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At least 667 records · Page 37

Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions

This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein–protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.

59 BASIC BIOLOGICAL SCIENCES↗

New Trick for an Old Dog: From Prediction to Properties of “Hidden Clathrates” Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6

The zinc–antimony phase space has been heavily investigated due to the structural complexity and abundance of high-performing thermoelectric materials. Consequentially, the desire to use zinc and antimony as framework elements to encage rattling cations and achieve phonon-glass-electron-crystal-type properties has remained an enticing goal with only two alkali metal clathrates to date, Cs 8 Zn 18 Sb 28 and K 58 Zn 122 Sb 207 . Guided by Zintl electron-counting predictions, here we explored the Ba–Zn–Pn (Pn = As, Sb) phase space proximal to the expected composition of the type-I clathrate. In situ powder X-ray diffraction studies revealed two “hidden” compounds which can only be synthesized in a narrow temperature range. The ex situ synthesis and crystal growth unveiled that instead of type-I clathrates, compositionally close but structurally different new clathrate-like compounds formed, Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6 . These materials crystallize in a unique structure, in the orthorhombic space group Pmna with the Wyckoff sequence i 2 h 6 gfe. Single-phase synthesis enabled the exploration of their transport properties. Rattling of the Ba cations in oversized cages manifested low thermal conductivity, which, coupled with the high Seebeck coefficients observed, are prerequisites for a promising thermoelectric material. Potential for further optimization of the thermoelectric performance by aliovalent doping was computationally analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Three-Dimensional Imaging and Quantification of Gas Storativity in Nanoporous Media via X-rays Computed Tomography

This study provides the engineering science underpinnings for improved characterization and quantification of the interplay of gases with kerogen and minerals in shale. Natural nanoporous media such as shale (i.e., mudstone) often present with low permeability and dual porosity, making them difficult to characterize given the complex structural and chemical features across multiple scales. These structures give nanoporous solids a large surface area for gas to sorb. In oil and gas applications, full understanding of these media and their sorption characteristics are critical for evaluating gas reserves, flow, and storage for enhanced recovery and CO 2 sequestration potential. Other applications include CO 2 capture from industrial plants, hydrogen storage on sorbent surfaces, and heterogeneous catalysis in ammonia synthesis. Therefore, high-resolution experimental procedures are demanded to better understand the gas–solid behavior. In this study, CT imaging was applied on the sub-millimeter scale to shale samples (Eagle Ford and Wolfcamp) to improve quantitative agreement between CT-derived and pulse decay (mass balance) derived results. Improved CT imaging formulations are presented that better match mass balance results, highlighting the significance of gas sorption in complex nanoporous media. The proposed CT routine implemented on the Eagle Ford sample demonstrated a 17% error reduction (22% to 5%) when compared to the conventional CT procedure. These observations are consistent in the Wolfcamp sample, emphasizing the reliability of this technique for broader implementation of digital adsorption studies in nanoporous geomaterials.

42 ENGINEERING↗

Performance of Embedded Sensors in 3D Printed SiC

This report summarizes recent advances in embedding sensors in 3D printed silicon carbide (SiC) ceramic components under the Transformational Challenge Reactor (TCR) program. The additive manufacturing technologies developed under this program will enable fabrication of complex structures with embedded fuels and sensors. The sensors will be capable of characterizing fuel performance using spatially distributed measurements at the most strategic locations that would be otherwise inaccessible using conventional manufacturing techniques. While previous programmatic updates describe initial concepts for embedding sensors, materials selection, and initial characterization of the embedded sensors, the technology requires further demonstration, and quality-significant procedures must be established before the embedding technology is ready for adoption by industry. To this end, this report describes the most effective techniques that have been used to embed functional sensors in 3D printed components using a combination of binder-jet additive manufacturing and chemical vapor infiltration (CVI). A detailed procedure describes each step in the process and is available upon request. Molybdenum (Mo)-sheathed thermocouples have been successfully embedded in complex SiC components, and temperatures were monitored in situ during the embedding process. Post-embedding measurements showed no significant hysteresis, and characterization of the interface revealed qualitatively strong bonding around the entire perimeter of the sensor sheath. Distributed fiber-optic temperature sensors were able to briefly measure temperature profiles during CVI, but they ultimately failed prior to completion of the CVI run. The failure appears to be related to the fiber coating at temperatures close to 1,000°C. Future work will focus on irradiation testing of embedded thermocouples and other sheathed electrical sensors, as well as the identification of fiber-optic sensor coatings that can survive CVI.

42 ENGINEERING↗

Prediction and Validation of Flow Properties in Porous Lattice Structures

High-porosity metal foams have been extensively studied as an attractive candidate for efficient and compact heat exchanger design. With the advancements in additive manufacturing, such foams can be manufactured with controlled topology to yield highly tailorable mechanical and transport properties. In this study, a lattice Boltzmann method (LBM)-based pore-scale model is implemented to simulate the fluid flow in additively manufactured (AM) metal foams with unit cell topologies of Cube, Face Diagonal (FD)-Cube, Tetrakaidecahedron (TKD), and Octet lattices. The pressure gradient versus average velocity profiles predicted by the LBM model were validated against in-house measurements on the AM lattice samples with the same unit cell topologies. Based on the simulation results, a novel hybrid model is proposed to accurately predict the volume averaged flow properties (permeability and inertial coefficients) of the four structures. Specifically, the linear LBM (neglecting inertial forces) is first implemented to obtain the intrinsic permeability, and then the standard LBM is applied to obtain the inertial coefficient. Convenient correlations for those flow properties as a function of porosity and fiber diameter are constructed. The effects of the AM print qualities on the flow properties are also discussed. The advantages of the hybrid model compared to the polynomial fitting approach for determining flow properties are discussed and compared quantitatively. The hybrid model and presented results are valuable for flow and thermal transport evaluation when designing new metal foams for specific applications and with different materials and topologies. Finally, the presented correlations based on pore-scale simulations can also be conveniently used in volume-averaged models to predict the macroscale flow behavior in such complex structures.

42 ENGINEERING↗

Effect of iron redox ratio on the structures of boroaluminosilicate glasses

Iron oxide is commonly found in natural or industrial glass compositions and can exist as ferrous (Fe 2+ ) or ferric (Fe 3+ ) species, with their ratios depending on glass composition, temperature, pressure and the redox reactions during the glass forming process. The iron redox ratio plays an important role on silicate glass structures and consequently various properties. This work aims to study the effect of iron oxide, and particularly the iron redox ratio, on the structures of borosilicate and boroaluminosilicate glasses using molecular dynamics simulations with newly developed iron potential parameters that are compatible with the borosilicate potentials. The results provide detailed cation coordination states of both iron species and the effect of redox ratio on boron coordination and other structural features. Particularly, competition for charge compensating modifier cations (such as Na + ) among the fourfold-coordinated cations such as B 3+ , Al 3+ , and Fe 3+ is investigated by calculating the cation–cation pair distribution functions and coordination preferential ratios. The results show that the trivalent ferric ions, with a shorter Fe–O bond distance and better defined first coordiation shell with mainly four-fold coordination, act as a glass former whereas the divalent ferrous ions mainly play the role of glass modifier. The ferrous/ferric ratio (Fe 2+ /Fe 3+ ) was found to affect the glass chemistry and hence glass properties by regulating the amount of four-coordinated boron, the fraction of non-briding oxygen and other features. Finally, the results are compared with available experimental data to gain insights of the complex structures and charge compensation schemes of the glass system.

36 MATERIALS SCIENCE↗

On Simulating the Formation of Structured, Crystalline Systems via Non-classical Pathways

Observations in crystal growth and assembly from recent in situ methods suggest alternative, non-classical crystallization pathways play an important role in the determination of the micro- and meso- structures in crystalline systems. These processes display parallels that cross-cut multiple disciplines investigating crystallization across four orders of magnitude in size scales and widely differing environments, hinting that alternative crystal growth pathways may be a fundamental scheme in natural crystal formation. Using a system of short-range attractive microbeads, we demonstrate that the addition of a small concentration of sub-species incommensurate with the lattice spacing of the dominant species results in a stark change in crystal size and morphology. These changes are attributed to the presence of fleeting, amorphous-like configurations of beads that ultimately change the melting and growth dynamics in preferred directions. From these real-time observations, we hypothesize the amorphous mineral precursors present in biological mineralized tissues undergo similar non-classical crystallization processes resulting in the complex structures found in biomineralization.

36 MATERIALS SCIENCE↗

Structural Health Monitoring of Nuclear Spent Fuel Storage Facilities

Interim storage of spent nuclear fuel from reactor sites has gained additional importance and urgency for resolving waste-management-related technical issues. To ensure that nuclear power remains clean energy, monitoring has been identified by DOE as a high priority cross-cutting need, necessary to determine and predict the degradation state of the systems, structures, and components (SSCs) important to safety (ITS). Therefore, nondestructive structural condition monitoring becomes a need to be installed on existing or to be integrated into future storage system to quantify the state of health or to guarantee the safe operation of nuclear power plants (NPPs) during their extended life span. In this project, the lead university and the collaborating national laboratory teamed to develop a nuclear structural health monitoring (n-SHM) system based on in-situ piezoelectric sensing technologies that can monitor structural degradation and aging for nuclear spent fuel DCSS and similar structures. We also aimed to identify and quantify possible influences of nuclear spent fuel environment (temperature and radiation) to the piezoelectric sensor system and come up with adequate solutions and guidelines therefore. We have therefore developed analytical model for piezoelectric based n-SHM methods, with considerations of temperature and irradiation influence on the model of sensing and algorithms in acoustic emission (AE), guided ultrasonic waves (GUW), and electromechanical impedance spectroscopy (EMIS). On the other side, experimentally the temperature and irradiation influence on the piezoelectric sensors and sensing capabilities were investigated. Both short-term and long-term irradiation investigation with our collaborating national laboratory were performed. Moreover, we developed multi-modal sensing, validated in laboratory setup, and conducted the testing on the We performed multi-modal sensing development, verification and validation tests on very complex structures including a medium-scale vacuum drying chamber and a small-scale mockup canister available for the desired testing. Our work developed the potential candidate for long term structural health monitoring of spent fuel canister through piezoelectric wafer sensors and provided the sensing methodologies based on AE and GUW methodologies. It overall provides an innovative system and methodology for enhancing the safe operation of nuclear power plant. All major accomplishments planned in the original proposal were successfully achieved.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New results in the studies of the high-lying nucleon resonances from the CLAS data on pi+pi-p electroproduction

The exclusive double-pion electroproduction represents the primary source of information on the structure of excited proton states in the mass region MN∗ > 1.6 GeV. Preliminary results on electrocouplings and πΔ and ρp hadronic decays of prominent N∗ states in this mass range will be presented. They were obtained from the analysis of CLAS data on π+π−p electroproduction at photon virtualities 0.5<Q2<1.5 GeV2 [1] within the framework of the reaction model [2]. Our results confirmed the electrocouplings of N(1680)5/2+ resonance determined in the studies of Nπ exclusive channels [3]. The electrocouplings of Δ(1620)1/2−, Δ(1700)3/2−, and N(1720)3/2+ resonances were determined for the first time from analysis of π+π−p electroproduction with good accuracy. The results on electrocouplings of proton states in the mass range up to 1.8 GeV provide stringent constraints for the development of QCD-based approaches aimed at describing the complex structure of excited nucleon states.

Burkert, Volker↗

High Performance-Multidisciplinary Simulation for Regional Scale Earthquake Hazard and Risk Assessments

Moderate-to-large magnitude earthquakes represent a significant risk around the world and a major issue across the Department of Energy (DOE) mission interests, ranging from DOE's one-of-a-kind mission critical facilities to national energy systems (nuclear power plants, electric/gas distribution systems, and renewable energy production facilities). As a result, for the DOE there is a strong motivation in promoting and developing a risk-informed and performance-based approach for both the assessment of existing facilities and the design of new structures. DOE National Labs have historically made multidisciplinary contributions to the solution of challenging seismic hazard and risk problems and have been at the forefront for the development of design standards for major facilities. The current approach for estimating the ground motion hazard for critical facilities is based upon a Probabilistic Seismic Hazard Analysis (PSHA), whereby measured ground motion data are collected and homogenized into a probabilistic framework to estimate the hazard for future events. However, recent studies have highlighted the site-specific nature of earthquakes and shown the limitations of a purely empirical approach. Moreover, the design of infrastructure systems has been moving toward a performance-based approach, in which specific performance goals are specified at different levels of excitation and for different limit states. Such an approach requires the availability of robust and reliable computational tools for the nonlinear dynamic analysis of complex structural systems. Ongoing research at Lawrence Berkeley National Laboratory (LBNL) and Lawrence Livermore National Laboratory (LLNL) aims at developing an advanced simulation environment at the exascale for a coupled assessment of earthquake hazard (ground motions) and earthquake risk (structural demands)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mechanistic Insights into Copper(I) and Copper(II) Cation Exchange Reactions in CdSe Nanoplatelets

