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DOE OSTI2020

FeS colloids – formation and mobilization pathways in natural waters

For this study, we have used synchrotron-based X-ray absorption spectroscopy (structure of Fe–S clusters), transmission electron microscopy (solid-phase crystallinity), Fourier-transform ion-cyclotron-resonance mass spectrometry (identity and composition of natural organic carbon compounds), inductively coupled plasma optical emission spectrometry (total aqueous Fe), and the revised ferrozine method (aqueous Fe( II ) and Fe( III ) concentrations) to determine the stability and nature of colloids generated by sulfidation of ferrihydrite nanoparticles in the absence and presence of organic compounds. We observed that reductive dissolution of ferrihydrite by aqueous sulfide generates nm-scale FeS clusters. Their subsequent aggregation, which promotes settling of FeS aggregates into the solid fraction, was directly correlated with sulfide/Fe ratio. At sulfide/Fe ratios ≤0.5, FeS clusters and larger colloids remained in suspension for at least 14 days (and up to several months). At sulfide/Fe ratios >0.5, sulfidation reaction rates were rapid and FeS cluster aggregation was accelerated. Moreover, the presence of organic compounds increased the time of suspension of FeS colloids, whereas increased ionic strength inhibited the generation of FeS colloids. We present a general conceptual model to predict when and where FeS colloids can form and enhance or inhibit the mobility of contaminants and nutrients associated with them. Our study indicates that in lowsalinity fresh groundwater systems poor in sulfate (i.e. low sulfidation; lakes, floodplains, peatlands etc.), the ferrihydrite sulfidation reaction generates aqueous FeS clusters and larger colloids that remain suspended over long time periods, thus mobilizing a substantial fraction of the total aqueous Fe and S.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Bridging the thermodynamics and kinetics of temperature-induced morphology evolution in polymer/fullerene organic solar cell bulk heterojunction

The performance of organic solar cells (OSC) critically depends on the morphology of the active layer. After deposition, the active layer is in a metastable state and prone to changes that lead to cell degradation. Here, a high efficiency fullerene:polymer blend is used as a model system to follow the temperature-induced morphology evolution through a series of thermal annealing treatments. Electron microscopy analysis of the nano-scale phase evolution during the early stages of thermal annealing revealed that spinodal decomposition, i.e. spontaneous phase separation with no nucleation stage, is possibly responsible for the formation of a fine scale bicontinuous structure. In the later evolution stages, large polycrystalline fullerene aggregates are formed. Optical microscopy and scattering revealed that aggregate-growth follows the Johnson–Mehl–Avrami–Kolmogorov equation indicating a heterogeneous transformation process, i.e., through nucleation and growth. These two mechanisms, spinodal decomposition vs. nucleation and growth, are mutually exclusive and their co-existence is surprising. This unexpected observation is resolved by introducing a metastable monotectic phase diagram and showing that the morphology evolution goes through two distinct and consecutive transformation processes where spinodal decomposition of the amorphous donor:acceptor blend is followed by nucleation and growth of crystalline acceptor aggregates. Lastly, this unified thermodynamic and kinetic mechanism allows us to correlate the morphology evolution with OSC degradation during thermal annealing.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Structural elucidation of polydopamine facilitated by ionic liquid solvation

Minimal understanding of the formation mechanism and structure of polydopamine (pDA) and its natural analogue, eumelanin, impedes the practical application of these versatile polymers and limits our knowledge of the origin of melanoma. The lack of conclusive structural evidence stems from the insolubility of these materials, which has spawned significantly diverse suggestions of pDA's structure in the literature. We discovered that pDA is soluble in certain ionic liquids. Using these ionic liquids (ILs) as solvents, we present an experimental methodology to solvate pDA, enabling us to identify pDA's chemical structure. The resolved pDA structure consists of self-assembled supramolecular aggregates that contribute to the increasing complexity of the polymer. The underlying molecular energetics of pDA solvation and a macroscopic picture of the disruption of the aggregates using IL solvents have been investigated, along with studies of the aggregation mechanism in water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Critical fluctuations in liquid–liquid extraction organic phases controlled by extractant and diluent molecular structure

