MAROKO133 Update ai: Korea’s next-gen system enables simultaneous production of hydrogen u

📌 MAROKO133 Breaking ai: Korea’s next-gen system enables simultaneous production o

Researchers in South Korea have developed a next-generation high-efficiency electrochemical system that enables the simultaneous production of hydrogen and value-added chemicals using waste glycerol.

The system reduces energy costs for hydrogen production while enabling the co-production of chemical feedstocks, thereby enhancing the economic viability of green hydrogen.

“This study demonstrates the large-scale synthesis of low-cost, non-precious metal catalysts and validates their performance in commercially relevant electrolyzer systems for the simultaneous production of hydrogen and chemical feedbacks,” said Juchan Yang, principal researcher at Korea Institute of Materials Science.

Key strategy for simultaneously advancing carbon neutrality

Professor Ji-Wook Jang of Ulsan National Institute of Science and Technology stated that technologies that convert bio-derived byproducts such as glycerol into value-added chemicals represent a key strategy for simultaneously advancing carbon neutrality and the hydrogen economy.

Researchers revealed that their study is significant as it replaces the anodic oxygen evolution reaction (OER), a key bottleneck in conventional water electrolysis, thereby reducing the overall cell voltage and improving energy efficiency and expanding the scope of electrochemical conversion technologies.

The research team also pointed out that hydrogen is gaining attention as a key energy source in the carbon-neutral era, and various water electrolysis technologies have been actively developed for its eco-friendly production. However, conventional electrolysis systems suffer from limitations due to the oxygen evolution reaction (OER) at the anode, which requires high energy input and exhibits slow kinetics, thereby reducing overall process efficiency and economic feasibility.

To address these challenges, the research team developed an anion exchange membrane water electrolysis (AEMWE) system that utilizes glycerol as an alternative feedstock and applies the glycerol oxidation reaction (GOR) at the anode as a paired electrolysis strategy. Glycerol, an abundant and low-cost byproduct of biodiesel production, enables the reaction to proceed at lower energy input compared to conventional water electrolysis, according to a press release.

Technology enables simultaneous production of hydrogen

The team also pointed out that this technology enables the simultaneous production of hydrogen and chemical feedstocks such as formate, distinguishing it from conventional water electrolysis processes that produce only hydrogen.

The system achieved a high selectivity of approximately 96% toward the target chemical product (formate), and stable performance was confirmed in a large-area electrolyzer cell of 79 cm², demonstrating its potential for practical industrial applications, as per the release.

Researchers also highlighted that their technology represents a promising electrochemical platform that simultaneously produces hydrogen and chemical feedstocks using waste bio-resources, offering both reduced production costs for green hydrogen and improved resource utilization efficiency.

In particular, it presents a carbon-neutral production strategy that integrates energy and chemical manufacturing processes, with the potential to replace conventional separated production systems. Furthermore, the system is scalable to continuous operation and megawatt (MW)-scale applications, highlighting its potential as a practical technology for industrial deployment, as per the release.

🔗 Sumber: interestingengineering.com

📌 MAROKO133 Eksklusif ai: Railway secures $100 million to challenge AWS with AI-na

Railway, a San Francisco-based cloud platform that has quietly amassed two million developers without spending a dollar on marketing, announced Thursday that it raised $100 million in a Series B funding round, as surging demand for artificial intelligence applications exposes the limitations of legacy cloud infrastructure.

TQ Ventures led the round, with participation from FPV Ventures, Redpoint, and Unusual Ventures. The investment values Railway as one of the most significant infrastructure startups to emerge during the AI boom, capitalizing on developer frustration with the complexity and cost of traditional platforms like Amazon Web Services and Google Cloud.

"As AI models get better at writing code, more and more people are asking the age-old question: where, and how, do I run my applications?" said Jake Cooper, Railway's 28-year-old founder and chief executive, in an exclusive interview with VentureBeat. "The last generation of cloud primitives were slow and outdated, and now with AI moving everything faster, teams simply can't keep up."

The funding is a dramatic acceleration for a company that has charted an unconventional path through the cloud computing industry. Railway raised just $24 million in total before this round, including a $20 million Series A from Redpoint in 2022. The company now processes more than 10 million deployments monthly and handles over one trillion requests through its edge network — metrics that rival far larger and better-funded competitors.

