Faculty Publications

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https://hdl.handle.net/1911/75173

This collection includes faculty journal articles deposited per Rice's Open Access Policy and additional faculty work. Items found in this collection can also be found in the authors' departmental faculty publication collections.

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Trapped-ion quantum simulation of electron transfer models with tunable dissipation
(AAAS, 2024) So, Visal; Duraisamy Suganthi, Midhuna; Menon, Abhishek; Zhu, Mingjian; Zhuravel, Roman; Pu, Han; Wolynes, Peter G.; Onuchic, José N.; Pagano, Guido; Center for Theoretical Biological Physics
Electron transfer is at the heart of many fundamental physical, chemical, and biochemical processes essential for life. The exact simulation of these reactions is often hindered by the large number of degrees of freedom and by the essential role of quantum effects. Here, we experimentally simulate a paradigmatic model of molecular electron transfer using a multispecies trapped-ion crystal, where the donor-acceptor gap, the electronic and vibronic couplings, and the bath relaxation dynamics can all be controlled independently. By manipulating both the ground-state and optical qubits, we observe the real-time dynamics of the spin excitation, measuring the transfer rate in several regimes of adiabaticity and relaxation dynamics. Our results provide a testing ground for increasingly rich models of molecular excitation transfer processes that are relevant for molecular electronics and light-harvesting systems.
Lateral Flow-Based Skin Patch for Rapid Detection of Protein Biomarkers in Human Dermal Interstitial Fluid
(American Chemical Society, 2024) Wilkirson, Elizabeth C.; Li, Danika; Lillehoj, Peter B.
Rapid diagnostic tests (RDTs) offer valuable diagnostic information in a quick, easy-to-use and low-cost format. While RDTs are one of the most commonly used tools for in vitro diagnostic testing, they require the collection of a blood sample, which is painful, poses risks of infection and can lead to complications. We introduce a blood-free point-of-care diagnostic test for the rapid detection of protein biomarkers in dermal interstitial fluid (ISF). This device consists of a lateral flow immunochromatographic assay (LFIA) integrated within a microfluidic skin patch. ISF is collected from the skin using a microneedle array and vacuum-assisted extraction system integrated in the patch, and transported through the lateral flow strip via surface tension. Using this skin patch platform, we demonstrate in situ detection of anti-tetanus toxoid IgG and SARS-CoV-2 neutralizing antibodies, which could be accurately detected in human ISF in <20 min. We envision that this device can be readily modified to detect other protein biomarkers in dermal ISF, making it a promising tool for rapid diagnostic testing.
Impact of Surface Enhanced Raman Spectroscopy in Catalysis
(American Chemical Society, 2024) Stefancu, Andrei; Aizpurua, Javier; Alessandri, Ivano; Bald, Ilko; Baumberg, Jeremy J.; Besteiro, Lucas V.; Christopher, Phillip; Correa-Duarte, Miguel; de Nijs, Bart; Demetriadou, Angela; Frontiera, Renee R.; Fukushima, Tomohiro; Halas, Naomi J.; Jain, Prashant K.; Kim, Zee Hwan; Kurouski, Dmitry; Lange, Holger; Li, Jian-Feng; Liz-Marzán, Luis M.; Lucas, Ivan T.; Meixner, Alfred J.; Murakoshi, Kei; Nordlander, Peter; Peveler, William J.; Quesada-Cabrera, Raul; Ringe, Emilie; Schatz, George C.; Schlücker, Sebastian; Schultz, Zachary D.; Tan, Emily Xi; Tian, Zhong-Qun; Wang, Lingzhi; Weckhuysen, Bert M.; Xie, Wei; Ling, Xing Yi; Zhang, Jinlong; Zhao, Zhigang; Zhou, Ru-Yu; Cortés, Emiliano
Catalysis stands as an indispensable cornerstone of modern society, underpinning the production of over 80% of manufactured goods and driving over 90% of industrial chemical processes. As the demand for more efficient and sustainable processes grows, better catalysts are needed. Understanding the working principles of catalysts is key, and over the last 50 years, surface-enhanced Raman Spectroscopy (SERS) has become essential. Discovered in 1974, SERS has evolved into a mature and powerful analytical tool, transforming the way in which we detect molecules across disciplines. In catalysis, SERS has enabled insights into dynamic surface phenomena, facilitating the monitoring of the catalyst structure, adsorbate interactions, and reaction kinetics at very high spatial and temporal resolutions. This review explores the achievements as well as the future potential of SERS in the field of catalysis and energy conversion, thereby highlighting its role in advancing these critical areas of research.