Extractant aggregation in liquid–liquid extraction organic phases impacts extraction energetics and is related to the deleterious efficiency-limiting liquid–liquid phase transition known as third phase formation. Using small angle X-ray scattering, we find that structural heterogeneities across a wide range of compositions in binary mixtures of malonamide extractants and alkane diluents are well described by Ornstein–Zernike scattering. This suggests that structure in these simplified organic phases originates from the critical point associated with the liquid–liquid phase transition. To confirm this, we measure the temperature dependence of the organic phase structure, finding critical exponents consistent with the 3D Ising model. Molecular dynamics simulations were also consistent with this mechanism for extractant aggregation. Due to the absence of water or any other polar solutes required to form reverse-micellar-like nanostructures, these fluctuations are inherent to the binary extractant/diluent mixture. Further, we also show how the molecular structure of the extractant and diluent modulate these critical concentration fluctuations by shifting the critical temperature: critical fluctuations are suppressed by increasing extractant alkyl tail lengths or decreasing diluent alkyl chain lengths. This is consistent with how extractant and diluent molecular structure are known to impact metal and acid loading capacity in many-component LLE organic phases, suggesting phase behavior of practical systems may be effectively studied in simplified organic phases. Overall, the explicit connection between molecular structure, aggregation and phase behavior demonstrated here will enable the design of more efficient separations processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Presentation layer of CMS Online Monitoring System

The Compact Muon Solenoid (CMS) is one of the experiments at the CERN Large Hadron Collider (LHC). The CMS Online Monitoring system (OMS) is an upgrade and successor to the CMS Web-Based Monitoring (WBM)system, which is an essential tool for shift crew members, detector subsystem experts, operations coordinators, and those performing physics analyses. The CMS OMS is divided into aggregation and presentation layers. Communication between layers uses RESTful JSON:API compliant requests. The aggregation layer is responsible for collecting data from heterogeneous sources, storage of transformed and pre-calculated (aggregated) values and exposure of data via the RESTful API. The presentation layer displays detector information via a modern, user-friendly and customizable web interface. The CMS OMS user interface is composed of a set of cutting-edge software frameworks and tools to display non-event data to any authenticated CMS user worldwide. The web interface tree-like component structure comprises (top-down): workspaces, folders, pages, controllers and portlets. A clear hierarchy gives the required flexibility and control for content organization. Each bottom element instantiates a portlet and is a reusable component that displays a single aspect of data, like a table, a plot, an article, etc. Pages consist of multiple different portlets and can be customized at runtime by using a drag-and-drop technique. This is how a single page can easily include information from multiple online sources. Different pages give access to a summary of the current status of the experiment, as well as convenient access to historical data. This paper describes the CMS OMS architecture, core concepts and technologies of the presentation layer.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

High-bandwidth density silicon photonic resonators for energy-efficient optical interconnects

The growth of artificial intelligence applications demands ever larger and more complex deep learning models, dominating today's—and tomorrow's—data center and high-performance computing systems. While traditional electronics are failing to keep pace with application demands, silicon photonic (SiPh) interconnects have emerged as a necessary technology to support these systems. SiPh-driven wavelength-division multiplexing (WDM) offers a particularly promising path toward supporting incredibly high-aggregate link bandwidth in a compact and efficient form factor. One of the basic building blocks of these integrated WDM interconnects is the SiPh resonator. Their inherent wavelength selectivity and compact footprint allow for efficient data transmission multiplexed across dozens of carrier wavelengths. Used as add-drop (AD) filters, SiPh resonators are critical to constructing integrated tunable wavelength-selective optical circuit switches as well as for demultiplexing the different carrier wavelengths toward independent wavelength-insensitive photodiodes in a dense wavelength-division multiplexing receiver. Resonators in the all-pass (AP) configuration are widespread as well, allowing for wavelength-selective modulation to drive aggregate link bandwidths far beyond the individual channel data rate. Unlike SiPh Mach–Zehnder modulators (MZM), resonant modulators can be driven using low, complementary metal-oxide-semiconductor drive voltages, allowing for tight co-integration between photonic integrated circuits, fabricated with larger process node technologies, and electronic integrated circuits, designed to exploit the advantages of the latest node. To push toward practical peta-scale interconnects, a comprehensive review of SiPh resonators is required, addressing bottlenecks and design constraints at both the architecture and device levels. We first describe the predominant integrated link architectures and identify their limits. We then discuss the device-level design considerations that can be made for both AD and AP configuration resonators to overcome the system level limits with novel resonator device designs. Analytical models and numerical simulation of resonators are validated by experimental measurement of devices fabricated in a commercial 300-mm foundry, showing a clear path toward volume manufacturing. The demonstrated resonant modulators and filters support the feasibility of increasing the aggregate bandwidth of resonator-driven SiPh interconnects into the peta-scale regime.

