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At least 1,099 records · Page 61

Coupling of organic cation and inorganic lattice in methylammonium lead halide perovskites: Insights into a pressure-induced isostructural phase transition

Organic-inorganic hybrid metal-halide perovskite (OIHP) materials provide a tunable platform for engineering their optoelectronic properties. Although several high-pressure studies have been conducted from the OIHP family of single crystals and films, the exact nature of the dynamic coupling of the CH 3 NH 3 (MA) cation with the octahedral lattice framework and the mechanisms responsible for the structural phase transformation under pressure are not well captured. By combined photoluminescence (PL), synchrotron-based x-ray diffraction, and Raman-scattering studies as a function of pressure from methylammonium lead bromide (MAPbBr 3 ), we shed light on an isostructural phase transition due to the coupling of the MA cation and the PbBr 6 lattice through hydrogen bonding. The sharp discontinuities at ~ 1 GPa and ~ 3 GPa in the PL peak positions correlate with the structural changes observed in high-pressure XRD and Raman-scattering studies. The electronic band edge as a function of pressure is calculated within density-functional theory. The PL peak position, intensity and width of the excitonic peak show significant changes at 2 GPa, which corroborate the changes observed in high-pressure Raman-scattering studies. The frequencies of the lattice modes and the C-H/N-H bending and stretching modes of the MA cation show anomalous changes and other nuances at 2 GPa. The suppression of rotational and orientational disorder of the organic moiety is initiated at 2 GPa and the ordering is completed by 3.0 GPa, leading to an order-disorder type cubic II (Im$\overline{3}$) to orthorhombic ( Pnma ) phase transition. Along with the revelation of an isostructural transformation at 2 GPa, this paper highlights the impact of molecular vibrations on the electronic properties of MAPbBr 3 under pressure.

36 MATERIALS SCIENCE↗

Study of microgrid resilience through co-simulation of power system dynamics and communication systems

The interdependence of power and communication systems in smart grid technologies is acknowledged, but difficult to quantify. Communication systems can be essential to maintaining stability in microgrids that are islanded due to extreme events. Though many power system studies assume the presence of communication networks, detailed modeling of power and communication systems for dynamic studies of microgrids is rare. The work presented in this paper develops a framework for power and communication system co-simulation to study the impact of communications system on microgrid stability. An operational use case is examined where a battery energy storage system operates to offset the loss of generation in an islanded microgrid. The framework is evaluated for different communication technologies, network structures, and communication media.

Thekkumparambath Mana, Priya↗

Taming the terminological tempest in invasion science

ABSTRACT Standardised terminology in science is important for clarity of interpretation and communication. In invasion science – a dynamic and rapidly evolving discipline – the proliferation of technical terminology has lacked a standardised framework for its development. The result is a convoluted and inconsistent usage of terminology, with various discrepancies in descriptions of damage and interventions. A standardised framework is therefore needed for a clear, universally applicable, and consistent terminology to promote more effective communication across researchers, stakeholders, and policymakers. Inconsistencies in terminology stem from the exponential increase in scientific publications on the patterns and processes of biological invasions authored by experts from various disciplines and countries since the 1990s, as well as publications by legislators and policymakers focusing on practical applications, regulations, and management of resources. Aligning and standardising terminology across stakeholders remains a challenge in invasion science. Here, we review and evaluate the multiple terms used in invasion science (e.g. ‘non‐native’, ‘alien’, ‘invasive’ or ‘invader’, ‘exotic’, ‘non‐indigenous’, ‘naturalised’, ‘pest’) to propose a more simplified and standardised terminology. The streamlined framework we propose and translate into 28 other languages is based on the terms ( i ) ‘non‐native’, denoting species transported beyond their natural biogeographic range, ( ii ) ‘established non‐native’, i.e. those non‐native species that have established self‐sustaining populations in their new location(s) in the wild, and ( iii ) ‘invasive non‐native’ – populations of established non‐native species that have recently spread or are spreading rapidly in their invaded range actively or passively with or without human mediation. We also highlight the importance of conceptualising ‘spread’ for classifying invasiveness and ‘impact’ for management. Finally, we propose a protocol for classifying populations based on ( i ) dispersal mechanism, ( ii ) species origin, ( iii ) population status, and ( iv ) impact. Collectively and without introducing new terminology, the framework that we present aims to facilitate effective communication and collaboration in invasion science and management of non‐native species.