Distilling the knowledge from large-language model for health event prediction
(Springer Nature, 2024) Ding, Sirui; Ye, Jiancheng; Hu, Xia; Zou, Na
Health event prediction is empowered by the rapid and wide application of electronic health records (EHR). In the Intensive Care Unit (ICU), precisely predicting the health related events in advance is essential for providing treatment and intervention to improve the patients outcomes. EHR is a kind of multi-modal data containing clinical text, time series, structured data, etc. Most health event prediction works focus on a single modality, e.g., text or tabular EHR. How to effectively learn from the multi-modal EHR for health event prediction remains a challenge. Inspired by the strong capability in text processing of large language model (LLM), we propose the framework CKLE for health event prediction by distilling the knowledge from LLM and learning from multi-modal EHR. There are two challenges of applying LLM in the health event prediction, the first one is most LLM can only handle text data rather than other modalities, e.g., structured data. The second challenge is the privacy issue of health applications requires the LLM to be locally deployed, which may be limited by the computational resource. CKLE solves the challenges of LLM scalability and portability in the healthcare domain by distilling the cross-modality knowledge from LLM into the health event predictive model. To fully take advantage of the strong power of LLM, the raw clinical text is refined and augmented with prompt learning. The embedding of clinical text are generated by LLM. To effectively distill the knowledge of LLM into the predictive model, we design a cross-modality knowledge distillation (KD) method. A specially designed training objective will be used for the KD process with the consideration of multiple modality and patient similarity. The KD loss function consists of two parts. The first one is cross-modality contrastive loss function, which models the correlation of different modalities from the same patient. The second one is patient similarity learning loss function to model the correlations between similar patients. The cross-modality knowledge distillation can distill the rich information in clinical text and the knowledge of LLM into the predictive model on structured EHR data. To demonstrate the effectiveness of CKLE, we evaluate CKLE on two health event prediction tasks in the field of cardiology, heart failure prediction and hypertension prediction. We select the 7125 patients from MIMIC-III dataset and split them into train/validation/test sets. We can achieve a maximum 4.48% improvement in accuracy compared to state-of-the-art predictive model designed for health event prediction. The results demonstrate CKLE can surpass the baseline prediction models significantly on both normal and limited label settings. We also conduct the case study on cardiology disease analysis in the heart failure and hypertension prediction. Through the feature importance calculation, we analyse the salient features related to the cardiology disease which corresponds to the medical domain knowledge. The superior performance and interpretability of CKLE pave a promising way to leverage the power and knowledge of LLM in the health event prediction in real-world clinical settings.
Validation studies of the FLASH-TV system to passively measure children’s TV viewing
(Springer Nature, 2024) Vadathya, Anil Kumar; Garza, Tatyana; Alam, Uzair; Ho, Alex; Musaad, Salma M. A.; Beltran, Alicia; Moreno, Jennette P.; Baranowski, Tom; Haidar, Nimah; Hughes, Sheryl O.; Mendoza, Jason A.; Veeraraghavan, Ashok; Young, Joseph; Sano, Akane; O’Connor, Teresia M.
