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DOE OSTI2025

Titanium nitride prepared by the urea-glass synthesis gives an active electrocatalyst for the oxygen reduction reaction

Rock-salt-structured titanium nitride (TiN) has emerged as a leading earth-abundant electrocatalyst for the oxygen reduction reaction (ORR). We compare TiN prepared in three ways starting from urea: the urea–glass method, by a direct reaction between urea and titanium(IV) chloride, and through a discrete monomeric complex. In the urea-glass route, a new-found [Ti 4 (µ-O) 6 (OC(NH 2 ) 2 ) 12 ] 4+ oxo-bridged titanium–urea precursor can be synthesized in a single-pot reaction at room temperature starting from titanium(IV) chloride, urea, and ethanol with a urea-to-titanium ratio of 6. Subsequent annealing of the polymeric gel that results at 750 °C in an N 2 atmosphere yields phase-pure, TiN particles on the 100 µm size scale. TiN can be deposited as an ink with PiperlON®anion exchange dispersion onto a glassy carbon rotating disk electrode (RDE), and of the three synthesis methods, the urea-glass method gives the most active ORR catalyst. The onset potential for ORR activity is −131 mV vs. Hg/HgO, and Koutecký–Levich analysis of linear-sweep voltammetry recorded at varying rotation rates supports a two-electron reduction pathway to H 2 O 2 , with a rate constant of 0.0172 cm s −1 . The higher activity is ascribed to a more oxygen-rich surface—boh defect sites and active oxygen species—afforeded by the oxo-bridged precursor, corrorborated by X-ray photoelectron spectroscopy (XPS) analysis.

Xie, Wanrui [University of Michigan, Ann Arbor, MI↗

DOE OSTI2025

Data-driven multi-element substitution of TiFe alloys for tunable thermodynamics and enhanced activation behaviour for hydrogen storage

Due to their high volumetric hydrogen storage capacity under moderate storage conditions, TiFe alloys have been widely investigated as candidates for practical solid-state hydrogen storage. Partially substituting Ti or Fe sites can improve the key characteristics of TiFe alloys, such as the first hydrogen absorption step (activation) and the equilibrium hydrogen pressure (thermodynamic properties). However, the selection of substitution elements has heavily relied on intuition and trial-and-error. Also, conventional substitution strategies have mainly focused on single-element substitution within the TiFe alloy, limiting the design space and tunability for target applications. Here, to address this limitation, we report a multi-element substitution strategy motivated by an efficient, data-driven machine learning (ML) approach combined with corroborating density functional theory (DFT) calculations. Our models successfully predict experimentally measured hydride stability in five selected alloys using only compositional descriptors. Most importantly, the multi-element substitution leads to enhanced activation properties compared to pure TiFe, achieving near room-temperature activation behaviour. This work provides a method for on-demand tuning of hydrogen storage and activation properties, which may have broad implications for data-driven discovery of energy storage materials.

Cho, YongJun [Korea Advanced Institute Science and↗

DOE OSTI2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗

DOE OSTI2024

Electric fields imbue enzyme reactivity by aligning active site fragment orbitals

It is broadly recognized that intramolecular electric fields, produced by the protein scaffold and acting on the active site, facilitate enzymatic catalysis. This field effect can be described by several theoretical models, each of which is intuitive to varying degrees. In this contribution, we show that a fundamental effect of electric fields is to generate electrostatic potentials that facilitate the energetic alignment of reactant frontier orbitals. We apply this model to demystify the impact of electric fields on high-valent iron–oxo heme proteins: catalases, peroxidases, and peroxygenases/monooxygenases. Specifically, we show that this model easily accounts for the observed field-induced changes to the spin distribution within peroxidase active sites and explains the transition between epoxidation and hydroxylation pathways seen in Cytochrome P450 active site models. Thus, for the intuitive interpretation of the chemical effect of the field, the strategy involves analyzing the response of the orbitals of active site fragments, and their energetic alignment. We note that the energy difference between fragment orbitals involved in charge redistribution acts as a measure for the chemical hardness/softness of the reactive complex. This measure, and its sensitivity to electric fields, offers a single parameter model from which to quantitatively assess the effects of electric fields on reactivity and selectivity. Thus, the model provides an additional perspective to describe electrostatic preorganization and offers ways for its manipulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

