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Results for “programmable synthesis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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61 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fundamentals of hydrogen storage in nanoporous materials

Abstract Physisorption of hydrogen in nanoporous materials offers an efficient and competitive alternative for hydrogen storage. At low temperatures (e.g. 77 K) and moderate pressures (below 100 bar) molecular H 2 adsorbs reversibly, with very fast kinetics, at high density on the inner surfaces of materials such as zeolites, activated carbons and metal–organic frameworks (MOFs). This review, by experts of Task 40 ‘Energy Storage and Conversion based on Hydrogen’ of the Hydrogen Technology Collaboration Programme of the International Energy Agency, covers the fundamentals of H 2 adsorption in nanoporous materials and assessment of their storage performance. The discussion includes recent work on H 2 adsorption at both low temperature and high pressure, new findings on the assessment of the hydrogen storage performance of materials, the correlation of volumetric and gravimetric H 2 storage capacities, usable capacity, and optimum operating temperature. The application of neutron scattering as an ideal tool for characterising H 2 adsorption is summarised and state-of-the-art computational methods, such as machine learning, are considered for the discovery of new MOFs for H 2 storage applications, as well as the modelling of flexible porous networks for optimised H 2 delivery. The discussion focuses moreover on additional important issues, such as sustainable materials synthesis and improved reproducibility of experimental H 2 adsorption isotherm data by interlaboratory exercises and reference materials.

08 HYDROGEN↗
DOE OSTI2021

A Reconfigurable Neural Network ASIC for Detector Front-End Data Compression at the HL-LHC

Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported from the detector to off-detector logic where trigger decisions are made. We demonstrate that a neural network (NN) autoencoder model can be implemented in a radiation-tolerant application-specific integrated circuit (ASIC) to perform lossy data compression alleviating the data transmission problem while preserving critical information of the detector energy profile. For our application, we consider the high-granularity calorimeter from the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider. The advantage of the machine learning approach is in the flexibility and configurability of the algorithm. By changing the NN weights, a unique data compression algorithm can be deployed for each sensor in different detector regions and changing detector or collider conditions. To meet area, performance, and power constraints, we perform quantization-aware training to create an optimized NN hardware implementation. The design is achieved through the use of high-level synthesis tools and the hls4ml framework and was processed through synthesis and physical layout flows based on a low-power (LP)-CMOS 65-nm technology node. The flow anticipates 200 Mrad of ionizing radiation to select gates and reports a total area of 3.6 mm 2 and consumes 95 mW of power. The simulated energy consumption per inference is 2.4 nJ. Furthermore, this is the first radiation-tolerant on-detector ASIC implementation of an NN that has been designed for particle physics applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Circularity in Sequence-Controlled Copolyamides Enabled by Regioselective Enzymatic Hydrolysis

Sequence-controlled polymers enable precise control over macromolecular structures and function, but both their synthesis and end-of-life management remain fundamental challenges. Achieving high sequence fidelity is synthetically demanding, and conventional depolymerization methods lack regioselectivity, leading to irreversible loss of encoded molecular information and limiting polymer circularity. Enzymatic catalysis offers a potential solution by combining substrate specificity with selective bond cleavage. Here, we report the synthesis, characterization, and regioselective enzymatic depolymerization of poly- (X,AMA), a sequence-controlled copolyamide composed of alternating hexamethylenediamine−adipic acid (MA) and pxylylenediamine− adipic acid (XA) repeat units. Poly(X,AMA) was synthesized via solid-state polycondensation (SSP) of sequence-defined oligomers, enabling precise control over repeat-unit order. Polymer microstructure and sequence fidelity were confirmed by 13 C NMR spectroscopy and MALDI−TOF mass spectrometry. Comparison with a statistical copolymer analogue and Nylon-66 demonstrated pronounced differences in crystallinity, morphology, and thermal behavior arising from sequence control. Screening of 96 Nylon hydrolase homologues against poly(X,AMA) revealed strongly enzyme-dependent depolymerization profiles. While tetrad formation was generally favored, enzymes displayed pronounced sequence selectivity, preferentially releasing distinct sequence-defined tetrads XAMA or MAXA. SSP of sequence-defined tetrad MAXA produced a copolyamide with near identical monomer ordering as poly(X,AMA). Computational modeling of enzyme−substrate complexes identified structural features consistent with the observed regioselectivity. Together, these results establish selective enzymatic depolymerization as a viable strategy for the circular recycling of sequence-controlled polymers and provide a foundation for the rational engineering of enzymes for programmable polymer deconstruction.