TV viewing is associated with health risks, but existing measures of TV viewing are imprecise due to relying on self-report. We developed the Family Level Assessment of Screen use in the Home (FLASH)-TV, a machine learning pipeline with state-of-the-art computer vision methods to measure children’s TV viewing. In three studies, lab pilot (n = 10), lab validation (n = 30), and home validation (n = 20), we tested the validity of FLASH-TV 3.0 in task-based protocols which included video observations of children for 60 min. To establish a gold-standard to compare FLASH-TV output, the videos were labeled by trained staff at 5-second epochs for whenever the child watched TV. For the combined sample with valid data (n = 59), FLASH-TV 3.0 provided a mean 85% (SD 8%) accuracy, 80% (SD 17%) sensitivity, 86% (SD 8%) specificity, and 0.71 (SD 0.15) kappa, compared to gold-standard. The mean intra-class correlation (ICC) of child’s TV viewing durations of FLASH-TV 3.0 to gold-standard was 0.86. Overall, FLASH-TV 3.0 correlated well with the gold standard across a diverse sample of children, but with higher variability among Black children than others. FLASH-TV provides a tool to estimate children’s TV viewing and increase the precision of research on TV viewing’s impact on children’s health.
Thermal imaging through hot emissive windows
(Springer Nature, 2024) Prasad, Ciril Samuel; Everitt, Henry O.; Naik, Gururaj V.
It is not currently possible for an infrared camera to see through a hot window. The window’s own blinding thermal emission prevents objects on the other side from being imaged. Here, we demonstrate a path to overcoming this challenge by coating a hot window with an asymmetrically emitting infrared metasurface whose specially engineered imaginary index of refraction produces an asymmetric spatial distribution of absorption losses in its constituent nanoscale resonators. Operating at 873 K, this metasurface-coated window suppresses thermal emission towards the camera while being sufficiently transparent for thermal imaging, doubling the thermal imaging contrast when compared to a control window at the same temperature
Whole-cell multi-target single-molecule super-resolution imaging in 3D with microfluidics and a single-objective tilted light sheet
(Springer Nature, 2024) Saliba, Nahima; Gagliano, Gabriella; Gustavsson, Anna-Karin; Smalley-Curl Institute;Center for Nanoscale Imaging Sciences
Multi-target single-molecule super-resolution fluorescence microscopy offers a powerful means of understanding the distributions and interplay between multiple subcellular structures at the nanoscale. However, single-molecule super-resolution imaging of whole mammalian cells is often hampered by high fluorescence background and slow acquisition speeds, especially when imaging multiple targets in 3D. In this work, we have mitigated these issues by developing a steerable, dithered, single-objective tilted light sheet for optical sectioning to reduce fluorescence background and a pipeline for 3D nanoprinting microfluidic systems for reflection of the light sheet into the sample. This easily adaptable microfluidic fabrication pipeline allows for the incorporation of reflective optics into microfluidic channels without disrupting efficient and automated solution exchange. We combine these innovations with point spread function engineering for nanoscale localization of individual molecules in 3D, deep learning for analysis of overlapping emitters, active 3D stabilization for drift correction and long-term imaging, and Exchange-PAINT for sequential multi-target imaging without chromatic offsets. We then demonstrate that this platform, termed soTILT3D, enables whole-cell multi-target 3D single-molecule super-resolution imaging with improved precision and imaging speed.
Imaging shapes of atomic nuclei in high-energy nuclear collisions
(Springer Nature, 2024) STAR Collaboration
Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes1–3, traditionally explored using non-invasive spectroscopic techniques at low energies4,5. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors6,7. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.
Neural Dynamics of Creative Movements During the Rehearsal and Performance of “LiveWire"
(Springer Nature, 2024) Pacheco-Ramírez, Maxine Annel; Ramírez-Moreno, Mauricio A.; Kukkar, Komal; Rao, Nishant; Huber, Derek; Brandt, Anthony K.; Noble, Andy; Noble, Dionne; Ealey, Bryan; Contreras-Vidal, Jose L.