In vitro maturation of fully active [FeFe]-hydrogenase in a defined system including the iron carrier NfuA

The [FeFe]-hydrogenase employs an active-site 6Fe H-cluster to catalyze the reversible reduction of protons to H 2 . A [4Fe-4S] subcluster of the H-cluster is synthesized by housekeeping iron-sulfur cluster assembly machinery, and then dedicated hydrogenase maturation enzymes, together with components of the glycine cleavage system, build and deliver a [2Fe] subcluster to generate the full H-cluster. Here, we report that theEscherichia coliiron-sulfur carrier protein NfuA supports in vitro maturation of fully active [FeFe]-hydrogenase, with H 2 production rates comparable to that of the in vivo-maturedChlamydomonas reinhardtii[FeFe]-hydrogenase (CrHydA). Inclusion of NfuA in the in vitro maturation process improves its efficacy by delivering the iron essential for formation of the [Fe II (cys)(CN)(CO) 2 ] – synthon at the dangler iron site of the HydG auxiliary cluster. NfuA serves an additional role in reconstituting and maintaining the catalytically essential iron-sulfur clusters on the maturase enzymes HydE, HydF, and HydG. Further inclusion of a high CO affinity myoglobin variant (Mb H64L ) sequesters free CO generated during the maturation process, minimizing formation of the CO-inhibited H ox -CO enzyme state, significantly increasing hydrogenase activity. The addition of NfuA and Mb H64L to the fully defined maturation system thus results in an in vitro [FeFe]-hydrogenase maturation system that generates highly active enzyme while providing insights into factors important to in vivo maturation.

Science & Technology - Other Topics↗

DOE OSTI2025

Genomic and transcriptomic characterization of carbohydrate-active enzymes in the anaerobic fungus Neocallimastix cameroonii var. constans

Anaerobic gut fungi effectively degrade lignocellulose in the guts of large herbivores, but there remain a limited number of isolated, publicly available, and sequenced strains that impede our understanding of the role of anaerobic fungi within microbial communities. We isolated and characterized a new fungal isolate, Neocallimastix cameroonii var. constans, providing a transcriptomic and genomic understanding of its ability to degrade diverse carbohydrates. This anaerobic fungal strain was stably cultivated for multiple years in vitro among members of an initial enrichment microbial community derived from goat feces, and it demonstrated the ability to pair with other microbial members, namely, archaeal methanogens to produce methane from lignocellulose. Genomic analysis revealed a higher number of predicted carbohydrate-active enzymes encoded in the N. cameroonii var. constans genome compared to most other sequenced anaerobic fungi. The carbohydrate-active enzyme profile for this isolate contained 660 glycoside hydrolases, 160 carbohydrate esterases, 194 glycosyltransferases, and 85 polysaccharide lyases. Differential gene expression analysis showed the upregulation of thousands of genes (including predicted carbohydrate-active enzymes) when N. cameroonii var. constans was grown on lignocellulose (reed canary grass) compared to less complex substrates, such as cellulose (filter paper), cellobiose, and glucose. AlphaFold was used to predict functions of transcriptionally active yet poorly annotated genes, revealing feruloyl esterases that likely play an important role in lignocellulose degradation by anaerobic fungi. The combination of this strain's genomic and transcriptomic characterization, omics-informed structural prediction, and robustness in microbial co-culture make it a well-suited platform to conduct future investigations into bioprocessing and enzyme discovery.

