Spectral machine vision collects both the spectral and spatial dependence (x,y,λ) of incident light, containing potentially useful information such as chemical composition or micro/nanoscale structure.  However, analyzing the dense 3D hypercubes of information produced by hyperspectral and multispectral imaging causes a data bottleneck and demands tradeoffs in spatial/spectral information, frame rate, and power efficiency. Furthermore, real-time applications like precision agriculture, rescue operations, and battlefields have shifting, unpredictable environments that are challenging for spectroscopy. A spectral imaging detector that can analyze raw data and learn tasks in-situ, rather than sending data out for post-processing, would overcome challenges. No intelligent device that can automatically learn complex spectral recognition tasks has been realized.       UC Berkeley researchers have met this opportunity by developing a novel photodetector capable of learning to perform machine learning analysis and provide ultimate answers in the readout photocurrent. The photodetector automatically learns from example objects to identify new samples. Devices have been experimentally built in both visible and mid-infrared (MIR) bands to perform intelligent tasks from semiconductor wafer metrology to chemometrics. Further calculations indicate 1,000x lower power consumption and 100x higher speed than existing solutions when implemented for hyperspectral imaging analysis, defining a new intelligent photodetection paradigm with intriguing possibilities.

      Microwave impedance microscopy (MIM) is an emerging scanning probe technique that enables non-contact, nanoscale measurement of local complex permittivity. By integrating an ultrasensitive, phase-resolved microwave sensor with a near-field probe, MIM has made significant contributions to diverse fundamental and applied fields. These include strongly correlated and topological materials, two-dimensional and biological systems, as well as semiconductor, acoustic, and MEMS devices. Concurrently, notable progress has been made in refining the MIM technique itself and broadening its capabilities. However, existing literature has focused exclusively on linear MIM based on homodyne architectures, where reflected or transmitted microwave is demodulated and detected at the incident frequency. As such, linear MIM lacks the ability to probe local electrical nonlinearity, which is widely present, for example, in dielectrics, semiconductors, and superconductors. Elucidating such nonlinearity with nanoscale spatial resolution would provide critical insights into semiconductor processing and diagnostics as well as fundamental phenomena like local symmetry breaking and phase separation.       To address this shortcoming, UC Berkeley researchers have introduced a novel methodology and apparatus for performing multi-harmonic MIM to locally probe electrical nonlinearities at the nanoscale. The technique achieves unprecedented spatial and spectral resolution in characterizing complex materials. It encompasses both hardware configurations enabling multi-harmonic data acquisition and the theoretical and calibration protocols to transform raw signals into accurate measures of intrinsic nonlinear permittivity and conductivity. The advance extends existing linear MIM into the nonlinear domain, providing a powerful, versatile, and minimally invasive tool for semiconductor diagnostics, materials research, and device development.

      Pebble bed reactors (PBRs) are an emerging advanced nuclear reactor design where fuel pebbles constantly circulate through the core, as opposed to housing static fuel assemblies, generating numerous advantages including the ability for online refueling versus expensive shutdowns. Online refueling is overall beneficial but poses an operation challenge in that the pebbles must be measured and analyzed for burnup characteristics very quickly (in under 40 seconds), without much time to cool down, challenging the high Purity Germanium (HPGe) detectors historically used for burnup measurements. HPGe detectors can normally only be operated up to tens of thousands of counts per second, far below radiation rates from freshly discharged fuel, and are therefore operated at large distances from sources, with significant shielding. Only a small fraction of detected counts comes from burnup markers, yielding high uncertainty, or can be completely masked by effects of Compton scattering within the detectors.      To overcome the challenges of using HGPe detectors to measure burnup in continuously fueled reactors, UC Berkeley researchers have developed a novel technology capable of measuring gamma rays within a fine energy ranges and without the interference of Compton scattering. The device is also significantly cheaper than HPGe detectors and offers a reduced detector footprint. Nuclides including but not limited to Np-239, Eu-156, and Zr-95 can be measured and analyzed for burnup, path information through the core, and fast and thermal fluence. Furthermore, precise measurement of the Np-239 content provides better data for reactor safeguard purposes. The technology offers meaningful improvements in measurement accuracy, footprint, and cost, for PBRs and other continuously fueled reactors, such as molten salt reactors (MSRs).

