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The growing adoption of residential distributed energy resources (DERs) introduces more uncertain variability in power grid operation. More importantly, the residential DERs operate behind customers’ energy meters, and therefore, the utility cannot “directly” monitor them. Prior approaches to enable visibility into behind-the-meter (BTM) DERs either depend on estimations or require intrusive instrumentation on the customer side. To address the critical need for direct real-time monitoring of BTM DERs, in this paper, we propose a novel approach for utility-side direct real-time monitoring of residential BTM DERs. We utilize high-frequency (> 10kHz) conducted electromagnetic interference (EMI) from residential DERs’ grid-tied inverters to monitor their power generation. We discuss the working principle of our approach and present supporting results using three of-the-shelf grid-tied inverters. 

Freshwater scarcity is a global problem that requires collective efforts across all industry sectors. Nevertheless, a lack of access to operational water footprint data bars many applications from exploring optimization opportunities hidden within the temporal and spatial variations. To break this barrier into research in water sustainability, we build a dataset for operation direct water usage in the cooling systems and indirect water embedded in electricity generation. Our dataset consists of the hourly water efficiency of major U.S. cities and states from 2019 to 2023. We also offer cooling system models that capture the impact of weather on water efficiency. We present a preliminary analysis of our dataset and discuss three potential applications that can benefit from it. Our dataset is publicly available at Open Science Framework (OSF). 

Low fiber-direction compressive strength is a well-recognized weakness of carbon fiber-reinforced polymer (CFRP) composites. When a CFRP is produced using 3D printing, the compressive strength is further degraded. To solve this issue, in this paper, a novel magnetic compaction force-assisted additive manufacturing (MCFA-AM) method is used to print CFRP laminates reinforced with carbon nanofiber (CNF) z-threads (i.e., ZT-CFRP). MCFA-AM utilizes a magnetic force to simultaneously levitate, deposit, and compact fast-curing CFRP prepregs in free space and quickly solidifies the CFRP laminate part without any mold nor supporting substrate plate; it effectively reduces the voids. The longitudinal compressive test was performed on five different sample types. ZT-CFRP/MCFA-AM samples were printed under two different magnetic compaction rolling pressures, i.e., 0.5 bar and 0.78 bar. Compared with the longitudinal compressive strength of a typical CFRP manufactured by the traditional out-of-autoclave–vacuum-bag-only (OOA-VBO) molding process at the steady-state pressure of 0.82 bar, the ZT-CFRP/MCFA-AM samples showed either comparable results (by −1.00% difference) or enhanced results (+7.42% improvement) by using 0.5 bar or 0.78 bar magnetic rolling pressures, respectively. 

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates targeted drug delivery (TDD) to ensure that inhaled aerosolized drugs reach specific sites, such as the larynx and glottis, without harming healthy tissues. Using computational fluid particle dynamics (CFPD) and machine learning (ML), this study (1) investigated how drug properties and individual factors influence TDD efficiency for JORRP treatment and (2) developed personalized inhalation therapy using an ML-empowered smart inhaler control algorithm for precise medication release. This algorithm optimizes the inhaler nozzle position and diameter based on drug and patient-specific data, enhancing drug delivery to the larynx and glottis. CFPD simulations show that particle size significantly affects deposition fractions in the upper airway, emphasizing the importance of particle size selection. Additionally, optimal nozzle diameter and delivery efficiency depend on particle size, inhalation flow rate, and release time. The ML-based TDD strategy, employing a classification and regression tree model, outperforms conventional inhalation therapy by achieving a higher delivery efficiency to the larynx and glottis. This innovative concept of an ML-empowered smart inhaler represents a promising step toward personalized and precise pulmonary healthcare through inhalation therapy. It demonstrates the potential of AI-driven smart inhalers for improving the treatment outcomes of lung diseases that require TDD at designated lung sites.

 

Morphing matter that change shapes and properties in response to external stimuli have gained significant interests in material science, robotics, biomedical engineering, wearables, architecture, and design. Along with functional advances, there is growing pressure and interest in considering the environmental impact of morphing matter during its life cycle. The unique manufacturing and usage of morphing matter means that existing sustainable design frameworks and principles for general physical products may not apply directly. For example, manufacturing morphing matter often requires designing and predicting materials' behaviors over time, and using devices fabricated with morphing matter often involves harnessing renewable energy and self‐reconfiguration, which pose unique sustainability opportunities and challenges. This study reflects and summarizes the field's practice in sustainable manufacturing, transport, use, and end‐of‐life handling of morphing matter. The term “sustainable morphing matter” (SMM) is coined, suggesting that sustainability‐conscious factors can become an integral component of morphing matter. In addition, ways to apply sustainability‐conscious factors to augment the existing design pipeline of morphing matter are presented, and more quantitative and algorithmic‐level developments are needed to apply these factors rigorously to the design process.