Amides↗
DOE OSTI2026

Tuning Anisotropic Optical Properties of Inorganic and Hybrid Organic–Inorganic MXenes via Topochemical Surface Modification

Surface groups are central to the properties of MXenes, yet their role in optical anisotropy remains largely unexplored. Here, we use a topochemical route to synthesize single crystals of stacked Ti 3 C 2 Cl 2 and hybrid organic–inorganic MXenes (h-MXenes) with lateral sizes of 38–75 μm, rotational registry, and tunable interlayer spacing. Solid-state NMR spectroscopy shows that topochemical substitution generates mixed amido, imido, and hydride surface motifs, which modify the electronic structure of the Ti 3 C 2 inorganic core. Imaging spectroscopic ellipsometry with micron-scale spatial resolution enables reconstruction of the complex dielectric tensor of individual multilayer crystals. Ti 3 C 2 Cl 2 exhibits a type-II hyperbolicity above 930 nm, whereas h-MXenes do not display hyperbolicity within the measured 300–1700 nm window, instead showing reduced in-plane conductivity, suppressed out-of-plane light absorption, and a chain-length-dependent blue shift of a near-infrared absorption feature. These results demonstrate topochemical surface modification as a direct handle for engineering MXenes as surface-programmable optical media.

Hybrid materials↗
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 OSTI2019

Multivalent Cation-Induced Actuation of DNA-Mediated Colloidal Superlattices

Nanoparticles functionalized with DNA can assemble into ordered superlattices with defined crystal habits through programmable DNA “bonds”. Here, we examine the interactions of multivalent cations with these DNA bonds as a chemical approach for actuating colloidal superlattices. Multivalent cations alter DNA structure on the molecular scale, enabling the DNA “bond length” to be reversibly altered between 17 and 3 nm, ultimately leading to changes in the overall dimensions of the micrometer-sized superlattice. The identity, charge, and concentration of the cations each control the extent of actuation, with Ni2+ capable of inducing a remarkable >65% reversible change in crystal volume. In addition, these cations can increase “bond strength”, as evidenced by superlattice thermal stability enhancements of >60 °C relative to systems without multivalent cations. Molecular dynamics simulations provide insight into the conformational changes in DNA structure as the bond length approaches 3 nm and show that cations that screen the negative charge on the DNA backbone more effectively cause greater crystal contraction. Finally, taken together, the use of multivalent cations represents a powerful strategy to alter superlattice structure and stability, which can impact diverse applications through dynamic control of material properties, including the optical, magnetic, and mechanical properties.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Selective reduction in epitaxial SrFe 0.5 Co 0.5 O 2.5 and its reversibility

Oxygen-vacancy engineering in transition metal oxides enables programmable functionalities by modulating the valence states and local coordination of constituents. Here, we report the selective reduction of cobalt ions in epitaxial SrFe 0.5 Co 0.5 O 2.5 thin films under reducing gas environments, while iron ions remain unchanged. X-ray absorption spectroscopy reveals an absorption edge shift of 1.65 eV in the Co L-edge upon reduction, and multiplet simulations estimate a decrease in the average Co valence from Co 2.91+ to Co 2.00+ . This site- and element-specific reduction leads to the formation of a structurally distinct oxygen-deficient phase stabilized by oxygen vacancies at tetrahedral sites, as confirmed by density functional theory. Optical spectroscopy reveals an increase in the bandgap from 2.47 eV to 3.04 eV, accompanied by enhanced transparency. Furthermore, simultaneous in situ diffraction and transport measurements confirm fully reversible redox-driven transitions among three phases: reduced defective perovskite, brownmillerite, and oxygen-rich perovskite phases. These findings demonstrate that selective redox control in multi-cation oxides enables the realization of chemically and functionally distinct oxygen-deficient phases.

Fuel cells↗