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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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At least 91 records · Page 5

DNA origami protection and molecular interfacing through engineered sequence-defined peptoids

DNA nanotechnology has established approaches for designing programmable and precisely controlled nanoscale architectures through specific Watson−Crick base-pairing, molecular plasticity, and intermolecular connectivity. In particular, superior control over DNA origami structures could be beneficial for biomedical applications, including biosensing, in vivo imaging, and drug and gene delivery. However, protecting DNA origami structures in complex biological fluids while preserving their structural characteristics remains a major challenge for enabling these applications. Here, we developed a class of structurally well-defined peptoids to protect DNA origamis in ionic and bioactive conditions and systematically explored the effects of peptoid architecture and sequence dependency on DNA origami stability. The applicability of this approach for drug delivery, bioimaging, and cell targeting was also demonstrated. A series of peptoids (PE1–9) with two types of architectures, termed as “brush” and “block,” were built from positively charged monomers and neutral oligo-ethyleneoxy monomers, where certain designs were found to greatly enhance the stability of DNA origami. Through experimental and molecular dynamics studies, we demonstrated the role of sequence-dependent electrostatic interactions of peptoids with the DNA backbone. We showed that octahedral DNA origamis coated with peptoid (PE2) can be used as carriers for anticancer drug and protein, where the peptoid modulated the rate of drug release and prolonged protein stability against proteolytic hydrolysis. Finally, we synthesized two alkyne-modified peptoids (PE8 and PE9), conjugated with fluorophore and antibody, to make stable DNA origamis with imaging and cell-targeting capabilities. Our results demonstrate an approach toward functional and physiologically stable DNA origami for biomedical applications.

36 MATERIALS SCIENCE↗

A unified understanding of minimum lattice thermal conductivity

Here, we propose a first-principles model of minimum lattice thermal conductivity ($κ^{min}_L$) based on a unified theoretical treatment of thermal transport in crystals and glasses. We apply this model to thousands of inorganic compounds and find a universal behavior of $κ^{min}_L$ in crystals in the high-temperature limit: The isotropically averaged $κ^{min}_L$ is independent of structural complexity and bounded within a range from ~0.1 to ~2.6 W/(m K), in striking contrast to the conventional phonon gas model which predicts no lower bound. We unveil the underlying physics by showing that for a given parent compound, $κ^{min}_L$ is bounded from below by a value that is approximately insensitive to disorder, but the relative importance of different heat transport channels (phonon gas versus diffuson) depends strongly on the degree of disorder. Moreover, we propose that the diffuson-dominated $κ^{min}_L$ in complex and disordered compounds might be effectively approximated by the phonon gas model for an ordered compound by averaging out disorder and applying phonon unfolding. With these insights, we further bridge the knowledge gap between our model and the well-known Cahill–Watson–Pohl (CWP) model, rationalizing the successes and limitations of the CWP model in the absence of heat transfer mediated by diffusons. Finally, we construct graph network and random forest machine learning models to extend our predictions to all compounds within the Inorganic Crystal Structure Database (ICSD), which were validated against thermoelectric materials possessing experimentally measured ultralow κ L . Our work offers a unified understanding of $κ^{min}_L$, which can guide the rational engineering of materials to achieve .

42 ENGINEERING↗

Base pairing, structural and functional insights into N 4 -methylcytidine (m 4 C) and N 4 ,N 4 -dimethylcytidine (m 4 2 C) modified RNA

The N 4 -methylation of cytidine (m 4 C and m 4 2 C) in RNA plays important roles in both bacterial and eukaryotic cells. In this work, we synthesized a series of m 4 C and m 4 2 C modified RNA oligonucleotides, conducted their base pairing and bioactivity studies, and solved three new crystal structures of the RNA duplexes containing these two modifications. Our thermostability and X-ray crystallography studies, together with the molecular dynamic simulation studies, demonstrated that m 4 C retains a regular C:G base pairing pattern in RNA duplex and has a relatively small effect on its base pairing stability and specificity. By contrast, the m 4 2 C modification disrupts the C:G pair and significantly decreases the duplex stability through a conformational shift of native Watson-Crick pair to a wobble-like pattern with the formation of two hydrogen bonds. This double-methylated m 4 2 C also results in the loss of base pairing discrimination between C:G and other mismatched pairs like C:A, C:T and C:C. The biochemical investigation of these two modified residues in the reverse transcription model shows that both mono- or di-methylated cytosine bases could specify the C:T pair and induce the G to T mutation using HIV-1 RT. In the presence of other reverse transcriptases with higher fidelity like AMV-RT, the methylation could either retain the normal nucleotide incorporation or completely inhibit the DNA synthesis. These results indicate the methylation at N 4 -position of cytidine is a molecular mechanism to fine tune base pairing specificity and affect the coding efficiency and fidelity during gene replication.

