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At least 1,225 records · Page 68

Results from an Interval Management (IM) Flight Test and Its Potential Benefit to Air Traffic Management Operations

NASA's first Air Traffic Management Technology Demonstration (ATD-1) subproject successfully completed a 19-day flight test of an Interval Management (IM) avionics prototype. The prototype was built based on IM standards, integrated into two test aircraft, and then flown in real-world conditions to determine if the goals of improving aircraft efficiency and airport throughput during high-density arrival operations could be met. The ATD-1 concept of operation integrates advanced arrival scheduling, controller decision support tools, and the IM avionics to enable multiple time-based arrival streams into a high-density terminal airspace. IM contributes by calculating airspeeds that enable an aircraft to achieve a spacing interval behind the preceding aircraft. The IM avionics uses its data (route of flight, position, etc.) and Automatic Dependent Surveillance-Broadcast (ADS-B) state data from the Target aircraft to calculate this airspeed. The flight test demonstrated that the IM avionics prototype met the spacing accuracy design goal for three of the four IM operation types tested. The primary issue requiring attention for future IM work is the high rate of IM speed commands and speed reversals. In total, during this flight test, the IM avionics prototype showed significant promise in contributing to the goals of improving aircraft efficiency and airport throughput.

Baxley, Brian↗

Identification of 2-Hydroxyacyl-CoA Synthases with High Acyloin Condensation Activity for Orthogonal One-Carbon Bioconversion

One-carbon (C1) compounds are emerging as cost-effective and potentially carbon-negative feedstocks for biomanufacturing, which require efficient, versatile metabolic platforms for the synthesis of value-added products. Synthetic formyl-CoA elongation (FORCE) pathways allow diverse product synthesis from C1 compounds via iterative C1 elongation, operating independently from the host metabolism with reduced engineering complexity and improved theoretical yields. However, a major bottleneck was identified as the suboptimal kinetics of the core C1–C1 condensation enzyme, 2-hydroxyacyl-CoA synthase (HACS), catalyzing the acyloin condensation reaction between formaldehyde and formyl-CoA. Furthermore, we used a combinatorial approach of bioprospecting and rational protein engineering to identify multiple HACS variants with significantly improved activities toward C1 substrates. Sequence and structure alignment of the active variants elucidated the key regions for the catalytic function, which were targeted for mutagenesis, leading to improved catalytic efficiency. In parallel, a consecutive round of bioprospecting for homologs with high similarity with active variants revealed a highly active HACS variant exhibiting up to 7-fold improvement in catalytic efficiency (k cat /K M ) and 14-fold improvement in the FORCE pathway flux in vivo compared to the previous reports. Upon further optimization of the downstream pathway, the orthogonal C1-to-product bioconversion system showed a metabolic flux of up to 700 μM glycolate OD –1 h –1 (2.1 mmol gDCW –1 h –1 ) and an industrially relevant glycolate titer, rate, and yield of 5.2 g L –1 (67.8 mM), 0.22 g L –1 h –1 , and 94% carbon yield, respectively.

2-hydroxyacyl-CoA synthase↗

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗

NextGen Flight Deck Surface Trajectory-Based Operations (STBO): Contingency Holds

The purpose of this pilot-in-the-loop taxi simulation was to investigate a NextGen Surface Trajectory-Based Operations (STBO) concept called "contingency holds." The contingency-hold concept parses a taxi route into segments, allowing an air traffic control (ATC) surface traffic management (STM) system to hold an aircraft when necessary for safety. Under nominal conditions, if the intersection or active runway crossing is clear, the hold is removed, allowing the aircraft to continue taxiing without slowing, thus improving taxi efficiency, while minimizing the excessive brake use, fuel burn, and emissions associated with stop-and-go taxi. However, when a potential traffic conflict exists, the hold remains in place as a fail-safe mechanism. In this departure operations simulation, the taxi clearance included a required time of arrival (RTA) to a specified intersection. The flight deck was equipped with speed-guidance avionics to aid the pilot in safely meeting the RTA. On two trials, the contingency hold was not released, and pilots were required to stop. On two trials the contingency hold was released 15 sec prior to the RTA, and on two trials the contingency hold was released 30 sec prior to the RTA. When the hold remained in place, all pilots complied with the hold. Results also showed that when the hold was released at 15-sec or 30-sec prior to the RTA, the 30-sec release allowed pilots to maintain nominal taxi speed, thus supporting continuous traffic flow; whereas, the 15-sec release did not. The contingency-hold concept, with at least a 30-sec release, allows pilots to improve taxiing efficiency by reducing braking, slowing, and stopping, but still maintains safety in that no pilots "busted" the clearance holds. Overall, the evidence suggests that the contingency-hold concept is a viable concept for optimizing efficiency while maintaining safety.