This report contains a description of physiological and motion data, recorded simultaneously and in synchrony using the hyperscanning method from two professional dancers using wireless mobile brain-body imaging (MoBI) technology during rehearsals and public performances of “LiveWire” - a new composition comprised of five choreographed music and dance sections inspired by neuroscience principles. Brain and ocular activity were measured using 28-channel scalp electroencephalography (EEG), and 4-channel electrooculography (EOG), respectively; and head motion was recorded using an inertial measurement unit (IMU) placed on the forehead of each dancer. Video recordings were obtained for each session to allow for tagging of physiological and motion signals and for behavioral analysis. Data recordings were collected from 10 sessions over a 4-month period, in which the dancers rehearsed or performed (in front of an audience) choreographed expressive movements. A detailed explanation of the experimental set-up, the steps carried out for data collection, and an explanation on the usage are provided in this report.
Development and characterization of a low intensity vibrational system for microgravity studies
(Springer Nature, 2024) Khan, Omor M.; Gasperini, Will; Necessary, Chess; Jacobs, Zach; Perry, Sam; Rexroat, Jason; Nelson, Kendall; Gamble, Paul; Clements, Twyman; DeLeon, Maximilien; Howard, Sean; Zavala, Anamaria; Farach-Carson, Mary; Blaber, Elizabeth; Wu, Danielle; Satici, Aykut; Uzer, Gunes
Extended-duration human spaceflight necessitates a better understanding of the physiological impacts of microgravity. While the ground-based microgravity simulations identified low intensity vibration (LIV) as a possible countermeasure, how cells may respond to LIV under real microgravity remain unexplored. In this way, adaptation of LIV bioreactors for space remains limited, resulting in a significant gap in microgravity research. In this study, we introduce an LIV bioreactor designed specifically for the usage in the International Space Station. Our research covers the bioreactor’s design process and evaluation of the short-term viability of cells encapsulated in hydrogel-laden 3D printed scaffolds under 0.7 g, 90 Hz LIV. An LIV bioreactor compatible with the operation requirements of space missions provides a robust platform to study cellular effects of LIV under real microgravity conditions.
High-performance 2D electronic devices enabled by strong and tough two-dimensional polymer with ultra-low dielectric constant
(Springer Nature, 2024) Fang, Qiyi; Yi, Kongyang; Zhai, Tianshu; Luo, Shisong; Lin, Chen-yang; Ai, Qing; Zhu, Yifan; Zhang, Boyu; Alvarez, Gustavo A.; Shao, Yanjie; Zhou, Haolei; Gao, Guanhui; Liu, Yifeng; Xu, Rui; Zhang, Xiang; Wang, Yuzhe; Tian, Xiaoyin; Zhang, Honghu; Han, Yimo; Zhu, Hanyu; Zhao, Yuji; Tian, Zhiting; Zhong, Yu; Liu, Zheng; Lou, Jun; Rice Advanced Materials Institute
As the feature size of microelectronic circuits is scaling down to nanometer order, the increasing interconnect crosstalk, resistance-capacitance (RC) delay and power consumption can limit the chip performance and reliability. To address these challenges, new low-k dielectric (k < 2) materials need to be developed to replace current silicon dioxide (k = 3.9) or SiCOH, etc. However, existing low-k dielectric materials, such as organosilicate glass or polymeric dielectrics, suffer from poor thermal and mechanical properties. Two-dimensional polymers (2DPs) are considered promising low-k dielectric materials because of their good thermal and mechanical properties, high porosity and designability. Here, we report a chemical-vapor-deposition (CVD) method for growing fluoride rich 2DP-F films on arbitrary substrates. We show that the grown 2DP-F thin films exhibit ultra-low dielectric constant (in plane k = 1.85 and out-of-plane k = 1.82) and remarkable mechanical properties (Young’s modulus > 15 GPa). We also demonstrated the improved performance of monolayer MoS2 field-effect-transistors when utilizing 2DP-F thin films as dielectric substrates.