      The demand for miniaturized power electronics with increased efficiency and performance motivates the exploration of piezoelectric structures as alternative passive components; piezoelectric components store energy in mechanical compliance and inertia with extremely high quality factors and energy densities significantly greater than those of magnetics at small scales. Recent magnetic-less dc-dc converter designs based on single-port piezoelectric resonators (PRs) have demonstrated power stage efficiencies of 99% and PR power handling densities of up to 5.7 kW/cm3. While marking tremendous milestones, such performance has only been achieved in non-isolated dc-dc converters with mild (2:1) voltage conversion ratios, confining the utility of piezoelectric-based power conversion to a narrow subset of applications.       Piezoelectrics may be expanded to a broader set of applications through use of multi-port piezoelectric transformers (PTs), which offer the same advantages as PRs but with the added potential for galvanic isolation and inherent voltage transformation. The present invention overcomes standing performance shortcomings in isolated magnetic-less PT-based dc-dc converters, providing a framework for high-efficiency piezoelectric transformer (PT) designs (wherein isolated PTs serve as the primary passive components in isolated dc-dc converters). One of the proposed PT designs is validated in a dc-dc power converter prototype and demonstrates a peak efficiency of 97.5%. The measured performance represents a 17x reduction in loss ratio compared to previous isolated magnetic-less PT-based dc-dc converter designs, and expands the value of piezoelectrics to applications requiring isolation.

      Goniophotometers measure the luminance distribution of light emitted or reflected from a point in space or a material sample. Increasingly there is a need for such measurements in real-time, and in real-world situations, for example, for daylight monitoring or harvesting in commercial and residential buildings, design and optimization of greenhouses, and testing laser and display components for AR/VR and autonomous vehicles, to name a few. However, current goniophotometers are ill-suited for real-time measurements; mechanical scanning goniophotometers have a large form factor and slow acquisition times. Parallel goniophotometers take faster measurements but suffer from complexity, expense, and limited angular view ranges (dioptric angular mapping systems) or strict form factor and sample positioning requirements (catadioptric angular mapping systems). Overall, current goniophotometers are therefore limited to in-lab environments.      To overcome these challenges, UC Berkeley researchers have invented an optical sensor  for parallel goniophotometry that is compact, cost-effective, and capable of real-time daylight monitoring. The novel optical design addresses key size and flexibility constraints of current state-of-the-art catadioptric angular mapping systems, while maximizing the view angle measurement at 90°. This camera-like, angular mapping device could be deployed at many points within a building to measure reflected light from fenestrations, in agricultural greenhouses or solar farms for real-time monitoring, and in any industry benefitting from real-time daylight data.

      Probabilistic Seismic Hazard Analysis (PSHA) has become a foundational method for determining seismic design levels and conducting regional seismic risk analyses for insurance risk analysis, governmental hazard mapping, critical infrastructure planning, and more. PSHA traditionally relies on two computationally intensive approaches: Riemann Sum and conventional Monte Carlo (MC) integration. The former requires fine slices across magnitude, distance, and ground motion, and the latter demands extensive synthetic earthquake catalogs. Both approaches become notably resource intensive for low-probability seismic hazards, where achieving a COV of 1% for a 10−4 annual hazard probability may require 108 MC samples.       UC Berkeley researchers have developed an Adaptive Importance Sampling (AIS) PSHA, a novel framework to approximate optimal importance sampling (IS) distributions and dramatically reduce the number of MC samples to estimate hazards. Efficiency and accuracy of the proposed framework have been validated against Pacific Earthquake Engineering Research Center (PEER) PSHA benchmarks covering various seismic sources, including areal, vertical, and dipping faults, as well as combined types. Seismic hazards are calculated up to 3.7×104 and 7.1×103 times faster than Riemann Sum and traditional MC methods, respectively. Coefficients of variation (COVs) are below 1%. Enhanced “smart” AIS PSHA variants are also available that outperform “smart” implementations of Riemann Sum by a factor of up to 130.