NextGen↗

Aeroelastic Modeling of Elastically Shaped Aircraft Concept via Wing Shaping Control for Drag Reduction

Lightweight aircraft design has received a considerable attention in recent years as a means for improving cruise efficiency. Reducing aircraft weight results in lower lift requirements which directly translate into lower drag, hence reduced engine thrust requirements during cruise. The use of lightweight materials such as advanced composite materials has been adopted by airframe manufacturers in current and future aircraft. Modern lightweight materials can provide less structural rigidity while maintaining load-carrying capacity. As structural flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. Abstract This paper describes a recent aeroelastic modeling effort for an elastically shaped aircraft concept (ESAC). The aircraft model is based on the rigid-body generic transport model (GTM) originally developed at NASA Langley Research Center. The ESAC distinguishes itself from the GTM in that it is equipped with highly flexible wing structures as a weight reduction design feature. More significantly, the wings are outfitted with a novel control effector concept called variable camber continuous trailing edge (VCCTE) flap system for active control of wing aeroelastic deflections to optimize the local angle of attack of wing sections for improved aerodynamic efficiency through cruise drag reduction and lift enhancement during take-off and landing. The VCCTE flap is a multi-functional and aerodynamically efficient device capable of achieving high lift-to-drag ratios. The flap system is comprised of three chordwise segments that form the variable camber feature of the flap and multiple spanwise segments that form a piecewise continuous trailing edge. By configuring the flap camber and trailing edge shape, drag reduction could be achieved. Moreover, some parts of the flap system can be made to have a high frequency response for roll control, gust load alleviation, and aeroservoelastic (ASE) modal suppression control. Abstract The aeroelastic model of the ESAC is based on one-dimensional structural dynamic theory that captures the aeroelastic deformation of a wing structure in a combined motion that involves flapwise bending, chordwise bending, and torsion. The model includes the effect of aircraft propulsion due to wing flexibility which causes the propulsive forces and moments to couple with the wing elastic motion. Engine mass is also accounted in the model. A fuel management model is developed to describe the wing mass change due to fuel usage in the main tank and wing tanks during cruise. Abstract The model computes both static and dynamic responses of the wing structures. The static aeroelastic deflections are used to estimate the effect of wing flexibility on induced drag and the potential drag reduction by the VCCTE flap system. A flutter analysis is conducted to estimate the flutter speed boundary. Gust load alleviation via adaptive control has been recently investigated to address flexibility of aircraft structures. A multi-objective flight control approach is presented for drag reduction control. The approach is based on an optimal control framework using a multi-objective cost function. Future studies will demonstrate the potential benefits of the approach.

Aeroelasticity↗

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗

Experimental test of model predictive control in a variable air volume system

Model predictive control (MPC) has been widely studied as a promising approach for improving energy efficiency and operational flexibility in buildings, yet its real-world performance for commercial variable air volume (VAV) systems remains insufficiently characterized. In particular, the impacts of model mismatch on control robustness, real-time computational burden, and device-level operation are rarely evaluated using long-term field data. Here, this study presents a comprehensive experimental evaluation of MPC applied to a full-scale VAV system in Oak Ridge National Laboratory’s Flexible Research Platform-2 building with constant cooling/heating temperature setpoints and no occupancy. The study offers three key advantages over existing work: (1) it uses a representative building in a full-scale experimental test, capturing realistic system dynamics and complexity; (2) it evaluates a relatively sophisticated MPC formulation using two different optimization solvers (Gurobi and PSO), fully accounting for computational complexity and methodological diversity; and (3) it systematically assesses potential negative impacts on various building devices, benchmark against a well-established baseline, ASHRAE Guideline 36 (G36). To isolate zone- and air-handling-unit–level supervisory control effects, the supply fan was operated with a fixed static pressure setpoint under all strategies, and the trim-and-response static pressure reset in G36 was not enabled. Results show that MPC maintained thermal comfort while improving energy efficiency. Abrupt solar radiation variations degraded performance. Computation times ranged from ∼1 s (Gurobi) to ∼ 70 s (PSO). Compared with G36, MPC achieves 33% energy savings and reduces median reheat coil output by approximately a factor of 5–10 for a representative cooling day under matched weather conditions. However, it increases the maximum discomfort deviation from 0.5 to 1°C and results in a 32% increase in staging frequency. In addition, PSO-based MPC introduced damper oscillations, also affecting actuator longevity.