Exploration of the hierarchical assembly space of collagen-like peptides beyond the triple helix
(Springer Nature, 2024) Yu, Le Tracy; Kreutzberger, Mark A. B.; Bui, Thi H.; Hancu, Maria C.; Farsheed, Adam C.; Egelman, Edward H.; Hartgerink, Jeffrey D.
The de novo design of self-assembling peptides has garnered significant attention in scientific research. While alpha-helical assemblies have been extensively studied, exploration of polyproline type II helices, such as those found in collagen, remains relatively limited. In this study, we focus on understanding the sequence-structure relationship in hierarchical assemblies of collagen-like peptides, using defense collagen Surfactant Protein A as a model. By dissecting the sequence derived from Surfactant Protein A and synthesizing short collagen-like peptides, we successfully construct a discrete bundle of hollow triple helices. Amino acid substitution studies pinpoint hydrophobic and charged residues that are critical for oligomer formation. These insights guide the de novo design of collagen-like peptides, resulting in the formation of diverse quaternary structures, including discrete and heterogenous bundled oligomers, two-dimensional nanosheets, and pH-responsive nanoribbons. Our study represents a significant advancement in the understanding and harnessing of collagen higher-order assemblies beyond the triple helix.
Protracted carbon burial following the Early Jurassic Toarcian Oceanic Anoxic Event (Posidonia Shale, Lower Saxony Basin, Germany)
(Springer Nature, 2024) Celestino, R. F. S.; Ruhl, M.; Dickson, A. J.; Idiz, E.; Jenkyns, H. C.; Leng, M. J.; Mattioli, E.; Minisini, D.; Hesselbo, S. P.
Lower Jurassic marine basins across the northwest European epicontinental shelf were commonly marked by deposition of organic-rich black shales. Organic-carbon burial was particularly widespread during the Toarcian Oceanic Anoxic Event (T-OAE: also known as the Jenkyns Event) with its accompanying negative carbon-isotope excursion (nCIE). Lower Toarcian black shales in central and southern Germany are known as the Posidonia Shale Formation (Posidonienschiefer) and are thought to have formed during the T-OAE nCIE. Here, we present stratigraphic (carbon-isotope, Rock–Eval, calcareous nannofossil) data from the upper Pliensbachian and lower Toarcian strata from a core drilled on the northern flank of the Lower Saxony Basin, north–west Germany. The bio- and chemostratigraphic framework presented demonstrates that (i) the rock record of the T-OAE at the studied locality registered highly condensed sedimentation and/or multiple hiatuses and (ii) the deposition of organic-rich black shale extended significantly beyond the level of the T-OAE, thereby contrasting with well-studied sections of the Posidonia Shale in southern Germany but showing similarities with geographically nearby basins such as the Paris Basin (France). Prolonged and enhanced organic-carbon burial represents a negative feedback mechanism in the Earth system, with locally continued environmental perturbance accelerating the recovery of the global climate from T-OAE-associated hyperthermal conditions, whilst also accelerating a return to more positive δ13C values in global exogenic carbon pools.