59 BASIC BIOLOGICAL SCIENCES↗

ADAR activation by inducing a syn conformation at guanosine adjacent to an editing site

Abstract ADARs (adenosine deaminases acting on RNA) can be directed to sites in the transcriptome by complementary guide strands allowing for the correction of disease-causing mutations at the RNA level. However, ADARs show bias against editing adenosines with a guanosine 5′ nearest neighbor (5′-GA sites), limiting the scope of this approach. Earlier studies suggested this effect arises from a clash in the RNA minor groove involving the 2-amino group of the guanosine adjacent to an editing site. Here we show that nucleosides capable of pairing with guanosine in a syn conformation enhance editing for 5′-GA sites. We describe the crystal structure of a fragment of human ADAR2 bound to RNA bearing a G:G pair adjacent to an editing site. The two guanosines form a Gsyn:Ganti pair solving the steric problem by flipping the 2-amino group of the guanosine adjacent to the editing site into the major groove. Also, duplexes with 2′-deoxyadenosine and 3-deaza-2′-deoxyadenosine displayed increased editing efficiency, suggesting the formation of a Gsyn:AH+anti pair. This was supported by X-ray crystallography of an ADAR complex with RNA bearing a G:3-deaza dA pair. This study shows how non-Watson–Crick pairing in duplex RNA can facilitate ADAR editing enabling the design of next generation guide strands for therapeutic RNA editing.

Doherty, Erin E.↗

Processing of DNA single-strand breaks with oxidatively damaged ends by LIG1

Abstract DNA ligase 1 (LIG1) seals broken strand breaks by joining two adjacent ends during DNA replication and repair transactions. We previously reported atomic-level insight into the strategies that LIG1 uses to discriminate mismatches or ribonucleotides. However, how LIG1 processes strand breaks with oxidatively damaged ends in the absence and presence of a “wrong” sugar remains unknown. Here, we determined the crystal structures of LIG1/nick DNA complexes with 3′-8-oxodG and 3′-8-oxorG templating A or C during the pre- and post-catalytic steps of the ligation reaction. Our structures demonstrated differences in the distances at the +1 and +2 nucleotides relative to the 3′-end of the nick and a shift in the template base position to accommodate the oxidative lesion depending on the dual coding potential of 8-oxoG, which forms Hoogsteen or Watson–Crick base pairing in -syn or -anti conformation. Furthermore, these structural adjustments lead to mutagenic ligation or non-mutagenic end joining of the nick substrates. Overall, our findings provide mechanistic insight into how LIG1 processes nicks harboring oxidative damage and ribonucleotides to ensure fidelity at the final ligation step of DNA repair and replication to maintain genome integrity.

Balu, Kanal E [Department of Biochemistry and Mole↗

Crystal structures of ‘ALternative Isoinformational ENgineered’ DNA in B-form

The first structural model of duplex DNA reported in 1953 by Watson & Crick presented the double helix in B-form, the form that genomic DNA exists in much of the time. Thus, artificial DNA seeking to mimic the properties of natural DNA should also be able to adopt B-form. Using a host–guest system in which Moloney murine leukemia virus reverse transcriptase serves as the host and DNA as the guests, we determined high-resolution crystal structures of three complexes including 5'-CTTBPPBBSSZZSAAG, 5'-CTTSSPBZPSZBBAAG and 5'-CTTZZPBSBSZPPAAG with 10 consecutive unnatural nucleobase pairs in B-form within self-complementary 16 bp duplex oligonucleotides. We refer to this ALternative Isoinformational ENgineered (ALIEN) genetic system containing two nucleobase pairs (P:Z, pairing 2-amino-imidazo-[1,2-a]-1,3,5-triazin-(8H)-4-one with 6-amino-5-nitro-(1H)-pyridin-2-one, and B:S, 6-amino-4-hydroxy-5-(1H)-purin-2-one with 3-methyl-6-amino-pyrimidin-2-one) as ALIEN DNA. We characterized both position- and sequence-specific helical, nucleobase pair and dinucleotide step parameters of P:Z and B:S pairs in the context of B-form DNA. We conclude that ALIEN DNA exhibits structural features that vary with sequence. Further, Z can participate in alternative stacking modes within a similar sequence context as captured in two different structures. This finding suggests that ALIEN DNA may have a larger repertoire of B-form structures than natural DNA.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of three-body forces on elastic nucleon-nucleus scattering observables