42 ENGINEERING↗

DOE OSTI2020

Ring currents modulate optoelectronic properties of aromatic chromophores at 25 T

The properties of organic molecules can be influenced by magnetic fields, and these magnetic field effects are diverse. They range from inducing nuclear Zeeman splitting for structural determination in NMR spectroscopy to polaron Zeeman splitting organic spintronics and organic magnetoresistance. A pervasive magnetic field effect on an aromatic molecule is the aromatic ring current, which can be thought of as an induction of a circular current of π-electrons upon the application of a magnetic field perpendicular to the π-system of the molecule. While in NMR spectroscopy the effects of ring currents on the chemical shifts of nearby protons are relatively well understood, and even predictable, the consequences of these modified electronic states on the spectroscopy of molecules has remained unknown. In this work, we find that photophysical properties of model phthalocyanine compounds and their aggregates display clear magnetic field dependences up to 25 T, with the aggregates showing more drastic magnetic field sensitivities depending on the intermolecular interactions with the amplification of ring currents in stacked aggregates. These observations are consistent with ring currents measured in NMR spectroscopy and simulated in time-dependent density functional theory calculations of magnetic field-dependent phthalocyanine monomer and dimer absorption spectra. Here, we propose that ring currents in organic semiconductors, which commonly comprise aromatic moieties, may present new opportunities for the understanding and exploitation of combined optical, electronic, and magnetic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Structure-based design of nanobodies that inhibit seeding of Alzheimer’s patient–extracted tau fibrils

Despite much effort, antibody therapies for Alzheimer’s disease (AD) have shown limited efficacy. Challenges to the rational design of effective antibodies include the difficulty of achieving specific affinity to critical targets, poor expression, and antibody aggregation caused by buried charges and unstructured loops. To overcome these challenges, we grafted previously determined sequences of fibril-capping amyloid inhibitors onto a camel heavy chain antibody scaffold. These sequences were designed to cap fibrils of tau, known to form the neurofibrillary tangles of AD, thereby preventing fibril elongation. The nanobodies grafted with capping inhibitors blocked tau aggregation in biosensor cells seeded with postmortem brain extracts from AD and progressive supranuclear palsy (PSP) patients. The tau capping nanobody inhibitors also blocked seeding by recombinant tau oligomers. Another challenge to the design of effective antibodies is their poor blood–brain barrier (BBB) penetration. In this study, we also designed a bispecific nanobody composed of a nanobody that targets a receptor on the BBB and a tau capping nanobody inhibitor, conjoined by a flexible linker. We provide evidence that the bispecific nanobody improved BBB penetration over the tau capping inhibitor alone after intravenous administration in mice. Our results suggest that the design of synthetic antibodies that target sequences that drive protein aggregation may be a promising approach to inhibit the prion-like seeding of tau and other proteins involved in AD and related proteinopathies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Membrane-mediated fibrillation and toxicity of the tau hexapeptide PHF6

The aggregation of the tau protein into neurofibrillary tangles is believed to correlate with cognitive decline in several neurodegenerative disorders, including Alzheimer's disease. Recent studies suggest that tau's interactions with the cell membrane could serve as a toxicity pathway and also enhance fibrillation into paired helical filaments (PHFs). Conformational changes associated with tau-membrane interactions are poorly understood, and their characterization could improve our understanding of tau pathogenicity. In this study, we investigated the molecular level structural changes associated with the interaction of the tau hexapeptide PHF6 with model lipid membranes and characterized the effects of these interactions on membrane stability and peptide fibrillation. We used two PHF6 forms, the aggregation-prone PHF6 with N-terminal acetylation (Ac-PHF6) and the non-aggregation prone PHF6 with a standard N terminus (NH$^+_3$-PHF6). We found that both PHF6 peptides are neurotoxic and exhibit similar membrane-mediated changes, consisting of: 1) favorable interactions with anionic membranes, 2) membrane destabilization through lipid extraction, and 3) membrane-mediated fibrillation. The rate at which these changes occurred was the main difference between the two peptides. NH$^+_3$-PHF6 displayed slow membrane-mediated fibrillation after 6 days of incubation, whereas Ac-PHF6 adopted a β-sheet conformation at the surface of the membrane within hours. Ac-PHF6 interactions with the membrane were also accompanied by membrane invagination and rapid membrane destabilization. Overall, our results reveal that membrane interactions could play a critical role in tau toxicity and fibrillation, and highlight that unraveling these interactions is important for significantly advancing the development of therapeutic strategies to manage tau-associated neurodegenerative diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