CAZymes↗

DOE OSTI2025

Antimicrobial activity of peptoids against Metallo-β-lactamase-producing Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa , and other WHO priority pathogens, including Candida auris

Abstract Aims The World Health Organization has identified ESKAPE bacteria and Candida auris as priority pathogens, emphasizing an urgent need for novel antimicrobials to combat them. This study aimed to explore the therapeutic potential of antimicrobial peptidomimetics, specifically peptoids with sequence-specific N-substituted glycines, against ESKAPEE pathogens, including metallo-β-lactamase (MBL) producers, as well as C. auris strains. Methods and results This study evaluated activity of the peptoids against the multidrug-resistant priority pathogens. The peptoid TM8 (with an N-decyl alkyl chain) demonstrated a geometric mean minimum inhibitory concentration (MIC) of 7.8 μg ml−1 against MBL-producing bacteria, and 5.5 μg ml−1 against C. auris. TM8 showed synergy with ciprofloxacin, enhancing its effectiveness 4-fold against NDM-1-producing Klebsiella pneumoniae. No antagonism was seen when TM8 was used with either conventional antibiotics or antifungals. Peptoids that had therapeutic indices below 3 were generally more hydrophobic, due to either alkyl chains or bromine. Scanning electron microscopy and live-dead staining assay on peptoid-treated C. auris confirmed morphological changes and killing activity, respectively. Furthermore, the peptoid could effectively inhibit biofilm formation by C. auris. Conclusion Peptoids demonstrated antibacterial activity against ESKAPEE, particularly against MBL-producing Gram-negative bacteria. Additionally, they exhibited antifungal and anti-biofilm activities against C. auris strains.

Biotechnology & Applied Microbiology↗

DOE OSTI2026

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗

DOE OSTI2026

Secondary-Side Active Rectifier Synchronization and Control in LCC-LC Compensated Inductive Power Transfer Systems

This paper proposes a communication-less synchronization and output power control strategy for LCC-LC compensated inductive power transfer systems with a secondaryside active rectifier. By replacing the passive rectifier with an active bridge, the proposed architecture eliminates the need for a separate secondary-side DC-DC converter and enables direct regulation of battery power. The key challenge in such a system is achieving robust synchronization of the secondary active bridge with the primary inverter without access to primary-side signals. To address this issue, the secondary-side variables are analyzed and the current through the secondary series inductor is identified as a load-independent synchronization variable with a fixed phase relationship to the primary excitation. A fixed-frequency second order generalized (SOGI)-based phase locked loop (PLL) is used to estimate the switching phase and frequency, and a phase-shift-based output power controller is developed using a phasor-transformer model of the active bridges. A modified control formulation is further introduced to remove phase-dependent loop-gain variation and simplify controller design. Simulation results validate the proposed method under both fixed and varying switching-frequency conditions, demonstrating successful frequency tracking from 82 kHz to 88 kHz and accurate output power regulation over a wide operating range. The proposed method offers a compact and effective solution for high-power IPT systems by enabling secondary-side synchronization and control without wireless communication or an additional DC-DC conversion stage.

Fernandes, Arnold Anthony [ORNL] (ORCID:0009000631↗

DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗

DOE OSTI2026

Elongation Factor Tu Acts as a Chaperone to Activate an Antibacterial RNase Toxin

Many Gram-negative bacterial species use contact-dependent growth inhibition (CDI) systems to deliver toxic proteins into neighboring competitors. CDI + strains deploy CdiA effector proteins, which translocate their C-terminal toxin (CT) domains into target bacteria through a receptor-mediated delivery pathway. To protect against auto-intoxication, CDI + bacteria also produce CdiI immunity proteins that neutralize CT toxin activity. Here, we present the crystal structure of the CT·CdiI O32:H37 complex from Escherichia coli O32:H37. CT O32:H37 adopts the same fold as the tRNase domain of colicin D, and the nucleases share similar catalytic centers. However, unlike colicin D, which cleaves the anticodon loops of tRNA Arg isoacceptors, CT O32:H37 exhibits nonspecific RNase activity. Notably, we find that endogenous elongation factor Tu (EF-Tu) co-purifies with the over-produced CT·CdiI O32:H37 complex. Although EF-Tu does not bind stably to CT O32:H37 in the absence of CdiI O32:H37 , the translation factor is required for toxic RNase activity in vitro. AlphaFold 3 modeling and site-directed mutagenesis indicate that CT O32:H37 interacts with the N-terminal GTPase domain of EF-Tu. EF-Tu appears to stabilize residue Trp52 within the hydrophobic core of the toxin, which in turn supports the RNase active site through an unusual hydrogen-bonding interaction with the catalytic His67 residue. Furthermore, EF-Tu is hijacked as an essential co-factor to organize the toxin's catalytic center.

