts.