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At least 217 records · Page 12

Waste Handling and Emplacement Options for Disposal of Radioactive Waste in Deep Boreholes.

Traditional methods cannot be used to handle and emplace radioactive wastes in boreholes up to 16,400 feet (5 km) deep for disposal. This paper describes three systems that can be used for handling and emplacing waste packages in deep borehole: (1) a 2011 reference design that is based on a previous study by Woodward–Clyde in 1983 in which waste packages are assembled into “strings” and lowered using drill pipe; (2) an updated version of the 2011 reference design; and (3) a new concept in which individual waste packages would be lowered to depth using a wireline. Emplacement on coiled tubing was also considered, but not developed in detail. The systems described here are currently designed for U.S. Department of Energy-owned high-level waste (HLW) including the Cesium- 137/Strontium-90 capsules from the Hanford Facility and bulk granular HLW from fuel processing in Idaho.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The SURE House (Solar Decathlon 2015)

Coastal towns and cities across the Northeastern US, with their high population density, aged utility infrastructure, and unique geography, are increasingly vulnerable to climate change related storm events. In October 2012 superstorm Sandy highlighted the fragility of our current coastal building types and made clear the need for a new model of design and construction which works to understand and mitigate these weaknesses. Dramatic changes in public policy, championed by both The Federal Emergency Management Agency (FEMA) and the National Flood Insurance Program (NFIP) are driving the rebuilding of these shore communities, often resulting in costly renovations, un-sustainable neighborhood configurations and in direct conflict with concurrent government policies such as The American with Disabilities Act (ADA). The SURE HOUSE demonstrates a series of new design solutions to these conflicting public policies and environmental imperatives. At Stevens Institute of Technology, the 2015 Solar Decathlon started with the challenge: Can we design a home for coastal New Jersey that dramatically reduces its energy use while protecting itself from the realities of a changing, more extreme climate? The SURE HOUSE merges the iconic 20th century shore home with 21st century building science. Utilizing innovative renewable energy technologies, a ‘Passive House’ level building envelope, and rugged glass-fiber-composite materials to flood-proof the home, the SURE HOUSE is a high-performance, net-zero-energy home, armored against extreme weather, designed for the contemporary lifestyle of the Jersey Shore and other vulnerable coastal communities. SUSTAINABLE At Stevens, we recognize that energy use in the home and workplace is directly connected to the growing problem of climate change. Reducing our energy consumption by designing higher performing, compact homes that are both functional, comfortable and desirable is the first critical step towards a modern, sustainable architecture for New Jersey and beyond. This is what informed the architectural design of the house. Configured about a compact form, thickly insulated and air-sealed walls eliminate thermal bridging and minimize energy losses while advanced glazing brings in free solar heat during the winter months. As a result of these passive design strategies, the SURE HOUSE has a greatly reduced carbon footprint requiring 91% less energy than a typical New Jersey home. Photovoltaic (PV) arrays on both the rooftop and operable shutters easily provide energy in excess of the home’s modest demands. The Stevens team considers a truly sustainable home in the era of climate change, one that prioritizes low energy use, and integrates right-sized renewable generation to supply the home’s needs. Low consumption, low production. RESILIENT In October of 2012, Hurricane Sandy wreaked havoc along the east coast of the US. In New Jersey alone there was an estimated 29.4 billion dollars in damages, 346,000 homes affected, and almost two and a half million people left without power, in some cases for over 10 days. Recovery from this storm and associated flooding is ongoing to this day, as many New Jersey homeowners grapple with the large costs of rebuilding and struggle to adapt to complicated new home building regulations. Damage from this storm to Hoboken, the home of the Stevens Institute of Technology’s campus, and to the New Jersey shore was extensive and many students on the SURE HOUSE team were directly affected by this historic event. The Stevens design team recognizes that in a world of more frequent and stronger storms, the ability to absorb and adapt to change is more important than ever. Successfully weathering the next storm and its aftermath is one of the primary goals in the design of the SURE HOUSE prototype. The SURE HOUSE introduces unique ‘dry flood-proofing’ methods to residential construction. Innovative wall and floor flood-proofing, utilizing durable composite sheathing materials adapted from the boating industry, were developed by the student team to render the SURE House’s building envelope flood proof up to the FEMA AE 6/7 Zone (+ 6/7 feet of water above sea-level). Designed and fabricated utilizing glass-fiber composite materials, the custom storm shutter system serves to protect the large glazed openings of the home from both air-borne debris impact and water infiltration during a storm event while also providing deterrence from the vandalism that often occurs in the aftermath of a calamitous event. During extended power outages, a ‘resilient’ solar array is capable of supplying critical amounts of energy and hot water to the home, without the use of battery storage or grid infrastructure. PV Description AC GRID-TIED PV SYSTEM The SURE HOUSE solar system consists of two distinct arrays, the grid-tied rooftop array which produces AC Powerand the shutter-mounted array which converts DC power generated by the modules directly into usable heat for the domestic hot water (DHW). The roof-mounted AC grid-tied array is comprised of three strings, two 11 module strings connected to an SMA SB 5000TL-US-223 inverter and a single 10 module string equipped and an SMA SB 3000TL-US-22 central inverter. All modules for the rooftop AC array are LG MonoX 2804 watt solar panels, chosen for their durability and efficiency. Inverter sizing and string size are optimized to the electrical characteristics of the chosen PV modules and the desired energy production, see Appendix 5B. The SURE HOUSE is projected to produce 12,353 kWh per year to meet 6,157 kWh per year of estimated consumption. Solar modules for the two AC grid-tied sub arrays are mounted on the main roof surface of the SURE HOUSE with a 10 degree tilt angle using a partially-ballasted polyethylene roof mounting system made by Renusol, which is particularly suited to the corrosive salt air of a coastal environment. This method was chosen for its installation simplicity and to limit detrimental roof penetrations. The 10 degree tilt optimizes the energy generated per roof area at a lower price, see Appendix 5A, and ensures that there is minimal wind uplift. DC SOLAR ELECTRIC DOMESTIC HOT WATER The SURE HOUSE’s approach to sustainable and resilient domestic hot water (DHW) consists of a unique, custom engineered DC solar electric hot water system. Employing the use of Advanced Energy’s DC electric PV heater (DCPVH)5 to heat domestic water well beyond the draw temperature, the SURE HOUSE is able to obtain a remarkably high solar fraction of 75% or more. The custom modified 80 gallon Vaughn DHW tank acts as a large solar ‘battery’ that stores heat energy in the form of hot water at almost 150 degrees, harvesting energy when the sun is out for use later in the day or overnight. The system, which uses electricity rather than heated fluid, is distinct from traditional ‘solar thermal’ systems by eliminating the dangers and associated maintenance issues of fluid based systems. By forgoing the use of external fluid loops, overheated solar collectors and pipes are not an issue for the SURE HOUSE system which never needs any yearly or seasonal flushing. In weather conditions where the integrated DCPVH unit cannot produce enough hot water via solar energy alone, the Vaughn hot water tank comes factory made with an AC powered 2.6 COP heat pump and a AC heating coil that serve as back-up heating elements. The DCPVH is powered by a DC array consisting of 10 custom-made Solbian by PVilion 180 watt, monocrystalline, flexible solar modules6. The Solbian modules are directly mounted to the top half of the operable storm shutters on the south façade of the SURE HOUSE. The SURE HOUSE team worked closely with PVillion, a PV system designer specializing in flexible architectural photovoltaics, to design an adhesive system that works with the glass-fiber storm shutter surface in a reliable manner over an extended period. Because this system operates in DC-only mode and never connects to the municipal power grid, the system can continue to create hot water safely and effectively even during grid disruption events. This hot water, and the energy stored within it, could be used for a range of activities including washing and cooking to more elaborate hydronic heating systems as desired. See Appendix 6 for system engineering, sizing and modeling.

14 SOLAR ENERGY↗

Minkowski conformal blocks and the Regge limit for Sachdev-Ye-Kitaev-like models

We discuss scattering in a conformal field theory (CFT) via the conformal partial-wave analysis and the Regge limit. The focus of this paper is on understanding an operator product expansion (OPE) with Minkowski conformal blocks. Starting with a t-channel OPE, it leads to an expansion for an s-channel scattering amplitude in terms of t-channel exchanges. By contrasting with Euclidean conformal blocks we see a precise relationship between conformal blocks in the two limits without preforming an explicit analytic continuation. We discuss a generic feature for a CFT correlation function having singular F (M) (u,v) ~ u –δ , δ > 0, in the limit u → 0 and v → 1. Here, δ = (ℓ eff – 1)/2, with ℓ eff serving as an effective spin and it can be determined through an OPE. In particular, it is bounded from above, ℓ eff ≤ 2, for all CFTs with a gravity dual, and it can be associated with string modes interpolating the graviton in AdS. This singularity is historically referred to as the Pomeron. This bound is nearly saturated by SYK-like effective d = 1 CFT, and its stringy and thermal corrections have piqued current interests. Our analysis has been facilitated by dealing with Wightman functions. We provide a direct treatment in diagonalizing dynamical equations via harmonic analysis over physical scattering regions. As an example these methods are applied to the SYK model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Attention to quantum complexity

The imminent era of error-corrected quantum computing demands robust methods to characterize quantum state complexity from limited, noisy measurements. We introduce the Quantum Attention Network (QuAN), a classical artificial intelligence (AI) framework leveraging attention mechanisms tailored for learning quantum complexity. Inspired by large language models, QuAN treats measurement snapshots as tokens while respecting permutation invariance. Combined with our parameter-efficient miniset self-attention block, this enables QuAN to access high-order moments of bit-string distributions and preferentially attend to less noisy snapshots. We test QuAN across three quantum simulation settings: driven hard-core Bose-Hubbard model, random quantum circuits, and toric code under coherent and incoherent noise. QuAN directly learns entanglement and state complexity growth from experimental computational basis measurements, including complexity growth in random circuits from noisy data. In regimes inaccessible to existing theory, QuAN unveils the complete phase diagram for noisy toric code data as a function of both noise types, highlighting AI’s transformative potential for assisting quantum hardware.

Kim, Hyejin [Cornell Univ., Ithaca, NY (United Sta↗

Codon2Vec v1.0

Background: Codon2Vec is an embedding neural network that predicts 'high' or 'low' gene expression directly from the protein-coding sequences. Embedding neural networks are commonly used for natural language processing (NLP) applications. Analogous to how an English sentence is a string of words, a gene can be thought of as a string of codons. Similar to how NLP neural networks model English sentences as a non-random sequence of words, we considered a coding sequence as a non-random non-overlapping array of codons (k-mers of length = 3). Value Proposition: - Codon2Vec achieved a high median AUC-ROC score of 83.8% when trained and applied to transcriptomic data from 300 fungal species - Unlike Codo2Vec, conventional methods predicting for expression based on codon usage rely on a priori knowledge of optimal codons or a set of reference genes. - Unlike Codon2vec, these methods do not account for the effect of codon order on gene expression. - Codon2Vec neural network bypasses the need for artisanal feature selection step that is necessary for traditional machine learning models.

Wint, Rhondene↗

Development of Software Defined Radio Protocol for Acoustic Communication on Pipes

Nuclear Science Engineering Division at Argonne has been developing a new method of transmitting information via acoustic waves on pipes in a nuclear facility. This method provides the capability to communicate information from within the containment building under the conditions of total power outage following a severe accident. Compared to traditional RF communications, acoustic communications allows for signal transmission across thick concrete barriers, and better information security due to spatial confinement of the signal. Data of interest consists of sensor readings, voice, and images. Transmission of images is most challenging because corruption of the header string might render the reconstructed image unreadable.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Describing hadronization via histories and observables for Monte-Carlo event reweighting

We introduce a novel method for extracting a fragmentation model directly from experimental data without requiring an explicit parametric form, called Histories and Observables for Monte-Carlo Event Reweighting (HOMER), consisting of three steps: the training of a classifier between simulation and data, the inference of single fragmentation weights, and the calculation of the weight for the full hadronization chain. We illustrate the use of HOMER on a simplified hadronization problem, a q\bar{q} q q ‾ string fragmenting into pions, and extract a modified Lund string fragmentation function f(z) f ( z ) . We then demonstrate the use of HOMER on three types of experimental data: (i) binned distributions of high-level observables, (ii) unbinned event-by-event distributions of these observables, and (iii) full particle cloud information. After demonstrating that f(z) f ( z ) can be extracted from data (the inverse of hadronization), we also show that, at least in this limited setup, the fidelity of the extracted f(z) f ( z ) suffers only limited loss when moving from (i) to (ii) to (iii). Public code is available at https://gitlab.com/uchep/mlhad.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Toward distinguishing Dirac from Majorana neutrino mass with gravitational waves

We propose a new method toward distinguishing the Dirac versus Majorana nature of neutrino masses from the spectrum of gravitational waves (GWs) associated with neutrino mass genesis. Motivated by the principle of generating small neutrino masses without tiny Yukawa couplings, we assume generic seesaw mechanisms for both Majorana and Dirac neutrino masses. For Majorana neutrinos, we further assume a spontaneously broken gauged U ( 1 ) B − L symmetry, independently of the type of Majorana seesaw mechanism, which gives a cosmic string induced GW signal flat over a wide range of frequencies. For Dirac neutrinos, we assume the spontaneous breaking of a Z 2 symmetry, the minimal symmetry choice associated with all Dirac seesaw mechanisms, which is softly broken, generating a peaked GW spectrum from the annihilation of the resulting domain walls. In fact, the GW spectra for all types of Dirac seesaws with such a broken Z 2 symmetry are identical, subject to a mild caveat. As an illustrative example, we study the simplest respective type-I seesaw mechanisms, and show that the striking difference in the shapes of the GW spectra can help differentiate between these Dirac and Majorana seesaws, complementing results of neutrinoless double beta decay experiments. We also discuss detailed implications of the recent NANOGrav data for Majorana and Dirac seesaw models. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Non-Semisimple TQFT's and BPS q -Series

We propose and in some cases prove a precise relation between 3-manifold invariants associated with quantum groups at roots of unity and at generic q. Both types of invariants are labeled by extra data which plays an important role in the proposed relation. Bridging the two sides - which until recently were developed independently, using very different methods - opens many new avenues. In one direction, it allows to study (and perhaps even to formulate) q-series invariants labeled by spin c structures in terms of non-semisimple invariants. In the opposite direction, it offers new insights and perspectives on various elements of non-semisimple TQFT's, bringing the latter into one unifying framework with other invariants of knots and 3-manifolds that recently found realization in quantum field theory and in string theory.

3-manifold invariants↗

HDSense: An efficient method for ranking observable sensitivity

Identifying which observables most effectively constrain model parameters can be computationally prohibitive when considering full likelihoods of many correlated observables. This is especially important for, e.g., hadronization models, where high precision is required to interpret the results of collider experiments. We introduce the High-Dimensional Sensitivity (HDSense) score, a computationally efficient metric for ranking observable sets using only one-dimensional histograms. Derived by profiling over unknown correlations in the Fisher information framework, the score balances total information content against redundancy between observables. We apply HDSense to rank a set observables in terms of their constraining power with respect to five parameters of the Lund string model of hadronization implemented in Pythia using simulated leptonic collider events at the $Z$ pole. Validation against machine-learning--based full-likelihood approximations demonstrates that HDSense successfully identifies near-optimal observable subsets. The framework naturally handles data from multiple experiments with different acceptances and incorporates detector effects. While demonstrated on hadronization models, the methodology applies broadly to generic parameter estimation problems where correlations are unknown or difficult to model.

Assi, Benoît [Cincinnati U.] (ORCID:00000003092433↗

Stable vacua with realistic phenomenology and cosmology in heterotic M-theory satisfying Swampland conjectures

We recently described a protocol for computing the potential energy in heterotic M-theory for the dilaton, complex structure and Kähler moduli. This included the leading order non-perturbative contributions to the complex structure, gaugino condensation and worldsheet instantons assuming a hidden sector that contains an anomalous U(1) structure group embedded in E8. In this paper, we elucidate, in detail, the mathematical and computational methods required to utilize this protocol. These methods are then applied to a realistic heterotic M-theory model, the B – L MSSM, whose observable sector is consistent with all particle physics requirements. Within this context, it is shown that the dilaton and universal moduli can be completely stabilized at values compatible with every phenomenological and mathematical constraint — as well as with ΛCDM cosmology. We also show that the heterotic M-theory vacua are consistent with all well-supported Swampland conjectures based on considerations of string theory and quantum gravity, and we discuss the implications of dark energy theorems for compactified theories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Universal Bound on Effective Central Charge and Its Saturation

The effective central charge (denoted by 𝑐 eff ) is a measure of entanglement through a conformal interface, while the transmission coefficient (encoded in the coefficient 𝑐 𝐿⁢𝑅 of the two-point function of the energy-momentum tensor across the interface) is a measure of energy transmission through the interface. It has been pointed out that these two are generally different. In this Letter, we propose the inequalities, 0 ≤ 𝑐 𝐿⁢𝑅 ≤ 𝑐 eff ≤ min⁡(𝑐 𝐿 ,𝑐 𝑅 ). They have the simple but important implication that the amount of energy transmission can never exceed the amount of information transmission. We verify them using the AdS/CFT correspondence, using the perturbation method, and in examples beyond holography. We also show that these inequalities are sharp by constructing a class of interfaces that saturate them.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2021 [Slides]