In a previous series of papers we investigated the domain of applicability of chiral potentials to the construction of a microscopic optical potential (OP) for elastic nucleon-nucleus scattering. The OP was derived at the first order of the spectator expansion of the Watson multiple scattering theory and its final expression was a folding integral between the nucleon-nucleon ( N N ) t matrix and the nuclear density of the target. In the calculations N N and three-nucleon ( 3 N ) chiral interactions were used for the target density and only the N N interaction for the N N t matrix. The purpose of this study is to achieve another step towards the calculation of a more consistent OP introducing the 3 N force also in the dynamic part of the OP. The full treatment of the 3 N interaction is beyond our present capabilities. Thus, here it is approximated with a density dependent N N interaction obtained after the averaging over the Fermi sphere. In practice, in our model the 3 N force acts as a medium correction of the bare N N interaction used to calculate the t matrix. Even if the 3 N force is treated in an approximate way, this method naturally extends our previous model of the OP and allows a direct comparison of our present and previous results. We consider as case studies the elastic scattering of nucleons off C 12 and O 16 . We present results for the differential cross section and the spin observables for different values of the projectile energy. From the comparison with the experimental data and with the results of our previous model we assess the importance of the 3 N interaction in the dynamic part of the OP. Conclusions: Our analysis indicates that the contribution of the 3 N force in the t matrix is small for the differential cross section and it is sizable for the spin observables, in particular, for the analyzing power. We find that the two-pion exchange term is the major contributor to the 3 N force. A chiral expansion order-by-order analysis of the scattering observables confirms the convergence of our results at the next-to-next-to-next-to-leading-order, as already established in our previous work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Elastic proton scattering off nonzero spin nuclei

In recent years, we constructed a microscopic optical potential (OP) for elastic nucleon-nucleus ( NA ) scattering using modern approaches based on chiral theories for the nucleon-nucleon ( NN ) interaction. The OP was derived at first order of the spectator expansion in Watson multiple scattering theory and its final expression was a folding integral between the NN t matrix and the nuclear density of the target. Two- and three-body forces are consistently included both in the target and in the projectile description. The purpose of this work is to apply our microscopic OP to nuclei characterized by a ground state of spin-parity quantum numbers J π ≠ 0 + . We extended our formalism to include the spin of the target nucleus. The full amplitudes of the NN reaction matrix are retained in the calculations starting from two- and three-body chiral forces. The microscopic OP can be applied in the energy range 100 ≤ E ≤ 350 MeV. Finally, we show a remarkable agreement with experimental data for the available observables and, simultaneously, provide reliable estimates for the theoretical uncertainties. This work paves the way toward a full microscopic approach to inelastic NA scattering, showing that the derivation of optical potentials between states with J π ≠ 0 + is completely under control.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗

A Note on the Probability of Initiation Problem

The purpose of this note is to draw attention to Pál’s derivation of the Pál Bell equation which is used by LLNL and LANL to model Probability of Initiation (POI) problems. Both laboratories credit the equation to Bell and Lee. Although the equation formulated by Bell and Lee and the equation derived by Pál appear to be the same, the derivation by Bell and Lee is flawed. Scattering, which was absent in Bell’s original formulation of a POI problem, was later introduced by Bell and Lee by simply replacing a fission term with a scattering term. Such a replacement, however, leads to an inaccurate average number v̅ of neutrons that is produced by a fission event. By approaching a POI problem from probabilistic point of view, Pál formulates the problem as a branching process that determines v̅ correctly. There are six reasons for writing this report. The first is to clarify the failing in Bell and Lee’s derivation. The second is to establish the origin of the equation used by the laboratories. The third is to elucidate the fixed point technique formulated by Mokhtar-Kharroubi for solving the Pál-Bell equation. The fourth is to derive the α eigenvalue that is associated with a time dependent Pál-Bell equation. The fifth is to show in Appendix A that the non-linear fission operator of the Pál-Bell equation is descended from the operator of the Galton-Watson process of stochastic theory. The sixth is to describe in Appendix B a second order positivity preserving technique that accelerates the convergence of the first order fixed point method developed by Mokhtar-Kharroubi.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