Soto, Ismael↗

A tissue‐resolved, network‐based transcriptomic framework for abiotic stress responses in sorghum

Developing climate‐resilient crops requires a detailed understanding of stress‐induced gene expression dynamics, as maladaptive responses can compromise their productivity and survival. Sorghum, a globally important cereal with exceptional tolerance to multiple abiotic stresses, provides a powerful system for investigating these dynamics. However, how stress type, tissue specificity, and temporal progression jointly shape transcriptomic responses in crops remains poorly understood. Here, we present a comparative, time‐resolved transcriptomic atlas of sorghum responses to drought, heat, and salinity stress across shoot and root tissues. Integrative analyses revealed that tissue specificity is the dominant determinant of abiotic stress‐induced gene reprogramming across all three stresses. Building on these global comparisons, we focused on heat stress, as it elicited the most coherent and pronounced transcriptional and regulatory responses, enabling deeper network‐level interrogation. Co‐expression network analysis identified tissue‐specific modules enriched for phytohormone‐responsive genes, while gene regulatory network (GRN) mapping and cistrome analyses uncovered transcription factors (TFs) controlling key hub genes within these modules. Together, this study provides a foundational transcriptomic and network‐based resource for dissecting the regulatory architecture of abiotic stress responses in sorghum and offers prioritized candidates for future functional validation and engineering of climate‐resilient crops.

abiotic stress↗

Plant Cell Biology International Meeting 2022

There is a strong need to develop the knowledge base that will enable the rational design of improved crop species for sustainable agriculture and biomass production. To attain this goal, researchers must learn how plant cells integrate metabolism and cellular dynamics during growth and in response to environmental challenges. Meeting these goals require data sharing and the development and training of faculty, post-doctoral fellows, graduate and undergraduate students in state-of-the-art quantitative integrative cell biology methods. The inaugural Plant Cell Biology International (PCBI) meeting capitalized on the interaction between two well-established plant cell biology communities across the Atlantic, the Midwest Plant Cell Dynamics (PCD) and the European Network for Plant Endomembrane Research (ENPER) and provided a framework to meet these goals. The conference took place in person successfully during August 1-5th 2022 in Crete, Greece. The conference offered opportunities for undergraduate and graduate students, postdocs, young investigators across the globe to present their results and interact across different disciplines. The conference provided an open and inclusive forum for oral presentations that allowed all labs to share research results. It was attended over 80 % by students, postdocs and young investigators. Workshops on best practices for image acquisition and processing pipelines, publication guidelines by scientific journal editors, professional development and well-being benefited the participants at large. Overall, this was the inaugural joint Plant Cell Biology International conference that for the first time officially brought together plant cell biologists to discuss opportunities and challenges in the field to gain a mechanistic understanding of complex biological processes and advance sustainable agriculture. Due to its success, it was rescheduled for 2025 in Crete, to continue strengthening the plant cell biology community and exchanging knowledge and expertise across the globe.

59 BASIC BIOLOGICAL SCIENCES↗

Summary of Multiphysics Modeling for Sublimation Mass Transfer

This report summarizes the effort to develop a multiphysics modeling framework for sublimation mass transfer processes. The aim of the project was to develop a multiphysics code capable of predicting phase change between solid and gas in a closed container, and the movement of material within such a container when exposed to various exterior environmental conditions. Two modeling frameworks were developed towards this aim: one with a high-fidelity computational fluid dynamics (CFD) structure, and the other as a fast reduced-order model. Ultimately, both attempts were unsuccessful due to instabilities in the code and physical processes for which there is no adequate numerical representation. Both modeling attempts are briefly detailed before providing a brief survey of recent updates in the literature, and a recommendation for future work on this subject.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy Technology Innovation Partnership Project Strategic Energy Plan for Washington County, Maine