      Miniaturization and performance of power electronics is fundamentally limited by magnetic components, whose power densities inherently reduce at small scales. Piezoelectric resonators (PRs), which store energy in the mechanical compliance and inertia of a piezoelectric material, offer various advantages for power conversion including high quality factors, planar form factors, opportunity for batch fabrication, and potential for integration. Contrary to magnetic components, PRs have increased power handling densities at small scales. Noteworthy advancements have been made in magnetic-less, PR-based power converter designs, demonstrating significant achievements in both power density (up to 5.7 kW/cm3) and efficiency (up to >99%). However, while PRs are promising alternative passive components, they cannot be used as drag-and-drop replacements for magnetics; achieving high performance in a PR-based converter requires complicated control of multi-stage switching sequences. A need exists for more practical ways to leverage piezoelectrics in power conversion without such added complexity.      To address this challenge, UC Berkeley researchers have developed a piezoelectric component that may be leveraged to directly emulate the dynamics of a magnetic component. The “active inductor” can serve as a drag-and-drop replacement for bulky magnetic inductors in power converters. Power density and efficiency of underlying piezoelectrics are preserved while the design complexity associated with piezoelectric-based power converters is simplified. Detailed models and control strategies for the piezoelectric-based active inductors have been developed and usage demonstrated in a classic buck converter. The active inductor is further validated with closed-loop simulation results and open-loop experimental results, confirming its inductor-like behavior.

         While nuclear magnetic resonance (NMR) is one of the most universal synthetic chemistry tools for its ability to measure highly specific kinetic and structural information nondestructively/noninvasively, it is costly and low-throughput primarily due to the small sample-size volumes and expensive equipment needed for stringent magnetic field homogeneity. Conversely, zero-to-ultralow field (ZULF) NMR is an emerging alternative offering similar chemical information but relaxing field homogeneity requirements during detection. ZULF NMR has been further propelled by recent advancements in key componentry, optically pumped magnetometers (OPMs), but suffers in scope due to its low sensitivity and its susceptibility to noise. It has not been possible to detect most organic molecules without resorting to hyperpolarization or 13C enrichment using ZULF NMR.         To overcome these challenges, UC Berkeley researchers have developed a multi-channel ZULF spectrometer that greatly improves on both the sensitivity and throughput abilities of state-of-the art ZULF NMR devices. The novel spectrometer was used in the first reported detection of organic molecules in natural isotopic abundance by ZULF NMR, with sensitivity comparable to current commercial benchtop NMR spectrometers. A proof-of-concept multichannel version of the ZULF spectrometer was capable of measuring three distinct chemical samples simultaneously. The combined sensitivity and throughput distinguish the present ZULF NMR spectrometer as a novel chemical analysis tool at unprecedented scales, potentially enabling emerging fields such as robotic chemistry, as well as meeting the demands of existing fields such as chemical manufacturing, agriculture, and pharmaceutical industries.

      Quantum sensing is rapidly reshaping our ability to discern chemical processes with high sensitivity and spatial resolution. Many quantum sensors are based on nitrogen-vacancy (NV) centers in diamond, with nanodiamonds (NDs) providing a promising approach to chemical quantum sensing compared to single crystals for benefits in cost, deployability, and facile integration with the analyte. However, high-precision chemical quantum sensing suffers from large statistical errors from particle heterogeneity, fluorescence fluctuations related to particle orientation, and other unresolved challenges.      To overcome these obstacles, UC Berkeley researchers have developed a novel microfluidic chemical quantum sensing device capable of high-precision, background-free quantum sensing at high-throughput. The microfluidic device solves problems with heterogeneity while simultaneously ensuring close interaction with the analyte. The device further yields exceptional measurement stability, which has been demonstrated over >103s measurement and across ~105 droplets.  Greatly surpassing the stability seen in conventional quantum sensing experiments, these properties are also resistant to experimental variations and temperature shifts. Finally, the required ND sensor volumes are minuscule, costing only about $0.63 for an hour of analysis. 

Plastics are essential for the modern world but are also non-sustainable products of the petrochemical industry that negatively impact our health, environment, and food chain. Natural biogenic plastics, such as polyhydroxyalkanoates (PHA), are readily biodegradable, can be produced more sustainably, and offer an attractive alternative. The global demand for bioplastics is increasing with the 2019 market value of $8.3B expected to reach a compound annual growth rate of 16.1% from 2020-2027 (https://www.grandviewresearch.com/industry-analysis/bioplastics-industry). However, current PHA production is constrained by the underlying physiology of the microorganisms which produce them, meaning bioplastic production is currently limited to inefficient, batch fermentation processes that are difficult to scale.To address this problem, UC Berkeley researchers have developed a new system for PHA production wherein the PHA are generated continuously throughout microorganism growth lifecycles. The invention allows these sustainable bioplastics to be produced via precision continuous fermentation technology, a scalable and efficient approach.