Why three-minute deploy times have become unacceptable in the age of AI coding assistants

Railway's pitch rests on a simple observation: the tools developers use to deploy and manage software were designed for a slower era. A standard build-and-deploy cycle using Terraform, the industry-standard infrastructure tool, takes two to three minutes. That delay, once tolerable, has become a critical bottleneck as AI coding assistants like Claude, ChatGPT, and Cursor can generate working code in seconds.

"When godly intelligence is on tap and can solve any problem in three seconds, those amalgamations of systems become bottlenecks," Cooper told VentureBeat. "What was really cool for humans to deploy in 10 seconds or less is now table stakes for agents."

The company claims its platform delivers deployments in under one second — fast enough to keep pace with AI-generated code. Customers report a tenfold increase in developer velocity and up to 65 percent cost savings compared to traditional cloud providers.

These numbers come directly from enterprise clients, not internal benchmarks. Daniel Lobaton, chief technology officer at G2X, a platform serving 100,000 federal contractors, measured deployment speed improvements of seven times faster and an 87 percent cost reduction after migrating to Railway. His infrastructure bill dropped from $15,000 per month to approximately $1,000.

"The work that used to take me a week on our previous infrastructure, I can do in Railway in like a day," Lobaton said. "If I want to spin up a new service and test different architectures, it would take so long on our old setup. In Railway I can launch six services in two minutes."

Inside the controversial decision to abandon Google Cloud and build data centers from scratch

What distinguishes Railway from competitors like Render and Fly.io is the depth of its vertical integration. In 2024, the company made the unusual decision to abandon Google Cloud entirely and build its own data centers, a move that echoes the famous Alan Kay maxim: "People who are really serious about software should make their own hardware."

"We wanted to design hardware in a way where we could build a differentiated experience," Cooper said. "Having full control over the network, compute, and storage layers lets us do really fast build and deploy loops, the kind that allows us to move at 'agentic speed' while staying 100 percent the smoothest ride in town."

The approach paid dividends during recent widespread outages that affected major cloud providers — Railway remained online throughout.

This soup-to-nuts control enables pricing that undercuts the hyperscalers by roughly 50 percent and newer cloud startups by three to four times. Railway charges by the second for actual compute usage: $0.00000386 per gigabyte-second of memory, $0.00000772 per vCPU-second, and $0.00000006 per gigabyte-second of storage. There are no charges for idle virtual machines — a stark contrast to the traditional cloud model where customers pay for provisioned capacity whether they use it or not.

"The conventional wisdom is that the big guys have economies of scale to offer better pricing," Cooper noted. "But when they're charging for VMs that usually sit idle in the cloud, and we've purpose-built everything to fit much more density on these machines, you have a big opportunity."

How 30 employees built a platform generating tens of millions in annual revenue

Railway has achieved its scale with a team of just 30 employees generating tens of millions in annual revenue — a ratio of revenue per employee that would be exceptional even for established software companies. The company grew revenue 3.5 times last year and continues to expand at 15 percent month-over-month.

Cooper emphasized that the fundraise was strategic rather than necessary. "We're default alive; there's no reason for us to raise money," he said. "We raised because we see a massive opportunity to accelerate, not because we needed to survive."

The company hired its first salesperson only last year and employs just two solutions engineers. Nearly all of Railway's two million users discovered the platform through word of mouth — developers telling other developers about a tool that actually works.

"We basically did the standard engineering thing: if you build it, they will come," Cooper recalled. "And to some degree, they came."

From side projects to Fortune 500 deployments: Railway's unlikely corporate expansion

Despite its grassroots developer community, Railway has made significant inroads into large organizations. The company claims that 31 percent of Fortune 500 companies now use its platform, though deployments range from company-wide infrastructure to individual team projects.

Notable customers include Bilt, the loyalty program company; Intuit's GoCo subsidiary; TripAdvisor's Cruise Critic; and MGM Resorts. Kernel, a Y Combinator-backed startup providing AI infrastructure to over 1,000 companies, runs its entire customer-facing system on Railway for $444 per month.

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🔗 Sumber: venturebeat.com