ASHRAE guideline 36↗

Application of Banking Scoring and Rating for Coherent Risk Measures in Electricity Systems ABSCORES

This project developed a framework for asset and system risk management that can be incorporated into current electricity system operations to improve economic efficiency and establish an Electric Assets Risk Bureau. We leveraged scoring and ratings from banking and financial institutions alongside current optimization methods in dispatching power systems to help system operators and electricity markets schedule resources. This approach is based on the observation that there are major discrepancies between the power scheduled by a system operator and the actual power generated/consumed. These discrepancies—exacerbated by unplanned contingencies (e.g., natural disasters)—are caused by multiple factors, including the different financial, environmental and risk preferences of power producers, consumers, and aggregators. We developed a framework that counteracts two failures in electricity system operations: imperfect information and missing markets for products. The technical approach included five tasks. Tasks 1 and 2 supported the development of risk scores at the asset level with historical data collected for this project. Tasks 3, 4, and 5 incorporated scoring into decision-making at the system level. The proposed effort achieved PERFORM's Program Objectives because the proposed outputs and algorithms do not exist in the electricity industry and are an innovative approach to managing risk. Since the acknowledged need to better assess and act upon risk profiles for grid assets has not been met by the industry, this project will also impact ARPA-E's Mission Areas, including improving energy efficiency and giving the U.S. a technological lead in advanced energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗

Evaluation of Spray and Combustion Models for Simulating Dilute Combustion in a Direct-Injection Spark-Ignition Engine

Dilute combustion in spark-ignition engines has the potential to improve thermal efficiency by mitigating knock and by reducing throttling and wall heat losses. However, ignition and combustion processes can become unstable for dilute operation due to a lowered laminar flame speed, resulting in excessive cycle-to-cycle variability (CCV) of the combustion process. To compensate for the slower combustion in less reactive mixtures, a modified intake port geometry can be employed to generate a strong tumble flow in the cylinder and elevate turbulence levels around the spark plug, thereby promoting a faster transition to turbulent deflagration. Consequently, optimizing combustion chamber geometry and operating strategy is crucial to maximizing the benefits of using dilute combustion with enhanced in-cylinder turbulence across a wide range of operating conditions. Computational fluid dynamics (CFD) simulations can be utilized for virtual engine optimization tasks, but this would require the models to be truly predictive regarding the impact of changes to the engine design and operational parameters.In this study, multicycle large-eddy simulations (LES) are performed for a direct-injection spark-ignition engine to investigate the model performance in predicting engine combustion characteristics with respect to changes in the intake configuration. A tumble plate that blocks the lower part of the intake port inlet is used to vary the tumble. A set of CFD models that have been recently developed are employed, which takes into account the drag of nonspherical droplets, flash-boiling behavior of liquid sprays, spray-wall interaction, surrogate formulation of a research-grade E10 gasoline, and fast chemical kinetic solvers. Simulation results are compared to experimental engine data in terms of cylinder pressure, apparent heat release rate, mass fraction burned timing, and flame images. It is found that LES employing the state-of-the-art CFD models are capable of properly predicting the spray processes and reproducing the measured mean cylinder pressure for the case with the tumble plate. On the other hand, the LES over-predicts the combustion rate during the early combustion stage and under-estimates the CCV, and these discrepancies become larger when the tumble plate is removed.

computational fluid dynamics simulation↗

Development of Two-Phase Dense Fluid Expander for Advanced Cryogenic Air Separation and Low-Grade Heat Recovery