For decades, researchers have been developing “cool roof” materials to cool buildings and save on energy usage from air conditioning. Cool roof materials are engineered to maximize infrared thermal emission, allowing heat to be effectively radiated into outer space and the building to cool down. Conventional cool roof materials emit heat even when it is cold outside, which exacerbates space heating costs and can outweigh energy-saving benefits. A temperature adaptive radiative coating (TARC) material was developed in 2021 that adapts its thermal emittance to ambient temperatures using metal-insulator transitions in vanadium oxide. TARC is projected to outperform existing roof materials in most climate areas, but the complicated structure required high-cost fabrication techniques such as photolithography, pulsed laser deposition, and XeF2 etching, which are not scalable.To address this problem, UC Berkeley researchers have developed a new scalable temperature-adaptive radiative coating (STARC). STARC has the same thermal emittance switching capability as TARC, allowing the thermal emittance to be switched between high- and low- emittance states at a preset temperature. However, STARC can be produced using high-throughput, roll-to-roll methods and low-cost materials. The STARC material also has an improved lifetime. As an added benefit, while cool roof materials are often engineered with uniformly low solar-absorption, the color and solar absorption of STARC can be tuned for aesthetic purposes or to meet local climate-specific needs.

The invention involves a target assembly designed to produce a neutron flux with sufficient flux and energy distribution. This is achieved through accelerator-driven thick target deuteron breakup. The assembly includes a low-Z deuteron breakup target and a supporting structure where the target is located. The deuteron breakup target can be made from materials such as graphite, metallic beryllium, a beryllium-water combination, or liquid lithium. The supporting structure is constructed from materials with high thermal conductivity to manage the high heat flux generated at the target location. This invention represents a significant advancement in neutron target technology, offering versatile applications and improved performance in isotope production and neutron-based research.

The inventors have discovered a new way to generate ultrafast back-gating, by leveraging the surface band bending inherent to many semiconductor materials. This new architecture consists of a standard bulk semiconductor material and a layered material on the surface. Optical pulses generate picosecond time-varying electric fields on the surface material. The inventors have successfully applied this method to a quantum well Rashba system, as this is considered today one of the most promising candidates for spin-based devices, such as the Datta Das spin-transistor. The technology can induce an ultrafast gate and drive time-dependent Rashba and quantum well dynamics never observed before, with switching faster than 10GHz. This approach minimizes lithography and will enable light-driven electronic and spintronics devices such as transistors, spin-transistors, and photo-controlled Rashba circuitry. This method can be applied with minimal effort to any two-dimensional material, for both exfoliated and molecular beam epitaxy grown samples. Electric field gating is one of the most fundamental tuning knobs for all modern solid-state technology, and is the foundation for many solid-state devices such as transistors. Current methods for in-situ back-gated devices are difficult to fabricate, introduce unwanted contaminants, and are unsuited for picosecond time-resolved electric field studies.  

In developed countries, buildings demand a large percentage of a region's energy-generating requirements. This has led to an urgent need for efficient buildings with reduced energy requirements. In office buildings, lighting takes up 20% to 45% of the total energy consumption. Furthermore, the adoption of smart lighting control strategies such as daylight harvesting is shown to reduce lighting energy use by 30% to 50%.For most closed-loop lighting control systems, the real-time data of the daylight level at areas of interest (e.g., the office workbench) are the most important inputs. Current state-of-the-art solutions use dense arrays of luxmeters (photosensors) to monitor the daylight environment inside buildings. The luxmeters are placed on either workbenches, or ceilings and walls near working areas. Digital cameras are used in controlled laboratory environments and occasionally in common buildings to evaluate glare resulting from excessive daylight. The disadvantage of these sensor-based approaches is that they're expensive to install and commission. Additionally, the sample area of these sensors is limited to either the area of the luxmeters or the view of the cameras. Consequently, many sensors are needed to measure the daylight in a large office space.To address this situation, researchers at UC Berkeley developed a portable cyber-physical system for real time, daylight evaluation in buildings, agriculture facilities, and solar farms (collectively referred to as "structures").