Nhan, Dinh Quan [University of California, Santa B↗

DOE OSTI2024

Surface molecular pump enables ultrahigh catalyst activity

The performance of electrocatalysts is critical for renewable energy technologies. While the electrocatalytic activity can be modulated through structural and compositional engineering following the Sabatier principle, the insufficiently explored catalyst-electrolyte interface is promising to promote microkinetic processes such as physisorption and desorption. By combining experimental designs and molecular dynamics simulations with explicit solvent in high accuracy, we demonstrated that dimethylformamide can work as an effective surface molecular pump to facilitate the entrapment of oxygen and outflux of water. Dimethylformamide disrupts the interfacial network of hydrogen bonds, leading to enhanced activity of the oxygen reduction reaction by a factor of 2 to 3. This strategy works generally for platinum-alloy catalysts, and we introduce an optimal model PtCuNi catalyst with an unprecedented specific activity of 21.8 ± 2.1 mA/cm 2 at 0.9 V versus the reversible hydrogen electrode, nearly double the previous record, and an ultrahigh mass activity of 10.7 ± 1.1 A/mg Pt .

Science & Technology - Other Topics↗

DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Future Projection of Tropical Upper-Tropospheric Troughs and Implications for Tropical Cyclone Activity

Summertime tropical upper-tropospheric troughs (TUTTs) provide a unified framework to better understand how extratropical and tropical forcings jointly modulate basin-scale tropical cyclone (TC) activity. In this study, we examine future changes in TUTTs and their implications for TC activity. Multimodel ensemble-mean projections from 45 Coupled Model Intercomparison Project phase 6 (CMIP6) models suggest a contraction of the Pacific TUTT and an expansion of the Atlantic TUTT as the climate warms. Consistently, future changes in environment-based TC indices indicate that the large-scale conditions will become more favorable for TC genesis and intensification over the central North Pacific but less favorable over the tropical North Atlantic and Gulf of Mexico. Utilizing a TC-permitting large-ensemble dataset [i.e., the Database for Policy Decision-Making for Future Climate Change (d4PDF)] that adequately captures the observed interannual TUTT–TC relationships, we further confirm the impacts of projected TUTT changes on the TC activity in a warmer climate. In contrast, the TUTT–TC relationship is poorly represented in most CMIP6 High-Resolution Model Intercomparison Project (HighResMIP) models; such deficiencies call for caution when assessing future TC risk based on explicitly tracked TCs in these models. Additionally, CMIP6 projections show large intermodel spread in TUTT changes, implying uncertainty in projected TC activity, especially over the central-to-eastern Pacific and the North Atlantic. This intermodel spread is associated with interhemispheric sea surface temperature warming asymmetry, which leads to a meridional shift of the intertropical convergence zone (ITCZ) and the simultaneous weakening or strengthening of TUTTs in the North Pacific and North Atlantic. The potential contributions of anthropogenic aerosol forcing and oceanic circulation to this interhemispheric warming asymmetry are briefly examined.

Climate Change↗

DOE OSTI2026

Viral Nuclease Inhibitors: Small molecule disruptors of the UL12 alkaline nuclease display broad anti-herpes virus activity

Herpes simplex virus 1 (HSV-1) UL12 encodes a highly conserved 5′ → 3′ alkaline exonuclease that is essential for the production of infectious virus. Together with the viral single-stranded DNA-binding/annealing protein ICP8, UL12 functions as a two-component recombinase that mediates recombination-dependent viral DNA replication. Here, we present the crystal structure of the catalytic domain of the HSV alkaline nuclease (UL12), which provides the first view of an α-herpesvirus alkaline nuclease. Using this structure, we optimized a series of small-molecule viral nuclease inhibitors (VNIs) that target the UL12 active site and potently inhibit UL12 exonuclease activity in vitro. We have thus established a robust platform for structure-based docking, SAR analysis and rational inhibitor design. Because UL12 orthologs are conserved across all human herpesviruses, we examined the activity of these compounds against the β- and γ-herpesvirus alkaline nucleases UL98 and SOX and found that they inhibit all three enzymes. The VNIs also exhibit antiviral activity against HSV-1 and HCMV in cell culture. EC 50 and IC 50 values were in the nanomolar to low micromolar range. Together, these findings establish herpesvirus alkaline nucleases as conserved, druggable antiviral targets and provide a foundation for the development of broad-spectrum anti-herpesvirus therapeutics, either as standalone agents or in combination with existing nucleoside analogs.