Cryogenic air separation represents the state-of-the-art technology to produce oxygen to feed coal gasification units. Given the maturity of this technology, it is difficult to identify opportunities to improve process efficiency and reduce the cost of the oxygen produced. However, Air Products conducted research and a feasibility investigation into the use of a two-phase (liquid-vapor) dense fluid expander (DFE) to improve the overall efficiency of cryogenic air separation. Demonstration of this novel concept was intended to allow two important process improvements: 1) elimination of the need for the DFE discharge to be single phase 2) expansion of the operating region of expanders in ASU service. Expanding the scope of turboexpander application beyond current application limits and traditional device designs would allow an increase in power recovery, and application of refrigeration and power recovery at new locations in process cycles would also enable the implementation of new process concepts. These new process concepts include power recovery from compression waste heat and refrigeration extraction and power recovery by replacing let-down valves with two-phase DFEs. Considering the maturity of cryogenic air separation, these new process options could represent a step change in power reduction and provide significant savings in operating costs. These new concepts would be particularly well-suited to large-scale oxygen production by cryogenic air separation and would enhance the economics of producing oxygen for use in coal gasification processes. Rotoflow, an Air Products business unit, manufactures dense fluid expanders in Pennsylvania for sites around the world. This project was executed in two phases, which are illustrated in Figure 1 below. Phase 1 consisted of a feasibility investigation of multiple applications of two-phase DFEs. In Phase 2, devices were identified, designed, fabricated and tested to explore the feasibility of commercial applications of DFEs operating in two-phase service. Engineering and testing were performed by personnel in Air Products’ Rotoflow business unit, with coordination with other Air Products business units.

01 COAL, LIGNITE, AND PEAT↗

Monolayer organic thin films as particle-contamination–resistant coatings

Abstract Three organic monolayers coatings were developed and tested for their effectiveness to increase cleaning efficiency of attached microscale particles by air flows. The experiments were performed using silica substrates coated with these organic thin films and subsequently exposed to stainless-steel and silica microparticles as a model of contamination. Laser-induced–damage tests confirmed that the coatings do not affect the laser-induced–damage threshold values. The particle exposure results suggest that although the accumulation of particles is not significantly affected under the experimental conditions used in this work, the coated substrates exhibit significantly improved cleaning efficiency with a gas flow. A size-distribution analysis was conducted to study the adsorption and cleaning efficiency of particles of different sizes. It was observed that larger size (> 5-μm) particles can be removed from coated substrates with almost 100% efficiency. It was also determined that the coatings improve the cleaning efficiency of the smaller particles (≤ 5 μm) by 17% to 30% for the stainless steel metal and 19% to 38% for the silica particles.

36 MATERIALS SCIENCE↗

Assessment of Technologies for Noncryogenic Hybrid Electric Propulsion

The Subsonic Fixed Wing Project of NASA's Fundamental Aeronautics Program is researching aircraft propulsion technologies that will lower noise, emissions, and fuel burn. One promising technology is noncryogenic electric propulsion, which could be either hybrid electric propulsion or turboelectric propulsion. Reducing dependence on the turbine engine would certainly reduce emissions. However, the weight of the electricmotor- related components that would have to be added would adversely impact the benefits of the smaller turbine engine. Therefore, research needs to be done to improve component efficiencies and reduce component weights. This study projects technology improvements expected in the next 15 and 30 years, including motor-related technologies, power electronics, and energy-storage-related technologies. Motor efficiency and power density could be increased through the use of better conductors, insulators, magnets, bearings, structural materials, and thermal management. Energy storage could be accomplished through batteries, flywheels, or supercapacitors, all of which expect significant energy density growth over the next few decades. A first-order approximation of the cumulative effect of each technology improvement shows that motor power density could be improved from 3 hp/lb, the state of the art, to 8 hp/lb in 15 years and 16 hp/lb in 30 years.

Electric Propulsion↗

Improved CO 2 utilization efficiency using membrane carbonation in outdoor raceways

Membrane carbonation, the delivery of CO 2 by diffusion through non-porous hollow fiber membranes, was successfully integrated into outdoor raceways (5.6 m 2 , 900 L) and operated continuously for up to 45 days. Biomass productivity associated with membrane carbonation was similar to using traditional sparging, but the average carbon utilization efficiencies for membrane carbonation was 3-fold higher than for sparging when 100% CO 2 was delivered to both systems. Here, when the pH setpoint was 8.5, growth on ammonium bicarbonate using membrane carbonation achieved a carbon utilization efficiency of 106 ± 45% due to uptake of some carbon from bicarbonate. Using nitrate as the N source had a 78 ± 55% carbon utilization efficiency, due to dissolved inorganic carbon accumulation as the medium alkalinity increased. Lowering the pH setpoint to 8.0 created a carbon-rich environment that decreased the carbon utilization efficiency to 51 ± 27% due to CO 2 off-gassing, but it still was 3-fold higher than with sparging.