Researchers at UC Berkeley have developed techniques for optical voltage sensing of power grids as well voltage sensing within a human or animal subject. The safe, accurate and economical measurement of time-varying voltages in electric power systems poses a significant challenge. Current systems for measuring power grid voltages typically involve instrument transformers. Although these systems are accurate and robust to environmental conditions, they are bulky, heavy, and expensive, thus limiting their use in microgrids and sensing applications. An additional drawback is that some designs explode when they fail. Optical methods for direct measurement of high voltages have gained attention in recent years, mainly due to the high available bandwidth, intrinsic electrical isolation, and the potential for low cost and remote monitoring. Stage of Research The inventors have developed a low-Q resonant optical cavity-based voltage sensor based on a piezoelectric AIN thin film that transduces a voltage applied across the piezo terminals into a change in the resonant frequency of the cavity. This sensor can be fabricated with high yield and low cost (<$1), which makes it uniquely well-suited to reduce the cost of grid voltage measurement.

The inventors have developed a highly scalable multiplexed approach to increase the density of graphene nanoribbon- (GNR) based transistors. The technology forms a single device/chip (scale to 16,000 to >1,000,000 parallel transistors) on a single integrated circuit for single molecule biomolecular sensing, electrical switching, magnetic switching, and logic operations. This work relates to the synthesis and the manufacture of molecular electronic devices, more particularly sensors, switches, and complimentary metal-oxide semiconductor (CMOS) chip-based integrated circuits.Bottom-up synthesized graphene nanoribbons (GNRs) have emerged as one of the most promising materials for post-silicon integrated circuit architectures and have already demonstrated the ability to overcome many of the challenges encountered by devices based on carbon nanotubes or photolithographically patterned graphene. The new field of synthetic electronics borne out of GNRs electronic devices could enable the next generation of electronic circuits and sensors.  

The power demands on data centers are large and increasing rapidly. This is straining data center economic and environment impacts, and in turn driving improvements in data center power efficiencies. Data centers have been widely adopting 48 V intermediate bus architectures due to higher efficiency, good flexibility, and reduced cost. However, a major challenge in such systems is the conversion from the 48 V bus to the extreme low voltage and high current operating levels of server CPUs and GPUs.To address this challenge, UC Berkeley researchers developed a multi-phase hybrid power converter architecture. The Berkeley design uses hybrid converter topologies. A switched-capacitor network is smartly merged with a switched-inductor network, resulting in circuit component number reduction and soft-charging operation of the capacitors. Furthermore, the Berkeley architecture integrates a multi-phase control technique to achieve a higher conversion ratio of the switched-capacitor network, which can further improve the overall system efficiency without increasing the circuit size.  

The inventors have developed two new CasX gene-editing platforms (DpbCasXv2 and PlmCasXv2) through rationale structural engineering of the CasX protein and gRNA, which yield improved in vitro and in vivo behaviors. These platforms dramatically increase DNA cleavage activity and can be used as the basis for further improving CasX tools.The RNA-guided CRISPR-associated (Cas) protein CasX has been reported as a fundamentally distinct, RNA-guided platform compared to Cas9 and Cpf1. Structural studies revealed structural differences within the nucleotide-binding loops of CasX, with a compact protein size less than 1,000 amino acids, and guide RNA (gRNA) scaffold stem. These structural differences affect the active ternary complex assembly, leading to different in vivo and in vitro behaviors of these two enzymes.

This technology combines air layer frictional drag reduction (ALDR) with super hydrophobic surfaces (SHS) to achieve frictional drag reduction of ALDR with significantly reduced gas flux. Thus, enabling increased net energy savings. The stable air layer is achieved with lesser gas flux when utilizing a SHS.Periodic air layers may replenish SHS, enabling drag reduction with reduced energy cost. Combinations of SHS and regular or other non-SHS surface may be used to control spreading of gas, thus facilitating formation of ALDR using discrete gas injection points better than previously achievable. Such surface variations could also be used to preferentially guide gas towards or away from propulsion, depending on desired outcome. By controlling ALDR regionally or globally on a surface, with or without SHS, this technology modifies flow around a hull. This mediates forces on partially or fully submerged objects, enabling control of flow patterns, resistance, steering, and/or dynamics.

Silicon photovoltaic (“Si-PV”) modules currently dominate the solar energy market. Increased progress into Si-PV efficiency enhancements combined with historically low module costs aim to decrease the overall Levelized Cost of Electricity (“LCOE”) to a point competitive with non-renewable energy sources. Despite recent LCOE reductions, Si-PV technology remains economically inferior to fossil fuels. Additionally, flat-plate Si solar modules generally require geographical locations with high direct normal incidence (“DNI”) sunlight conditions in order to maintain module performance. Both the strict DNI requirement and the high LCOE of Si-PV cells ultimately limit the dissemination of solar power into the global energy market. A solution for the capturing of diffuse sunlight includes the use of optical concentrators.  One class of optical concentrators includes luminescent solar concentrators (“LSCs”).  Luminescent solar concentrators have garnered interest due to their ability to utilize diffuse light and their potential for use in architectural applications such as large area power-generating windows. However, LSCs have not yet reached commercialization for photovoltaic power generation, largely due to their comparatively low power conversion efficiencies (“PCEs”) and lack of scalability.     Researchers at UC Berkeley and other educational institutions have developed luminescent solar concentrators that  can be designed to minimize photon thermalization losses and incomplete light trapping using various novel components and techniques.