TEX-HEU: Integral Experiment Execution with Polyethylene at Very Low Temperatures

The low-temperature variant of the TEX HEU (called Low-Temperature TEX or sometimes LT TEX) campaign is a highly anticipated and necessary experimental series by the greater nuclear science community. Fundamentally, the need for low-temperature integral experiments is required to perform validation of cross sections below room temperature. There has been substantial international interest in low-temperature benchmarks to validate below room temperature cross sections, namely talks given at the 2019 International Conference on Nuclear Criticality (ICNC): UK (Watson, 2019), France (Milin, 2019), and UK (Gan & Wilson, 2019). Additionally, NCSP funded thermal scattering laws (TSLs) were produced by North Carolina State University and require low-temperature benchmarks to validate them. Validation of low-temperature cross sections is also necessary for criticality safety applications. One particularly important application is to ensure that during transportation, fissile materials must remain subcritical under normal ambient conditions which is defined as temperatures down to -40°C/°F by the United States 10 CRF 71 as well as a regulation put forward by the International Atomic Energy Agency (IAEA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

CRADA Final Report: CRADA Number NFE-24-10036 with ThermaMatrix, Inc.

ThermaMatrix, Inc provides novel vision inspection solutions for a wide range of manufacturers and industries, providing and implementing the leading technologies for nondestructive inspection (NDI) and material characterization. Many other inspection solutions are either not adequate or are not approachable due to implementation barriers needing expert level operators, excessive inspection time, and high cost. ThermaMatrix’s advanced vision inspection technology addresses all of these limitations. The Lab Embedded Entrepreneurial Program (LEEP) opportunity by the Department of Energy (DOE) allows small-business start-ups to leverage national laboratory capabilities and skilled scientists to rapidly develop their technology that aligns with DOE goals. ThermaMatrix, Inc. was positioned in the Innovation Crossroads program at Oak Ridge National Laboratory to further develop the novel Watson Vision Inspection System to support manufacturing quality control efforts. The research goals were (1) explore fundamental parameters that would improve preexisting capabilities, (2) full-scale industrial setup for demonstration, and (3) capability testing and verification. Manufacturing is demanding more NDI implementation to support their quality control needs, which this technology development would support.

36 MATERIALS SCIENCE↗

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗

Finite amplitude instability of second-order fluids in plane Poiseuille flow.

The hydrodynamic stability of plane Poiseuille flow of second-order fluids to finite amplitude disturbances is examined using the method of Stuart and Watson as extended by Reynolds and Potter. For slightly non-Newtonian fluids subcritical instabilities are predicted. No supercritical equilibrium states are expected if the entire spectrum of disturbance wavelengths is present. Possible implications with respect to the Toms phenomenon are discussed.

Mcintire, L. V.↗

The effects of recent opacity corrections on a main-sequence stellar model of 2.25 solar masses.

Comparison of models calculated with the opacities of Carson et al. (1968) and the electron-scattering corrections of Watson with models based on the opacities of Cox et al. (1965). The models have a mass of 2.25 solar masses and a chemical composition with X = 0.596 and Z = 0.02. With the adopted formulas representing the new opacities, it is found that the percentage changes with respect to the model based on the opacities of Cox et al. can be as large as +11 for the stellar radius, -42 for the luminosity, -15 for the effective temperature, -30 for the mass of the convective core, -8 for the central pressure, and -4 for both the central density and the central temperature.

Novotny, E.↗

Elastic scattering of 600-MeV protons from H, D, He-3, and He-4.

Study of the elastic scattering of 600-MeV protons from light nuclei. Differential cross sections have been obtained for the scattering of protons from hydrogen, deuterium, helium-3, and helium-4. Polarization was measured for deuterium and He-4 nuclei. The p-p cross-section data are in excellent agreement with the predictions from the Livermore phase shifts. Small-angle p-D, p-He-3 elastic scattering data are compared with calculations based on the multiple-scattering theories of Watson and Glauber.

Boschitz, E. T.↗