This Strategic Energy Plan (SEP) for Washington County, Maine was developed through the U.S. Department of Energy's Energy Technology Innovation Partnership Project (ETIPP) to address local challenges related to electricity reliability, affordability, and safety. Grounded in a "relational infrastructure" approach, the plan recognizes that improved energy outcomes depend not only on physical grid investments but also on strengthened coordination and trust between utilities and communities. Using utility-provided reliability data, public datasets, and community input, the plan identifies key risks, including vegetation-related outages, high energy burden, and vulnerability among elderly and medically dependent populations. The SEP establishes three priority areas: hazard mitigation for energy infrastructure, outage safety and emergency readiness, and energy assistance and thermal safety. It outlines community-driven actions designed to complement utility-led system improvements, including targeted outreach, municipal coordination, and expanded access to energy programs. The plan also situates local conditions within broader state policy, market dynamics, and funding opportunities. Intended as a living document, this SEP provides a scalable framework for collaborative action to improve resilience, safety, and affordability in rural energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows

The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.

high pressure reverse osmosis↗

IRIS: Exploring Performance Scaling of the Intelligent Runtime System and its Dynamic Scheduling Policies

High-Performance Computing is becoming increasingly heterogeneous, relying on a diverse mix of hardware to achieve good performance. Paradoxically, current drivers and frameworks for these devices typically require separate languages and implementations for each vendor. Furthermore, there are few tools and little support to schedule codes between these devices in a truly heterogeneous manner-partly because of this fragmentation between vendors and the languages each supports. To overcome both limitations, the Intelligent Runtime System (IRIS) was developed. It allows a common task abstraction to automatically be shared among contemporary vendors and is run from a single host-side API. At runtime, IRIS queries the host system and registers which frameworks and drivers are available, these determine which kernels can be used by the scheduler-CPUs via OpenMP, Nvidia GPUs (CUDA), AMD GPUs (HIP), and Intel and Xilinx FPGAs with OpenCL. IRIS enables tasks to be scheduled to any heterogeneous device and resolves to the appropriate kernel binary at runtimeit only uses the devices supported by the system on which it is run. IRIS supports single-task and graph-based expressions of dependencies of tasks. Additionally, IRIS features a range of dynamic scheduling policies, allowing complex chains of tasks and interactions to be executed, relieving the programmer/user from considering the system to assign tasks to devices optimally. This paper presents the peak performance attainable by IRIS over a range of systems-each with different numbers and types of accelerator devices, it highlights the flexibility of IRIS since these devices are truly heterogeneous, relying on different backends (drivers, frameworks, and languages) which historically required unique implementations to utilize them. We then use this peak performance as a baseline to compare increasingly complex chains of tasks (with increasingly complex task dependencies) and evaluate how IRIS copes. Finally, we consider the performance of different IRIS scheduling policies on this range of task graphs.

Johnston, Beau↗

Ligand efficacy shifts a nuclear receptor conformational ensemble between transcriptionally active and repressive states

Abstract Nuclear receptors (NRs) are thought to dynamically alternate between transcriptionally active and repressive conformations, which are stabilized upon ligand binding. Most NR ligand series exhibit limited bias, primarily consisting of transcriptionally active agonists or neutral antagonists, but not repressive inverse agonists—a limitation that restricts understanding of the functional NR conformational ensemble. Here, we report a NR ligand series for peroxisome proliferator-activated receptor gamma (PPARγ) that spans a pharmacological spectrum from repression (inverse agonism) to activation (agonism) where subtle structural modifications switch compound activity. While crystal structures provide snapshots of the fully repressive state, NMR spectroscopy and conformation-activity relationship analysis reveals that compounds within the series shift the PPARγ conformational ensemble between transcriptionally active and repressive conformations that are natively populated in the apo/ligand-free ensemble. Our findings reveal a molecular framework for minimal chemical modifications that enhance PPARγ inverse agonism and elucidate their influence on the dynamic PPARγ conformational ensemble.