PIP4Kγ as a potential target for Huntington's disease

Phosphoinositide lipids provide spatial and temporal regulation of cell signaling and membrane traffic. The PI5P‐4‐kinase family is one of the less studied phosphoinositide lipid kinases. These enzymes catalyze the conversion of phosphatidylinositol 5‐phosphate to phosphatidylinositol 4,5‐bis phosphate. A recent study by Vicinanza et al., a suggested that depletion of the PI5P‐4‐kinase, PIP4Kγ promotes a non‐canonical autophagy pathway. Moreover, this depletion reduced the presence of huntingtin‐exon1‐polyglutamine aggregates. Expression of exon1 of huntingtin with an extended polyglutamine tract is a model for huntingtin protein aggregates. To further test the hypothesis that PIP4Kγ is a potential target to reduce huntingtin aggregates, we tested the depletion of PIP4Kγ in cell culture models that express full length mutant huntingtin (mHtt). We determined that depletion of PIP4Kγ, but not PIP4Kα or PIP4Kβ, lowers the levels of mHtt in patient fibroblasts and in immortalized Hdh Q111 mouse striatal neurons. We show that PIP4Kγ‐dependent depletion of mHtt requires lysosomal function because the depletion is blocked by the lysosomal inhibitor, bafilomycin A1. Moreover, we show that depletion of PIP4Kγ increases autophagic flux, as measured by an increase in LC3‐II levels by western blot analysis and an increase in LC3‐II puncta by microscopy. Our studies suggest that PIP4kγ should be further pursued as a target for Huntington's disease. Support or Funding Information This work was supported by AHA postdoctoral fellowship 14POST20480137 (Sai Srinivas Panapakkam Giridharan), NIH grants R01GM050403 and NS064015 (Lois S Weisman) and by HSS funding 1R03MH084839 (Juan Marugan)

Giridharan, Sai Srinivas Panapakkam↗

DOE OSTI2021

Toward witnessing molecular exciton entanglement from spectroscopy

Entanglement is a defining feature of quantum mechanics that can be a resource in engineered and natural systems, but measuring entanglement in experiment remains elusive especially for large chemical systems. Most practical approaches require determining and measuring a suitable entanglement witness which provides some level of information about the entanglement structure of the probed state. A fundamental quantity of quantum metrology is the quantum Fisher information (QFI), which is a rigorous witness of multipartite entanglement that can be evaluated from linear response functions for certain states. Here, in this paper, we explore measuring the QFI of molecular exciton states of the first-excitation subspace from spectroscopy. In particular, we utilize the fact that the linear response of a pure state subject to a weak electric field over all possible driving frequencies encodes the variance of the collective dipole moment in the probed state, which is a valid measure for QFI. The systems that are investigated include the molecular dimer, N-site linear aggregate with nearest-neighbor coupling, and N-site circular aggregate, all modeled as a collection of interacting qubits. Our theoretical analysis shows that the variance of the collective dipole moment in the brightest dipole-allowed eigenstate is the maximum QFI. The optical response of a thermally equilibrated state in the first-excitation subspace is also a valid QFI. Theoretical predictions of the measured QFI for realistic linear dye aggregates as a function of temperature and energetic disorder due to static variations of the host matrix show that two- to three-partite entanglement is realizable. This paper lays some groundwork and inspires measurement of multipartite entanglement of molecular excitons with ultrafast pump-probe experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Impacts of Lock-off Time on Virtual Battery Model from Thermostatically Controlled Loads

We test through simulation the influence of lock-off time on the aggregated flexibility of thermostatically controllable loads (TCLs), which is modeled by virtual battery (VB) models. The VB model provides a simple but effective way to quantify the aggregated flexibility of TCLs, but its efficacy is not clear when there is lock-off time for TCLs. TCLs cannot be turned on during the lock-off period, and so lock-off time imposes inevitable restrictions on not only the flexibility of individual TCLs but also the aggregated flexibility of a group of TCLs. We first test the influence of lock-off time on the efficacy of VB models with two artificial signals. One of the signal is of low frequency while the other is of high frequency. We then use real-world data to test the influence. One set of data is from a duck curve from CAISO while the other set of data is from AGC signals from PJM. The duck curve changes slowly while the AGC signals change rapidly over time. From both the artificial signals and real-word data, we find that lock-off time has a more significant impact on rapid signals than on slow signals.

Wang, Peng↗

DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗

DOE OSTI2024

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗

DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear-and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute time-scale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

irradiance↗

DOE OSTI2024

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗

DOE OSTI2019

Individual Load Model Parameter Estimation in Distribution Systems Using Load Switching Events

There currently exists a mature literature on modeling the aggregate load of a distribution feeder by making use of measurements at its feeder-head at substation. The primary application of such feeder-aggregated load models is in sub-transmission or transmission system analysis. However, there is a growing need in practice also to model each individual load across the feeder. If available, such individual load models have applications in power distribution system analysis, e.g., to better integrate distributed energy resources or to improve power quality and reliability. Motivated by this observation, in this paper, we propose a new method for individual load modeling in power distribution systems. It works by using the measurements only at the feeder-head. It takes an innovative approach to analyzing the load switching events across the distribution feeder itself, instead of or in addition to relying on upstream voltage events that are commonly used in feeder-aggregated load modeling. By tracking the downstream load switching events, the proposed method can make a robust estimation of the ZIP load model parameters for all individual loads. The proposed method is examined on small illustrative test-feeders as well as the IEEE 33-bus test system under various operating scenarios. The adverse impact of errors in measurements and system parameters are also investigated on the performance of the developed load modeling method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

42 ENGINEERING↗