Imaging the initial condition of heavy-ion collisions and nuclear structure across the nuclide chart
(Springer Nature, 2024) Jia, Jiangyong; Giacalone, Giuliano; Bally, Benjamin; Brandenburg, James Daniel; Heinz, Ulrich; Huang, Shengli; Lee, Dean; Lee, Yen-Jie; Loizides, Constantin; Li, Wei; Luzum, Matthew; Nijs, Govert; Noronha-Hostler, Jacquelyn; Ploskon, Mateusz; van der Schee, Wilke; Schenke, Bjoern; Shen, Chun; Somà, Vittorio; Timmins, Anthony; Xu, Zhangbu; Zhou, You
High-energy nuclear collisions encompass three key stages: the structure of the colliding nuclei, informed by low-energy nuclear physics, the initial condition, leading to the formation of quark–gluon plasma (QGP), and the hydrodynamic expansion and hadronization of the QGP, leading to final-state hadron distributions that are observed experimentally. Recent advances in both experimental and theoretical methods have ushered in a precision era of heavy-ion collisions, enabling an increasingly accurate understanding of these stages. However, most approaches involve simultaneously determining both QGP properties and initial conditions from a single collision system, creating complexity due to the coupled contributions of these stages to the final-state observables. To avoid this, we propose leveraging established knowledge of low-energy nuclear structures and hydrodynamic observables to independently constrain the QGP’s initial condition. By conducting comparative studies of collisions involving isobar-like nuclei—species with similar mass numbers but different ground-state geometries—we can disentangle the initial condition’s impacts from the QGP properties. This approach not only refines our understanding of the initial stages of the collisions but also turns high-energy nuclear experiments into a precision tool for imaging nuclear structures, offering insights that complement traditional low-energy approaches. Opportunities for carrying out such comparative experiments at the Large Hadron Collider and other facilities could significantly advance both high-energy and low-energy nuclear physics. Additionally, this approach has implications for the future electron-ion collider. While the possibilities are extensive, we focus on selected proposals that could benefit both the high-energy and low-energy nuclear physics communities. Originally prepared as input for the long-range plan of U.S. nuclear physics, this white paper reflects the status as of September 2022, with a brief update on developments since then.
Pleozymes: Pleiotropic Oxidized Carbon Nanozymes Enhance Cellular Metabolic Flexibility
(MDPI, 2024) Vo, Anh T. T.; Mouli, Karthik; Liopo, Anton V.; Lorenzi, Philip; Tan, Lin; Wei, Bo; Martinez, Sara A.; McHugh, Emily A.; Tour, James M.; Khan, Uffaf; Derry, Paul J.; Kent, Thomas A.; Smalley-Curl Institute;Rice Advanced Materials Institute;The NanoCarbon Center
Our group has synthesized a pleiotropic synthetic nanozyme redox mediator we term a “pleozyme” that displays multiple enzymatic characteristics, including acting as a superoxide dismutase mimetic, oxidizing NADH to NAD+, and oxidizing H2S to polysulfides and thiosulfate. Benefits have been seen in acute and chronic neurological disease models. The molecule is sourced from coconut-derived activated charcoal that has undergone harsh oxidization with fuming nitric acid, which alters the structure and chemical characteristics, yielding 3–8 nm discs with broad redox potential. Prior work showed pleozymes localize to mitochondria and increase oxidative phosphorylation and glycolysis. Here, we measured cellular NAD+ and NADH levels after pleozyme treatment and observed increased total cellular NADH levels but not total NAD+ levels. A 13C-glucose metabolic flux analysis suggested pleozymes stimulate the generation of pyruvate and lactate glycolytically and from the tricarboxylic acid (TCA) cycle, pointing to malate decarboxylation. Analysis of intracellular fatty acid abundances suggests pleozymes increased fatty acid β-oxidation, with a concomitant increase in succinyl- and acetyl-CoA. Pleozymes increased total ATP, potentially via flexible enhancement of NAD+-dependent catabolic pathways such as glycolysis, fatty acid β-oxidation, and metabolic flux through the TCA cycle. These effects may be favorable for pathologies that compromise metabolism such as brain injury.