Science & Technology - Other Topics↗

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗

Quantum criticality and topology in non-equilibrium systems

A key goal of condensed matter physics research is to identify new phases of matter, and to understand the universal features of the phase transitions between them. In the past decade, physicists have uncovered a wealth of new phases with interesting surface properties, exemplified by the theoretical prediction and subsequent experimental discovery of topological insulators and superconductors. Traditional condensed matter systems are usually in a thermal equilibrium state and typically at very low temperature. Very recently, experimental advances have sparked interest in the non-equilibrium setting. Non-equilibrium systems can host new phases and phenomena with no equilibrium counterpart, and could also enable robust ways to build quantum memory devices to store and manipulate quantum information in a coherent manner. These phases and phenomena are inherently “dynamical”: they are described not by changes in the arrangement or structure of the constituent particles, but instead marked by sharp distinctions in how the particles move and exchange energy or quantum information. The discovery of robust non-equilibrium phases raises many fundamental questions: Can we develop a systematic theory of states of matter and of dynamical transitions between such states? How can such states be realized and probed experimentally? The main goal of this project was to explore the emergence of topological phases and quantum criticality (two cornerstones of modern condensed matter physics in equilibrium) in such non-equilibrium quantum systems. Specific goals included (1) using tensor networks to efficiently represent non-equilibrium states of matter and their phase transitions; (2) studying and designing new probes for periodically driven systems; and (3) developing analytic and numerical tools to analyze non-equilibrium topological phase transitions. Advances in these directions were achieved using novel techniques appropriate to study the non-equilibrium dynamics in many-body quantum systems combining strong interactions and randomness. Taken together, these results provide a new conceptual framework for understanding the emergence of quantum critical and topological properties in quantum systems far from thermal equilibrium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

All-Inorganic Open-Framework Chalcogenides, A 3 Ga 5 S 9 · x H 2 O ( A = Rb and Cs), Exhibiting Ultrafast Uranyl Remediation and Illustrating a Novel Post-Synthetic Preparation of Open-Framework Oxychalcogenides

Fast and effective uranyl sequestration is of interest to the nuclear industry. Recently layered chalcogenide materials have demonstrated fast, selective, and efficient sorption properties towards uranyl cations and the development and investigation of new types of chalcogenide materials continues to be of interest and represents an intriguing option for uranyl remediation. Three new all-inorganic A 3 Ga 5 S 9 ·xH 2 O (A = Rb, Rb/Cs, and Cs) open-framework chalcogenides were obtained via an in-situ alkali carbonate to alkali sulfide conversion process achieved under mild hydrothermal conditions. The structures of the all-inorganic open framework chalcogenides consist of a 2-fold interpenetrated diamond-like 3D framework containing pseudo-T 3 [Ga 10 S 20 ] 10– supertetrahedra. 48% of the structural volume is occupied by A + cations and water species, as established by single-crystal X-ray diffraction (SCXRD), infrared (IR) and energy-dispersive (EDS) spectroscopies. The dynamic nature of the A + cations and water molecules within the pores was investigated via single crystal X-ray diffraction as well as by IR spectroscopy monitored H 2 O to D 2 O exchange experiments. Framework stability was probed with post-synthetic treatment of A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples in acidic solutions that resulted in the formation of the oxysulfide (A/H) 3 Ga 5 S 9–y O y ·xH 2 O (A = Rb and Cs; y = 0–1), as shown by SCXRD and IR. Ion-exchange studies on A 3 Ga 5 S 9 ·xH 2 O (A = Rb and Cs) samples were carried out utilizing a uranyl acetate solution. The presence of the UO 2 2+ species in the ion-exchanged product was supported by IR and EDS spectroscopies. Batch method ion-exchange experiments on Cs 3 Ga 5 S 9 ·xH 2 O powder demonstrated fast kinetics with 95% uranyl removal from the uranyl acetate solution during the first minute, a maximum uranyl uptake capacity of 15mg/g, and the subsequent elution of uranyl species with KCl solution. Furthermore, the porous and dynamic nature of the A 3 Ga 5 S 9 ·xH 2 O framework coupled with effective UO 2 2+ ···S 2– bonding interactions makes it a good potential sorbent for uranyl remediation from aqueous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracy

We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel method and Bayesian linear regression to compute the free energy, atomic forces, and pressure, in conjunction with a linear regression model between the internal and free energies to compute the internal energy, with all training data generated from Kohn–Sham density functional theory (DFT). We verify the accuracy of the formalism by comparing the Hugoniot for carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that Kohn–Sham calculations for the Hugoniot can be accelerated by up to two orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the Hugoniots of 14 materials in the FPEOS database, comprising 9 single elements and 5 compounds, between temperatures of 10 kK and 2 MK. We find good agreement with first principles results in the literature while providing tighter error bars. In addition, we confirm that the inter-element interaction in compounds decreases with temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A level-of-details framework for representing occupant behavior in agent-based models