54 ENVIRONMENTAL SCIENCES↗

Ab Initio Direct Dynamics

The reactivity and dynamics of molecular systems can be explored computationally by classical trajectory calculations. The traditional approach involves fitting a functional form of a potential energy surface (PES) to the energies from a large number of electronic structure calculations and then integrating numerous trajectories on this fitted PES to model the molecular dynamics. The ever-decreasing cost of computing and continuing advances in computational chemistry software have made it possible to use electronic structure calculations directly in molecular dynamics simulations without first having to construct a fitted PES. In this “on-the-fly” approach, every time the energy and its derivatives are needed for the integration of the equations of motion, they are obtained directly from quantum chemical calculations. This approach started to become practical in the mid-1990s as a result of increased availability of inexpensive computer resources and improved computational chemistry software. The application of direct dynamics calculations has grown rapidly over the last 25 years and would require a lengthy review article. The present Account is limited to some of our contributions to methods development and various applications. To improve the efficiency of direct dynamics calculations, we developed a Hessian-based predictor-corrector algorithm for integrating classical trajectories. Hessian updating made this even more efficient. Furthermore, this approach was also used to improve algorithms for following the steepest descent reaction paths. For larger molecular systems, we developed an extended Lagrangian approach in which the electronic structure is propagated along with the molecular structure. Strong field chemistry is a rapidly growing area, and to improve the accuracy of molecular dynamics in intense laser fields, we included the time-varying electric field in a novel predictor-corrector trajectory integration algorithm. Since intense laser fields can excite and ionize molecules, we extended our studies to include electron dynamics. Specifically, we developed code for time-dependent configuration interaction electron dynamics to simulate strong field ionization by intense laser pulses. Our initial application of ab initio direct dynamics in 1994 was to CH 2 O → H 2 + CO; the calculated vibrational distributions in the products were in very good agreement with experiment. In the intervening years, we have used direct dynamics to explore energy partitioning in various dissociation reactions, unimolecular dissociations yielding three fragments, reactions with branching after the transition state, nonstatistical dynamics of chemically activated molecules, dynamics of molecular fragmentation by intense infrared laser pulses, selective activation of specific dissociation channels by aligned intense infrared laser fields, angular dependence of strong field ionization, and simulation of sequential double ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Auger Recombination Lifetime Scaling for Type I and Quasi-Type II Core/Shell Quantum Dots

Having already achieved near-unity quantum yields, with promising properties for light-emitting diode, lasing, and charge separation applications, colloidal core/shell quantum dots have great technological potential. The shell thickness and band alignment of the shell and core materials are known to influence the efficiency of these devices. In many such applications, improving the efficiency requires a deep understanding of multiexcitonic states. In this paper, we elucidate the shell thickness and band alignment dependencies of the biexciton Auger recombination lifetime for quasi-type II CdSe/CdS and type I CdSe/ZnS core/shell quantum dots. We find that the biexciton Auger recombination lifetime increases with the total nanocrystal volume for quasi-type II CdSe/CdS core/shell quantum dots and is independent of the shell thickness for type I CdSe/ZnS core/shell quantum dots. To perform these calculations and compute Auger recombination lifetimes, we developed a low-scaling approach based on the stochastic resolution of identity. The numerical approach provided a framework for studying the scaling of the biexciton Auger recombination lifetimes in terms of the shell thickness dependencies of the exciton radii, Coulomb couplings, and density of final states in quasi-type II CdSe/CdS and type I CdSe/ZnS core/shell quantum dots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Teacher-student training improves the accuracy and efficiency of machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) are revolutionizing the field of molecular dynamics (MD) simulations. Recent MLIPs have tended towards more complex architectures trained on larger datasets. The resulting increase in computational and memory costs may prohibit the application of these MLIPs to perform large-scale MD simulations. Herein, we present a teacher-student training framework in which the latent knowledge from the teacher (atomic energies) is used to augment the students' training. We show that the light-weight student MLIPs have faster MD speeds at a fraction of the memory footprint compared to the teacher models. Remarkably, the student models can even surpass the accuracy of the teachers, even though both are trained on the same quantum chemistry dataset. Our work highlights a practical method for MLIPs to reduce the resources required for large-scale MD simulations.

36 MATERIALS SCIENCE↗