High sound pressure piezoelectric micromachined ultrasonic transducers using sputtered potassium sodium niobate
(Springer Nature, 2024) Xia, Fan; Peng, Yande; Yue, Wei; Luo, Mingze; Teng, Megan; Chen, Chun-Ming; Pala, Sedat; Yu, Xiaoyang; Ma, Yuanzheng; Acharya, Megha; Arakawa, Ryuichi; Martin, Lane W.; Lin, Liwei; Rice Advanced Materials Institute
This work presents air-coupled piezoelectric micromachined ultrasonic transducers (pMUTs) with high sound pressure level (SPL) under low-driving voltages by utilizing sputtered potassium sodium niobate K0.34Na0.66NbO3 (KNN) films. A prototype single KNN pMUT has been tested to show a resonant frequency at 106.3 kHz under 4 Vp-p with outstanding characteristics: (1) a large vibration amplitude of 3.74 μm/V, and (2) a high acoustic root mean square (RMS) sound pressure level of 105.5 dB/V at 10 cm, which is 5–10 times higher than those of AlN-based pMUTs at a similar frequency. There are various potential sensing and actuating applications, such as fingerprint sensing, touch point, and gesture recognition. In this work, we present demonstrations in three fields: haptics, loudspeakers, and rangefinders. For haptics, an array of 15 × 15 KNN pMUTs is used as a non-contact actuator to provide a focal pressure of around 160.3 dB RMS SPL at a distance of 15 mm. This represents the highest output pressure achieved by an airborne pMUT for haptic sensation on human palms. When used as a loudspeaker, a single pMUT element with a resonant frequency close to the audible range at 22.8 kHz is characterized. It is shown to be able to generate a uniform acoustic output with an amplitude modulation scheme. In the rangefinder application, pulse-echo measurements using a single pMUT element demonstrate good transceiving results, capable of detecting objects up to 2.82 m away. As such, this new class of high-SPL and low-driving-voltage pMUTs could be further extended to other applications requiring high acoustic pressure and a small form factor.
Comparison of synergy extrapolation and static optimization for estimating multiple unmeasured muscle activations during walking
(Springer Nature, 2024) Ao, Di; Fregly, Benjamin J.
Calibrated electromyography (EMG)-driven musculoskeletal models can provide insight into internal quantities (e.g., muscle forces) that are difficult or impossible to measure experimentally. However, the need for EMG data from all involved muscles presents a significant barrier to the widespread application of EMG-driven modeling methods. Synergy extrapolation (SynX) is a computational method that can estimate a single missing EMG signal with reasonable accuracy during the EMG-driven model calibration process, yet its performance in estimating a larger number of missing EMG signals remains unknown.
Modeling and experimental validation of nanophotonics-enhanced solar membrane distillation technology for treating reverse osmosis brine
(Springer Nature, 2024) Elrakhawi, Mayar; Tayel, Ahmed F.; Abdelrazek, Amr; He, Ze; Li, Qilin; Said, Ibrahim A.; Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment (NEWT)
A novel, cost-efficient Nanophotonic Enhanced Solar Membrane Distillation (NESMD) system, a solar-driven water desalination technology, was studied. The system features a photothermal membrane acting as a solar collector for water distillation, thus eliminating the need for an external condenser. To address the system’s vulnerability to thermal losses, a comprehensive mathematical model was developed and validated against real-world experimental data. This model represents intricately coupled heat and mass transfer within a sweeping-air NESMD system, incorporating heat loss considerations. The modeling strategy involved dividing the NESMD module into sub-cells and implementing a finite difference method for detailed analysis. This led to a series of nonlinear simultaneous equations, which were resolved via computational code using MATLAB software. The developed NESMD model exhibited commendable conformity to experimental data, exhibiting a relative percentage error of less than 10% for average permeate flux and identifying thermal losses as high as 63%. Depending on the operating conditions, heat transferred to the surroundings takes the lead among the heat loss contributors at higher feed rates (up to 25%), whereas heat conduction across the membrane dominates (up to 42%) thermal losses at low feed rates. The study established an exponential correlation between permeate production and solar energy, with a heat transfer coefficient ranging from 9.5 to 30 W m−2 K−1 and a coefficient of determination of 0.96. An integral part of this work includes calculating solar energy utilization and clarifying the system’s performance. Furthermore, this study examines the influence of diverse operational and geometric parameters, providing insights into enhancing production rates. Hence, an increase in feed layer thickness enhances freshwater production by 7%. Due to the intensification of solar irradiance, freshwater production increased ninefold, and specific energy consumption decreased by 134 kW hr m−3. This research underscores the potential of NESMD for sustainable desalination, providing a validated model that lays the groundwork for future advancements in membrane distillation technology.