Sharma, Nidhi↗

DOE OSTI2026

1995 OKI Household Activity and Travel Report Survey

The OKI Household Activity and Travel Report Survey 1995, conducted by Market Opinion Research, gathered household activity and travel data from 3,000 households within the OKI region (Ohio, Kentucky, and Indiana Council of Governments' service area). The region covers over 2,615 square miles and is home to 697,468 households (over 1.75 million people). The primary purpose of this study was to provide OKI with a new database of travel patterns and behavior to assist in updating the region's transportation models. Respondents were asked to report their activities for a 24-hour period from 3:00 a.m. to 3:00 a.m. on an assigned activity day. The survey included weekday assignments only from October 4, 1995, to November 30, 1995.

1Hz data↗

DOE OSTI2024

Neutral rhenium(i) tricarbonyl complexes with sulfur-donor ligands: anti-proliferative activity and cellular localization

Rhenium(I) tricarbonyl complexes are widely studied for their cell imaging properties and anticancer and anti-microbial activities, but the complexes with S-donor ligands remain relatively unexplored. A series of six fac-[Re(NN)(CO) 3 (SR)] complexes, where (NN) is 2,2'-bipyridyl (bipy) or 1,10-phenanthroline (phen), and RSH is a series of thiocarboxylic acid methyl esters, have been synthesized and characterized. Cellular uptake and anti-proliferative activities of these complexes in human breast cancer cell lines (MDA-MB-231 and MCF-7) were generally lower than those of the previously described fac-[Re(NN)(CO) 3 (OH 2 )] + complexes; however, one of the complexes, fac-[Re(CO) 3 (phen)(SC(Ph)CH 2 C(O)OMe))] (3b), was active (IC 50 ~ 10 μM at 72 h treatment) in thiol-depleted MDA-MB-231 cells. Moreover, unlike fac- [Re(CO) 3 (phen)(OH 2 )] + , this complex did not lose activity in the presence of extracellular glutathione. Taken together these properties show promise for further development of 3b and its analogues as potential anti-cancer drugs for co-treatment with thiol-depleting agents. Conversely, the stable and non-toxic complex, fac-[Re(bipy)(CO) 3 (SC(Me)C(O)OMe)] (1a), predominantly localized in the lysosomes of MDA-MB-231 cells, as shown by live cell confocal microscopy (λ ex = 405 nm, λ em = 470-570 nm). It is strongly localized in a subset of lysosomes (25 μM Re, 4 h treatment), as shown by co-localization with a Lysotracker dye. Longer treatment times with 1a (25 μM Re for 48 h) resulted in partial migration of the probe into the mitochondria, as shown by co-localization with a Mitotracker dye. These properties make complex 1a an attractive target for further development as an organelle probe for multimodal imaging, including phosphorescence, carbonyl tag for vibrational spectroscopy, and Re tag for X-ray fluorescence microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Active Nematic Ratchet in Asymmetric Obstacle Arrays

We numerically investigate the effect of an asymmetric periodic obstacle array in a two-dimensional active nematic. We find that activity in conjunction with the asymmetry leads to a ratchet effect or unidirectional flow of the fluid along the asymmetry direction. The directional flow is still present even in the active turbulent phase when the gap between obstacles is sufficiently small. We demonstrate that the dynamics of the topological defects transition from flow-mirroring to smectic-like as the gap between obstacles is made smaller, and explain this transition in terms of the pinning of negative winding number defects between obstacles. This also leads to a non-monotonic ratchet effect magnitude as a function of obstacle size, so that there is an optimal obstacle size for ratcheting at fixed activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