In this study, we investigated the synthesis of copper selenide nanoplatelets (NPLs) through a cation exchange reaction (CER) in 5-monolayer-thick CdSe NPLs using Cu(I) and Cu(II) precursors. We discovered that the exposure of CdSe NPLs to a Cu(I) precursor led to the transformation of NPLs into Cu 2-x Se while maintaining their nanoplatelet morphology. The replacement of Cd(II) with Cu(I) prevailed over the formation of doped structures. In the case of the Cu(II) precursor, we observed that Cu(II) was first reduced to Cu(I) before being intercalated into the host lattice, resulting in the synthesis of Cu 2-x Se, similar to CER with Cu(I) precursors but without preservation of the initial morphology of NPLs. Interestingly, the presence of oxygen was found to facilitate the cation exchange processes in CdSe NPLs, whereas a nitrogen atmosphere suppressed the CER. Further, despite the similar ionic sizes of Cu(I) and Cu(II), the substitution of Cd(II) with Cu(II) was found to be challenging, possibly due to the involvement of redox processes resulting in the significant deterioration of initial CdSe NPLs. We demonstrate that CER can achieve near-complete substitution of cadmium atoms with monovalent copper at room temperature. Understanding the processes involved in CERs is crucial for engineering more complex structures, such as high-entropy nanoparticles involving cation exchange with different oxidation states and development of material synthesis using machine learning and artificial intelligence approaches.

2D nanoplatelets↗

Dynamic Evolution of Copper Nanowires during CO 2 Reduction Probed by Operando Electrochemical 4D-STEM and X-ray Spectroscopy

Nanowires have emerged as an important family of one-dimensional (1D) nanomaterials owing to their exceptional optical, electrical, and chemical properties. In particular, Cu nanowires (NWs) show promising applications in catalyzing the challenging electrochemical CO 2 reduction reaction (CO 2 RR) to valuable chemical fuels. Despite early reports showing morphological changes of Cu NWs after CO 2 RR processes, their structural evolution and the resulting exact nature of active Cu sites remain largely elusive, which calls for the development of multimodal operando time-resolved nm-scale methods. Here, in this study, we report that well-defined 1D copper nanowires, with a diameter of around 30 nm, have a metallic 5-fold twinned Cu core and around 4 nm Cu 2 O shell. Operando electrochemical liquid-cell scanning transmission electron microscopy (EC-STEM) showed that as-synthesized Cu@Cu 2 O NWs experienced electroreduction of surface Cu 2 O to disordered (spongy) metallic Cu shell (Cu@Cu S NWs) under CO 2 RR relevant conditions. Cu@Cu S NWs further underwent a CO-driven Cu migration leading to a complete evolution to polycrystalline metallic Cu nanograins. Operando electrochemical four-dimensional (4D) STEM in liquid, assisted by machine learning, interrogates the complex structures of Cu nanograin boundaries. Correlative operando synchrotron-based high-energy-resolution X-ray absorption spectroscopy unambiguously probes the electroreduction of Cu@Cu 2 O to fully metallic Cu nanograins followed by partial reoxidation of surface Cu during postelectrolysis air exposure. This study shows that Cu nanowires evolve into completely different metallic Cu nanograin structures supporting the operando (operating) active sites for the CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlated disorder-to-order crossover in the local structure of K x Fe 2 - y Se 2 - z S z

Here, a detailed account of the local atomic structure and disorder at 5 K across the phase diagram of the high-temperature superconductor K x Fe 2 - y Se 2 - z S z ( 0 ≤ z ≤ 2) is obtained from neutron total scattering and associated atomic pair distribution function (PDF) approaches. Various model-independent and model-dependent aspects of the analysis reveal a high level of structural complexity on the nanometer length scale. Evidence is found for considerable disorder in the c -axis stacking of the ${\mathrm{FeSe}}_{1{-}x}{\mathrm{S}}_{x}$ slabs without observable signs of turbostratic character of the disorder. In contrast to the related FeCh (Ch = S, Se)-type superconductors, substantial Fe-vacancies are present in ${\mathrm{K}}_{x}{\mathrm{Fe}}_{2{-}y}{\mathrm{Se}}_{2{-}z}{\mathrm{S}}_{z}$ deemed detrimental for superconductivity when ordered. Our study suggests that the distribution of vacancies significantly modifies the iron-chalcogen bond-length distribution, in agreement with observed evolution of the PDF signal. A crossoverlike transition is observed at a composition of z ≈ 1 , from a correlated disorder state at the selenium end to a more vacancy-ordered (VO) state closer to the sulfur end of the phase diagram. The S-content-dependent measures of the local structure are found to exhibit distinct behavior on either side of this crossover, correlating well with the evolution of the superconducting state to that of a magnetic semiconductor toward the z ≈ 2 end. The behavior reinforces the idea of the intimate relationship of correlated Fe-vacancy order in the local structure and the emergent electronic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Customizable Approach for the Enzymatic Production and Purification of Diterpenoid Natural Products