Determining the N-Representability of a Reduced Density Matrix via Unitary Evolution and Stochastic Sampling
(American Chemical Society, 2024) Massaccesi, Gustavo E.; Oña, Ofelia B.; Capuzzi, Pablo; Melo, Juan I.; Lain, Luis; Torre, Alicia; Peralta, Juan E.; Alcoba, Diego R.; Scuseria, Gustavo E.
The N-representability problem consists in determining whether, for a given p-body matrix, there exists at least one N-body density matrix from which the p-body matrix can be obtained by contraction, that is, if the given matrix is a p-body reduced density matrix (p-RDM). The knowledge of all necessary and sufficient conditions for a p-body matrix to be N-representable allows the constrained minimization of a many-body Hamiltonian expectation value with respect to the p-body density matrix and, thus, the determination of its exact ground state. However, the number of constraints that complete the N-representability conditions grows exponentially with system size, and hence, the procedure quickly becomes intractable for practical applications. This work introduces a hybrid quantum-stochastic algorithm to effectively replace the N-representability conditions. The algorithm consists of applying to an initial N-body density matrix a sequence of unitary evolution operators constructed from a stochastic process that successively approaches the reduced state of the density matrix on a p-body subsystem, represented by a p-RDM, to a target p-body matrix, potentially a p-RDM. The generators of the evolution operators follow the well-known adaptive derivative-assembled pseudo-Trotter method (ADAPT), while the stochastic component is implemented by using a simulated annealing process. The resulting algorithm is independent of any underlying Hamiltonian, and it can be used to decide whether a given p-body matrix is N-representable, establishing a criterion to determine its quality and correcting it. We apply the proposed hybrid ADAPT algorithm to alleged reduced density matrices from a quantum chemistry electronic Hamiltonian, from the reduced Bardeen–Cooper–Schrieffer model with constant pairing, and from the Heisenberg XXZ spin model. In all cases, the proposed method behaves as expected for 1-RDMs and 2-RDMs, evolving the initial matrices toward different targets.
Harshly Oxidized Activated Charcoal Enhances Protein Persulfidation with Implications for Neurodegeneration as Exemplified by Friedreich’s Ataxia
(MDPI, 2024) Vo, Anh T. T.; Khan, Uffaf; Liopo, Anton V.; Mouli, Karthik; Olson, Kenneth R.; McHugh, Emily A.; Tour, James M.; Pooparayil Manoj, Madhavan; Derry, Paul J.; Kent, Thomas A.; Smalley-Curl Institute;Rice Advanced Materials Institute;The NanoCarbon Center
Harsh acid oxidation of activated charcoal transforms an insoluble carbon-rich source into water-soluble, disc structures of graphene decorated with multiple oxygen-containing functionalities. We term these pleiotropic nano-enzymes as “pleozymes”. A broad redox potential spans many crucial redox reactions including the oxidation of hydrogen sulfide (H2S) to polysulfides and thiosulfate, dismutation of the superoxide radical (O2−*), and oxidation of NADH to NAD+. The oxidation of H2S is predicted to enhance protein persulfidation—the attachment of sulfur to cysteine residues. Persulfidated proteins act as redox intermediates, and persulfidation protects proteins from irreversible oxidation and ubiquitination, providing an important means of signaling. Protein persulfidation is believed to decline in several neurological disorders and aging. Importantly, and consistent with the role of persulfidation in signaling, the master antioxidant transcription factor Nrf2 is regulated by Keap1’s persulfidation. Here, we demonstrate that pleozymes increased overall protein persulfidation in cells from apparently healthy individuals and from individuals with the mitochondrial protein mutation responsible for Friedreich’s ataxia. We further find that pleozymes specifically enhanced Keap1 persulfidation, with subsequent increased accumulation of Nrf2 and Nrf2’s antioxidant targets.

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