There are an estimated 130 million wooden poles that support overhead power lines in the US.  Extreme weather, aging, storms or sabotage can all lead to potential damage of these poles and power lines, which can leave large areas without basic necessities.  Due to this risk, it’s anticipated that power utility companies will deploy sensors and corresponding energy harvesters to better respond to potential damage of this critical electricity grid infrastructure. To address this anticipated mass deployment of sensors and harvesters, researchers at UC Berkeley have developed technology improvements to harvesting of electrical energy from energized conductors carrying alternating currents, such as those on overhead and underground power lines (as well as power-supplying conductors in offices and dwellings).  These enhanced harvesters would improve the economics of deploying sensors across a national power grid.  The Berkeley harvesters can readily provide enough power to supply wireless communication devices, energy storage batteries and capacitors, as well as sensors such as accelerometers, particulate matter measuring devices, and atmospheric sensors.

Surface defects dominate the behavior of minority carriers in semiconductors and optoelectronic devices. Photoluminescence quantum yield (QY), which dictates efficiency of optoelectrics such as LEDs, lasers, and solar cells, is extremely low in materials with a large number of surface defects. Researchers at UC Berkeley and Lawrence Berkeley National Laboratory have developed a bis(trifluoromethane) sulfonamide (TFSI) solution for passivation/repair of surface defects in 2D transition metal dichalcogenide (TMDC). This air-stable solution-based chemical treatment provides unmatched photoluminescence QY enhancement to values near 100% without changing the surface morphology. The treatment eliminates defect-mediated non-radiative recombination, which eliminates the low performance limit of TMDC and enhances its minority carrier lifetime. This novel development can address surface passivation in numerous semiconductors which will lead to highly efficient light emitting diodes, lasers and solar cells based on 2D materials.

This invention discloses a new class of materials known as Zeolitic Imidazolate Frameworks (ZIFs). These multivariant ZIFs are composed of transition metal ions (such as Zn or Co) connected by imidazolate linkers in a tetrahedral arrangement, forming three-dimensional crystalline structures. The invention includes methods for synthesizing these ZIFs, enabling precise control over their structural properties, and explores their use in various advanced applications.

As the most reducing and lightest metal, lithium is a desirable battery anode material due to its abilities to yield a high cell voltage and a high specific energy capacity. Lithium ion (Li-ion) battery technology is expected to grow to a $30B industry in the next 5 to 10 years. This growth is largely driven by the introduction of electric vehicles which reached one million plug-in electric vehicles globally in 2015. Problems with Li electrodes have been investigated and challenges remain, including dendrite growth, flammability of organic solvents, and decomposition of the anions at the electrode. To address these challenges, researchers at UC Berkeley are developing single-ion, solid polymer electrolytes as replacements for liquid electrolytes. The investigators have demonstrated a solid-state battery system which uses single-ion conduction and leverages three-dimensional connectivity of polymer networks to provide superior mechanical strength and flexibility which affects bulk conductivity.

Nearly all hydrocarbons are generated from petroleum or natural gas processing. Hydrocarbon mixtures are separated into component fractions at scale for the commercial production of fuels and chemical feedstocks. These large-scale systems use a lot of energy and require many sub-systems with expensive adsorbents or membrane materials like zeolites, polymers, metal oxides, and carbon. Since many of these hydrocarbon mixtures have molecules with similar structures, properties, and reactivities, many of the technical challenges and associated high costs remain. Metal-organic frameworks (MOFs) hold promise for efficient and complex separations based on their desirable surface areas, tunable pore geometries, and adjustable surface functionality. To help align MOFs with challenges in hydrocarbon separations, researchers at UC Berkeley have developed thermally robust and tunable MOF materials which are capable of separating mixtures of saturated, unsaturated, and aromatic hydrocarbons. The researchers have demonstrated the purification of a four component gas-phase mixture.