Diterpenoids form a diverse class of small molecule natural products that are widely distributed across the kingdoms of life and have critical biological functions in developmental processes, interorganismal interactions, and environmental adaptation. Due to these various bioactivities, many diterpenoids are also of economic importance as pharmaceuticals, food additives, biofuels, and other bioproducts. Advanced genomics and biochemical approaches have enabled a rapid increase in the knowledge of diterpenoid-metabolic genes, enzymes, and pathways. However, the structural complexity of diterpenoids and the narrow taxonomic distribution of individual compounds in often only a single species remain constraining factors for their efficient production. Availability of a broader range of metabolic enzymes now provide resources for producing diterpenoids in sufficient titers and purity to facilitate a deeper investigation of this important metabolite group. Drawing on established tools for microbial and plant-based enzyme co-expression, we present an easily operated and customizable protocol for the enzymatic production of diterpenoids in either Escherichia coli or Nicotiana benthamiana, and the purification of desired products via silica chromatography and semi-preparative HPLC. Using the group of maize (Zea mays) dolabralexin diterpenoids as an example, we highlight how modular combinations of diterpene synthase (diTPS) and cytochrome P450 monooxygenase (P450) enzymes can be used to generate different diterpenoid scaffolds. Purified compounds can be used in various downstream applications, such as metabolite structural analyses, enzyme structure-function studies, and in vitro and in planta bioactivity experiments.

09 BIOMASS FUELS↗

Isothermal Microcalorimetry Analysis of Li/ β -MnO 2 Discharge

Despite widespread use over several decades, the lithium/manganese dioxide (Li/MnO 2 ) discharge mechanism is not completely understood owing to the structural complexity of the material. However, an improved understanding could lead to broader adoption as a primary and even secondary cathode material. Here, we examine the discharge of single-phaseβ-MnO 2 using isothermal microcalorimetry for the first time. Equilibrium voltage and entropy changes are characterized over the entire discharge range and used to rationalize the results. These measurements are supplemented by electrochemical impedance and X-ray diffraction data that give the clearest picture of theβ-MnO 2 lithiation process to date. We find that the first half of discharge is dominated by a two-phase reaction to form Li 0.5 MnO 2 followed by single-phase insertion to a composition of Li 1.0 MnO 2 , which confirms prior first-principles calculations. The tetragonalβ-MnO 2 lattice undergoes asymmetric expansion from Jahn-Teller distorted Mn 3+ to form an orthorhombic LiMnO 2 phase which retains the 1 × 1 tunnel structure. Microcalorimetry results suggest the presence of parasitic reactions occurring during the second half of discharge, which could arise from decomposition of electrolyte or release and reaction of residual water retained in the structure.

Electrochemistry↗

Dual Atomic Coherence in the Self-Assembly of Patchy Heterostructural Nanocrystals

Advances in the synthesis and self-assembly of nanocrystals have enabled researchers to create a plethora of different nanoparticle superlattices. But while many super lattices with complex types of translational order have been realized, rotational order of nanoparticle building blocks within the lattice is more difficult to achieve. Self-assembled superstructures with atomically coherent nanocrystal lattices, which are desirable due to their exceptional electronic and optical properties, have been fabricated only for a few selected systems. Here, we combine experiments with molecular dynamics (MD) simulations to study the self-assembly of heterostructural nanocrystals (HNCs), consisting of a near-spherical quantum dot (QD) host decorated with a small number of epitaxially grown gold nanocrystal (Au NC) "patches ". Self-assembly of these HNCs results in face-centered-cubic (fcc) superlattices with well-defined orientational relationships between the atomic lattices of both QD hosts and Au patches. MD simulations indicate that the observed dual atomic coherence is linked to the number, size, and relative positions of gold patches. Here this study provides a strategy for the design and fabrication of NC superlattices with large structural complexity and delicate orientational order.

77 NANOSCIENCE AND NANOTECHNOLOGY↗