We report agent-based modeling is an advanced computational technique capable of representing complex and dynamic processes of human behavior in building performance simulation. Though the agent-based approach supports diverse applications concerning human behavior modeling within the built environment, there is no consensus on the optimal amount of information or level of granularity needed for occupant information representation. This paper attempts to formalize the level of details (LoD) needed for occupant behavior representation in agent-based environments. A novel framework, grounded on the concept of LoD, is proposed to select the required details in representing occupants in agent-based models. Ten attributes related to occupants' presence, movement, behavioral processes, and repertoire are considered to define the LoD. The framework identifies use case parameters as the guiding principle and allows a hybrid approach for selecting varying degrees of occupant attributes to serve the purpose of simulation. A discussion on the pertinence of different occupant behavior LoDs in relation to the desired objective and simulation context is also presented. The study intends to support the occupant behavior research by advancing agent-based occupant modeling in building performance simulation.

42 ENGINEERING↗

Control of solvent adsorption in porous liquids through solvent-solvent interactions

Type 3 Porous Liquids (PLs) are a new class of materials that offer transformative potential for gas capture and utilization. These PLs are comprised of a bulky solvent with a suspended empty nanoporous material that enables selective and high-capacity capture from dilute and complex gas steams. The relationship between the nanoporous material, the structure of the solvent molecules, and the time dependence of solvent adsorption into the nanoporous material governs long term adsorption properties. Herein, molecular dynamics (MD) calculations evaluated the solvent dynamics of nine neat solvents with a broad range of chemical identities and experimental density measurements probed the time-dependent adsorption of these solvents into the ZIF-8 metal-organic frameworks (MOFs) to form PL dispersions over three weeks. Two of the nine dispersion, using glyceryl triacetate and 2’-hydroxyacetopheneone as solvents, presented sufficiently low solvent infiltration—characterized by solvent adsorption less than 40% of the ZIF-8 pore volume—to be viable as PLs. The experimental solvent adsorption data for ZIF-8 dispersed in the four aromatic solvents (acetophenone, methylbenzoate, 2-isopropylphenol, and 2’-hydroxyacetophenone) was fit to a kinetic model to quantify rate of solvent adsorption into ZIF-8. The rates of adsorption of these four similar-sized solvents demonstrated that solvent adsorption is slowed and limited by solvent clustering dynamics that are, in turn, driven by intermolecular hydrogen bonding. Ultimately, experimental solvent sorption measurements indicated that glyceryl triacetate and 2’-hydroxyacetophenone with ZIF-8 formed PLs with the most stable porosity and the greatest potential for gas capture. In conclusion, the combined experimental-computational materials exploration framework used here reveals a novel relationship between molecular scale solvent dynamics and macroscale solvent adsorption kinetics critical for the discovery and rapid evaluation of Type 3 PL compositions.

Hydrogen bonding↗

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗

Sim2Real Autonomous Robotic Exploration [Poster]

Autonomous robots offer promising solutions for exploration in environments that are inaccessible or hazardous to humans. Despite this, physical training of such robots is often constrained by safety risks, high cost or limited accessibility. This project presents an end-to-end simulation to reality pipeline leveraging Nvidia Isaac Sim and Boston Dynamics' Spot to enable autonomous navigation in indoor environments. A reinforcement learning policy is first trained using Nvidia Isaac Lab to establish Spot's locomotion pattern. Virtual LiDAR sensors are then integrated to perform SLAM-based navigation using simulated odometry. Finally, the simulated navigation scheme is transferred to a physical Spot robot to inspect and record images of a real-world room by repeating the learnt trajectory. The proposed framework highlights the potential of scalable training in simulation and reliable deployment in physical environments. Future directions include dynamic trajectory generation in unseen and challenging environments and integration of environmental sensing like temperature, radiation or humidity via sensor and material simulation.

97 - MATHEMATICS AND COMPUTING↗