 

The matrix sensitive weaknesses of Carbon Fiber Reinforced Polymer (CFRP) laminates are usually magnified by mainstream additive manufacturing (AM) methods due to the AM-process-induced voids and defects. In this paper, a novel Magnetic Compaction Force Assisted-Additive Manufacturing (MCFA-AM) method is used to print Carbon Nanofibers (CNF) Z-threaded CFRP (i.e., ZT-CFRP) composite laminates. The MCFA-AM method utilizes a magnetic force to simultaneously support, deposit, and compact Continuous Carbon Fiber Reinforced Polymer (C-CFRP) composites in free space and quickly solidifies the CFRP part without any mold; it effectively reduces the voids. Past research proved that the zig-zag threading pattern of the CNF z-threads reinforces the interlaminar and intralaminar regions in the ZT-CFRP laminates manufactured by the traditional Out of Autoclave-Vacuum Bag Only (OOA-VBO) method, and enhances the matrix sensitive mechanical, thermal, and electrical properties. In this study, the longitudinal compressive test (ASTM D695, i.e., SACMA SRM 1R-94) was performed on the MCFA-AM printed ZT-CFRP laminate. The results were compared with unaligned CNF-modified CFRP (UA-CFRP), control CFRP, and no-pressure CFRP samples’ data to investigate the impact of the CNF z-threads and MCFA-AM process on the CFRP’s performance. The 0.5-bar MCFA-AM printed ZT-CFRP showed comparable longitudinal compressive strength with the 1-bar OOA-VBO cured CFRP. 

Server-level power monitoring in data centers can significantly contribute to its efficient management. Nevertheless, due to the cost of a dedicated power meter for each server, most data center power management only focuses on UPS or cluster-level power monitoring. In this paper, we propose a low-cost novel power monitoring approach that uses only one sensor to extract power consumption information of all servers. We utilize the conducted electromagnetic interference (EMI) of server power supplies to measure their power consumption from non-intrusive single-point voltage measurements. We present a theoretical characterization of conducted EMI generation in server power supply and its propagation through the data center power network. Using a set of ten commercial-grade servers (six Dell PowerEdge and four Lenovo ThinkSystem), we demonstrate that our approach can estimate each server's power consumption with less than ~7% mean absolute error. 

Previous studies have provided evidence that reinforcement of epoxy adhesives with nanostructures such as carbon nanofibers (CNFs) produces higher strength bonded joints between carbon fiber reinforced polymer (CFRP) laminates and shifts bond-line failure modes from the adhesive into the laminate. Despite this, there has been no research dedicated to applying reinforced adhesives to the bonding of nano-reinforced CFRP such as CNF z-threaded carbon fiber reinforced polymer (ZT-CFRP) laminates, which have been proven to exhibit increased interlaminar shear strength, mode-I delamination toughness, and compressive strength over traditional CFRP. This study examined the effectiveness of using CNF reinforced epoxy adhesives for unidirectional ZT-CFRP laminate bonding through single-lap shear tests using the ASTM D5868-01 standard. Unidirectional CFRP laminate samples bonded with both epoxy adhesive and CNF reinforced epoxy adhesive were also tested for comparison. It was found that the average shear strength observed for ZT-CFRP samples bonded with CNF reinforced epoxy adhesive was approximately 44% and 26 % higher than that of CFRP samples bonded with epoxy adhesive and CNF reinforced epoxy adhesive, respectively. Microscopic image analysis was performed to examine the mode of bond failure. The roles of nanomaterials in the fracture mechanism of the adhesives and the composite laminates are also discussed. 

Bacteriophage T4 is decorated with 155 180 Å-long fibers of the highly antigenic outer capsid protein (Hoc). In this study, we describe a near-atomic structural model of Hoc by combining cryo-electron microscopy and AlphaFold structure predictions. It consists of a conserved C-terminal capsid-binding domain attached to a string of three variable immunoglobulin (Ig)-like domains, an architecture well-preserved in hundreds of Hoc molecules found in phage genomes. Each T4-Hoc fiber attaches randomly to the center of gp23* hexameric capsomers in one of the six possible orientations, though at the vertex-proximal hexamers that deviate from 6-fold symmetry, Hoc binds in two preferred orientations related by 180° rotation. Remarkably, each Hoc fiber binds to all six subunits of the capsomer, though the interactions are greatest with three of the subunits, resulting in the off-centered attachment of the C-domain. Biochemical analyses suggest that the acidic Hoc fiber (pI, ~4–5) allows for the clustering of virions in acidic pH and dispersion in neutral/alkaline pH. Hoc appears to have evolved as a sensing device that allows the phage to navigate its movements through reversible clustering–dispersion transitions so that it reaches its destination, the host bacterium, and persists in various ecological niches such as the human/mammalian gut. 

Three-dimensional (3D) printing with continuous carbon-fiber-reinforced polymer (C-CFRP) composites is under increasing development, as it offers more versatility than traditional molding processes, such as the out-of-autoclave-vacuum bag only (OOA-VBO) process. However, due to the layer-by-layer deposition of materials, voids can form between the layers and weaken some of the parts’ properties, such as the interlaminar shear strength (ILSS). In this paper, a novel mold-less magnetic compaction force-assisted additive manufacturing (MCFA-AM) method was used to print carbon nanofiber (CNF) z-threaded CFRP (ZT-CFRP) laminates with significantly improved ILSS and reduced void content compared to traditional C-CFRP laminates, which are printed using a no-pressure 3D-printing process (similar to the fused-deposition-modeling process). The radial flow alignment (RFA) and resin-blending techniques were utilized to manufacture a printing-compatible fast-curing ZT-CFRP prepreg tape to act as the feedstock for a MCFA-AM printhead, which was mounted on a robotic arm. In terms of the ILSS, the MCFA-AM method coupled with ZT-CFRP nanomaterial technology significantly outperformed the C-CFRP made with both the traditional no-pressure 3D-printing process and the OOA-VBO molding process. Furthermore, the mold-less MCFA-AM process more than doubled the production speed of the OOA-VBO molding process. This demonstrates that through the integration of new nanomaterials and 3D-printing techniques, a paradigm shift in C-CFRP manufacturing with significantly better performance, versatility, agility, efficiency, and lower cost is achievable.