Our benchmarking method includes bottom-up accounting for all necessary system and projectdevelopment costs incurred when installing residential, commercial, and utility-scale systems, and it models the Q1 2021 costs for such systems, excluding any previous supply agreements or contracts. In general, we attempt to model the typical installation techniques and business operations from an installed-cost perspective, and our benchmarks are national averages. The residential PV-only benchmark and the commercial rooftop PV-only benchmark average costs by inverter type (string inverters, string inverters with direct current [DC] optimizers, and microinverters), weighted by inverter market share. The residential PV-only benchmark is further averaged across small installer and national integrator business models, weighted by market share. All benchmarks include variations—accounting for the differences in size, equipment, and operational use (particularly for storage)—that are currently available in the marketplace. All benchmarks assume nonunionized construction labor; residential and commercial PV systems predominantly use nonunionized labor, and the type of labor required for utility-scale PV systems depends heavily on the development process. All benchmarks assume the use of monofacial monocrystalline silicon PV modules. Benchmarks using cadmium telluride or bifacial modules could result in significantly different results. The data in this annual benchmark report inform the formulation of and track progress toward the U.S. Department of Energy (DOE) Solar Energy Technologies Office’s Government Performance and Reporting Act cost targets.

14 SOLAR ENERGY↗

Quantitative Electroluminescence Imaging Analysis for Performance Estimation of PID-Influenced PV Modules

An empirical method for estimating relative power losses caused by potential-induced degradation (PID) for p-type solar cells and modules using quantitative electroluminescence (EL) analysis (QELA) is presented. First, EL images are corrected for camera- and perspective distortion. The relative power loss map is then calculated from the logarithmic ratio of two EL images, taken either before and after PID degradation or at different applied currents. Only the cell average of the resulting power loss map is evaluated. The highest power loss across each string is averaged to obtain the overall power loss. Consequently, for modules with three strings, three cells are averaged. The resulting power loss depends on the current applied. The conversion to equivalent irradiance allows for comparison of measured and estimated device performance. The analysis of roughly 2000 EL images and related current-voltage (I-V) curves indicates a good agreement between flash-test-measured and performance estimated using QELA. A relative root mean square error of 1-3% can be achieved.

14 SOLAR ENERGY↗

Channel capacity: limitation of entropy rate during cell signal transduction

Cellular signal transduction is mediated through chain activation reactions involving signalling molecules. Information thermodynamics may be a promising approach for quantifying signal transduction. A cell signal is transduced through the signal molecule activation as a step of a signal transduction cascade. In each step, two types of entropy can be defined. First, the signal transduction was defined using thermodynamic entropy production during the chemical activation of signal molecules. Second, the chronology was described as a code string, and the logarithm of the number of signal code strings corresponded to the information entropy. Finally, the total entropy during signal transduction was determined by summing the two entropies. When maximising the total entropy, the total entropy rate per signalling molecule concentration was found to be consistent independently of each transduction step (i.e., signal molecule types). Consequently, the speed limit of the entropy rate can be calculated, providing the capacity, which is an essential property of the signal transduction cascade. The theory introduced here is expected to provide a basic framework for understanding new methods of discovering signal cascades and intracellular signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

De Novo Sequencing of Peptides from Top-Down Tandem Mass Spectra

De novo sequencing of proteins and peptides is one of the most important problems in mass spectrometry-driven proteomics. A variety of methods have been developed to accomplish this task from a set of bottom-up tandem (MS/MS) mass spectra. However, a more recently emerged top-down technology, now gaining more and more popularity, opens new perspectives for protein analysis and characterization, implying a need in efficient algorithms for processing this kind of MS/MS data. Here we describe a method that allows to retrieve from a set of top-down MS/MS spectra long and accurate sequence fragments of the proteins contained in a sample. To this end, we outline a strategy for generating high-quality sequence tags from top-down spectra, and introduce the concept of a T-Bruijn graph by adapting to the case of tags the notion of an A-Bruijn graph widely used in genomics. The output of the proposed approach represents the set of amino acid strings spelled out by optimal paths in the connected components of a T-Bruijn graph. We illustrate its performance on top-down datasets acquired from carbonic anhydrase 2 (CAH2) and the Fab region of alemtuzumab.

Environmental Molecular Sciences Laboratory↗

Efficient 3D Molecular Design with an E(3) Invariant Transformer VAE

This work introduces a three-dimensional (3D) invariant graph-to-string transformer variational autoencoders (VAE) (Vagrant) for generating molecules with accurate density functional theory (DFT)-level properties. Vagrant learns to model the joint probability distribution of a 3D molecular structure and its properties by encoding molecular structures into a 3D-aware latent space. Directed navigation through this latent space implicitly optimizes the 3D structure of a molecule, and the latent embedding can be used to condition a generative transformer to predict the candidate structure as a one-dimensional (1D) sequence. Additionally, we introduce two novel sampling methods that exploit the latent characteristics of a VAE to improve performance. Here, we show that our method outperforms comparable 3D autoregressive and diffusion methods for predicting quantum chemical property values of novel molecules in terms of both sample quality and computational efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